PETSTEP: Generation of synthetic PET lesions for fast evaluation of segmentation methods

Science.gov (United States)

Berthon, Beatrice; Häggström, Ida; Apte, Aditya; Beattie, Bradley J.; Kirov, Assen S.; Humm, John L.; Marshall, Christopher; Spezi, Emiliano; Larsson, Anne; Schmidtlein, C. Ross

2016-01-01

Purpose This work describes PETSTEP (PET Simulator of Tracers via Emission Projection): a faster and more accessible alternative to Monte Carlo (MC) simulation generating realistic PET images, for studies assessing image features and segmentation techniques. Methods PETSTEP was implemented within Matlab as open source software. It allows generating three-dimensional PET images from PET/CT data or synthetic CT and PET maps, with user-drawn lesions and user-set acquisition and reconstruction parameters. PETSTEP was used to reproduce images of the NEMA body phantom acquired on a GE Discovery 690 PET/CT scanner, and simulated with MC for the GE Discovery LS scanner, and to generate realistic Head and Neck scans. Finally the sensitivity (S) and Positive Predictive Value (PPV) of three automatic segmentation methods were compared when applied to the scanner-acquired and PETSTEP-simulated NEMA images. Results PETSTEP produced 3D phantom and clinical images within 4 and 6 min respectively on a single core 2.7 GHz computer. PETSTEP images of the NEMA phantom had mean intensities within 2% of the scanner-acquired image for both background and largest insert, and 16% larger background Full Width at Half Maximum. Similar results were obtained when comparing PETSTEP images to MC simulated data. The S and PPV obtained with simulated phantom images were statistically significantly lower than for the original images, but led to the same conclusions with respect to the evaluated segmentation methods. Conclusions PETSTEP allows fast simulation of synthetic images reproducing scanner-acquired PET data and shows great promise for the evaluation of PET segmentation methods. PMID:26321409

Feedforward and recurrent processing in scene segmentation: electroencephalography and functional magnetic resonance imaging.

Science.gov (United States)

Scholte, H Steven; Jolij, Jacob; Fahrenfort, Johannes J; Lamme, Victor A F

2008-11-01

In texture segregation, an example of scene segmentation, we can discern two different processes: texture boundary detection and subsequent surface segregation [Lamme, V. A. F., Rodriguez-Rodriguez, V., & Spekreijse, H. Separate processing dynamics for texture elements, boundaries and surfaces in primary visual cortex of the macaque monkey. Cerebral Cortex, 9, 406-413, 1999]. Neural correlates of texture boundary detection have been found in monkey V1 [Sillito, A. M., Grieve, K. L., Jones, H. E., Cudeiro, J., & Davis, J. Visual cortical mechanisms detecting focal orientation discontinuities. Nature, 378, 492-496, 1995; Grosof, D. H., Shapley, R. M., & Hawken, M. J. Macaque-V1 neurons can signal illusory contours. Nature, 365, 550-552, 1993], but whether surface segregation occurs in monkey V1 [Rossi, A. F., Desimone, R., & Ungerleider, L. G. Contextual modulation in primary visual cortex of macaques. Journal of Neuroscience, 21, 1698-1709, 2001; Lamme, V. A. F. The neurophysiology of figure ground segregation in primary visual-cortex. Journal of Neuroscience, 15, 1605-1615, 1995], and whether boundary detection or surface segregation signals can also be measured in human V1, is more controversial [Kastner, S., De Weerd, P., & Ungerleider, L. G. Texture segregation in the human visual cortex: A functional MRI study. Journal of Neurophysiology, 83, 2453-2457, 2000]. Here we present electroencephalography (EEG) and functional magnetic resonance imaging data that have been recorded with a paradigm that makes it possible to differentiate between boundary detection and scene segmentation in humans. In this way, we were able to show with EEG that neural correlates of texture boundary detection are first present in the early visual cortex around 92 msec and then spread toward the parietal and temporal lobes. Correlates of surface segregation first appear in temporal areas (around 112 msec) and from there appear to spread to parietal, and back to occipital areas. After 208

Figure-ground segmentation can occur without attention.

Science.gov (United States)

Kimchi, Ruth; Peterson, Mary A

2008-07-01

The question of whether or not figure-ground segmentation can occur without attention is unresolved. Early theorists assumed it can, but the evidence is scant and open to alternative interpretations. Recent research indicating that attention can influence figure-ground segmentation raises the question anew. We examined this issue by asking participants to perform a demanding change-detection task on a small matrix presented on a task-irrelevant scene of alternating regions organized into figures and grounds by convexity. Independently of any change in the matrix, the figure-ground organization of the scene changed or remained the same. Changes in scene organization produced congruency effects on target-change judgments, even though, when probed with surprise questions, participants could report neither the figure-ground status of the region on which the matrix appeared nor any change in that status. When attending to the scene, participants reported figure-ground status and changes to it highly accurately. These results clearly demonstrate that figure-ground segmentation can occur without focal attention.

3D Aware Correction and Completion of Depth Maps in Piecewise Planar Scenes

KAUST Repository

Thabet, Ali Kassem; Lahoud, Jean; Asmar, Daniel; Ghanem, Bernard

2015-01-01

RGB-D sensors are popular in the computer vision community, especially for problems of scene understanding, semantic scene labeling, and segmentation. However, most of these methods depend on reliable input depth measurements, while discarding

Exploiting current-generation graphics hardware for synthetic-scene generation

Science.gov (United States)

Tanner, Michael A.; Keen, Wayne A.

2010-04-01

Increasing seeker frame rate and pixel count, as well as the demand for higher levels of scene fidelity, have driven scene generation software for hardware-in-the-loop (HWIL) and software-in-the-loop (SWIL) testing to higher levels of parallelization. Because modern PC graphics cards provide multiple computational cores (240 shader cores for a current NVIDIA Corporation GeForce and Quadro cards), implementation of phenomenology codes on graphics processing units (GPUs) offers significant potential for simultaneous enhancement of simulation frame rate and fidelity. To take advantage of this potential requires algorithm implementation that is structured to minimize data transfers between the central processing unit (CPU) and the GPU. In this paper, preliminary methodologies developed at the Kinetic Hardware In-The-Loop Simulator (KHILS) will be presented. Included in this paper will be various language tradeoffs between conventional shader programming, Compute Unified Device Architecture (CUDA) and Open Computing Language (OpenCL), including performance trades and possible pathways for future tool development.

CSIR optronic scene simulator finds real application in self-protection mechanisms of the South African Air Force

CSIR Research Space (South Africa)

Willers, CJ

2010-09-01

Full Text Available The Optronic Scene Simulator (OSSIM) is a second-generation scene simulator that creates synthetic images of arbitrary complex scenes in the visual and infrared (IR) bands, covering the 0.2 to 20 μm spectral region. These images are radiometrically...

Advanced radiometric and interferometric milimeter-wave scene simulations

Science.gov (United States)

Hauss, B. I.; Moffa, P. J.; Steele, W. G.; Agravante, H.; Davidheiser, R.; Samec, T.; Young, S. K.

1993-01-01

Smart munitions and weapons utilize various imaging sensors (including passive IR, active and passive millimeter-wave, and visible wavebands) to detect/identify targets at short standoff ranges and in varied terrain backgrounds. In order to design and evaluate these sensors under a variety of conditions, a high-fidelity scene simulation capability is necessary. Such a capability for passive millimeter-wave scene simulation exists at TRW. TRW's Advanced Radiometric Millimeter-Wave Scene Simulation (ARMSS) code is a rigorous, benchmarked, end-to-end passive millimeter-wave scene simulation code for interpreting millimeter-wave data, establishing scene signatures and evaluating sensor performance. In passive millimeter-wave imaging, resolution is limited due to wavelength and aperture size. Where high resolution is required, the utility of passive millimeter-wave imaging is confined to short ranges. Recent developments in interferometry have made possible high resolution applications on military platforms. Interferometry or synthetic aperture radiometry allows the creation of a high resolution image with a sparsely filled aperture. Borrowing from research work in radio astronomy, we have developed and tested at TRW scene reconstruction algorithms that allow the recovery of the scene from a relatively small number of spatial frequency components. In this paper, the TRW modeling capability is described and numerical results are presented.

Presentation of 3D Scenes Through Video Example.

Science.gov (United States)

Baldacci, Andrea; Ganovelli, Fabio; Corsini, Massimiliano; Scopigno, Roberto

2017-09-01

Using synthetic videos to present a 3D scene is a common requirement for architects, designers, engineers or Cultural Heritage professionals however it is usually time consuming and, in order to obtain high quality results, the support of a film maker/computer animation expert is necessary. We introduce an alternative approach that takes the 3D scene of interest and an example video as input, and automatically produces a video of the input scene that resembles the given video example. In other words, our algorithm allows the user to "replicate" an existing video, on a different 3D scene. We build on the intuition that a video sequence of a static environment is strongly characterized by its optical flow, or, in other words, that two videos are similar if their optical flows are similar. We therefore recast the problem as producing a video of the input scene whose optical flow is similar to the optical flow of the input video. Our intuition is supported by a user-study specifically designed to verify this statement. We have successfully tested our approach on several scenes and input videos, some of which are reported in the accompanying material of this paper.

Superpixel-Based Feature for Aerial Image Scene Recognition

Directory of Open Access Journals (Sweden)

Hongguang Li

2018-01-01

Full Text Available Image scene recognition is a core technology for many aerial remote sensing applications. Different landforms are inputted as different scenes in aerial imaging, and all landform information is regarded as valuable for aerial image scene recognition. However, the conventional features of the Bag-of-Words model are designed using local points or other related information and thus are unable to fully describe landform areas. This limitation cannot be ignored when the aim is to ensure accurate aerial scene recognition. A novel superpixel-based feature is proposed in this study to characterize aerial image scenes. Then, based on the proposed feature, a scene recognition method of the Bag-of-Words model for aerial imaging is designed. The proposed superpixel-based feature that utilizes landform information establishes top-task superpixel extraction of landforms to bottom-task expression of feature vectors. This characterization technique comprises the following steps: simple linear iterative clustering based superpixel segmentation, adaptive filter bank construction, Lie group-based feature quantification, and visual saliency model-based feature weighting. Experiments of image scene recognition are carried out using real image data captured by an unmanned aerial vehicle (UAV. The recognition accuracy of the proposed superpixel-based feature is 95.1%, which is higher than those of scene recognition algorithms based on other local features.

Real-time maritime scene simulation for ladar sensors

Science.gov (United States)

Christie, Chad L.; Gouthas, Efthimios; Swierkowski, Leszek; Williams, Owen M.

2011-06-01

Continuing interest exists in the development of cost-effective synthetic environments for testing Laser Detection and Ranging (ladar) sensors. In this paper we describe a PC-based system for real-time ladar scene simulation of ships and small boats in a dynamic maritime environment. In particular, we describe the techniques employed to generate range imagery accompanied by passive radiance imagery. Our ladar scene generation system is an evolutionary extension of the VIRSuite infrared scene simulation program and includes all previous features such as ocean wave simulation, the physically-realistic representation of boat and ship dynamics, wake generation and simulation of whitecaps, spray, wake trails and foam. A terrain simulation extension is also under development. In this paper we outline the development, capabilities and limitations of the VIRSuite extensions.

Synthetic aperture design for increased SAR image rate

Science.gov (United States)

Bielek, Timothy P [Albuquerque, NM; Thompson, Douglas G [Albuqerque, NM; Walker, Bruce C [Albuquerque, NM

2009-03-03

High resolution SAR images of a target scene at near video rates can be produced by using overlapped, but nevertheless, full-size synthetic apertures. The SAR images, which respectively correspond to the apertures, can be analyzed in sequence to permit detection of movement in the target scene.

The influence of color on emotional perception of natural scenes.

Science.gov (United States)

Codispoti, Maurizio; De Cesarei, Andrea; Ferrari, Vera

2012-01-01

Is color a critical factor when processing the emotional content of natural scenes? Under challenging perceptual conditions, such as when pictures are briefly presented, color might facilitate scene segmentation and/or function as a semantic cue via association with scene-relevant concepts (e.g., red and blood/injury). To clarify the influence of color on affective picture perception, we compared the late positive potentials (LPP) to color versus grayscale pictures, presented for very brief (24 ms) and longer (6 s) exposure durations. Results indicated that removing color information had no effect on the affective modulation of the LPP, regardless of exposure duration. These findings imply that the recognition of the emotional content of scenes, even when presented very briefly, does not critically rely on color information. Copyright © 2011 Society for Psychophysiological Research.

a Super Voxel-Based Riemannian Graph for Multi Scale Segmentation of LIDAR Point Clouds

Science.gov (United States)

Li, Minglei

2018-04-01

Automatically segmenting LiDAR points into respective independent partitions has become a topic of great importance in photogrammetry, remote sensing and computer vision. In this paper, we cast the problem of point cloud segmentation as a graph optimization problem by constructing a Riemannian graph. The scale space of the observed scene is explored by an octree-based over-segmentation with different depths. The over-segmentation produces many super voxels which restrict the structure of the scene and will be used as nodes of the graph. The Kruskal coordinates are used to compute edge weights that are proportional to the geodesic distance between nodes. Then we compute the edge-weight matrix in which the elements reflect the sectional curvatures associated with the geodesic paths between super voxel nodes on the scene surface. The final segmentation results are generated by clustering similar super voxels and cutting off the weak edges in the graph. The performance of this method was evaluated on LiDAR point clouds for both indoor and outdoor scenes. Additionally, extensive comparisons to state of the art techniques show that our algorithm outperforms on many metrics.

Multiple Vehicle Detection and Segmentation in Malaysia Traffic Flow

Science.gov (United States)

Fariz Hasan, Ahmad; Fikri Che Husin, Mohd; Affendi Rosli, Khairul; Norhafiz Hashim, Mohd; Faiz Zainal Abidin, Amar

2018-03-01

Vision based system are widely used in the field of Intelligent Transportation System (ITS) to extract a large amount of information to analyze traffic scenes. By rapid number of vehicles on the road as well as significant increase on cameras dictated the need for traffic surveillance systems. This system can take over the burden some task was performed by human operator in traffic monitoring centre. The main technique proposed by this paper is concentrated on developing a multiple vehicle detection and segmentation focusing on monitoring through Closed Circuit Television (CCTV) video. The system is able to automatically segment vehicle extracted from heavy traffic scene by optical flow estimation alongside with blob analysis technique in order to detect the moving vehicle. Prior to segmentation, blob analysis technique will compute the area of interest region corresponding to moving vehicle which will be used to create bounding box on that particular vehicle. Experimental validation on the proposed system was performed and the algorithm is demonstrated on various set of traffic scene.

A hybrid multiview stereo algorithm for modeling urban scenes.

Science.gov (United States)

Lafarge, Florent; Keriven, Renaud; Brédif, Mathieu; Vu, Hoang-Hiep

2013-01-01

We present an original multiview stereo reconstruction algorithm which allows the 3D-modeling of urban scenes as a combination of meshes and geometric primitives. The method provides a compact model while preserving details: Irregular elements such as statues and ornaments are described by meshes, whereas regular structures such as columns and walls are described by primitives (planes, spheres, cylinders, cones, and tori). We adopt a two-step strategy consisting first in segmenting the initial meshbased surface using a multilabel Markov Random Field-based model and second in sampling primitive and mesh components simultaneously on the obtained partition by a Jump-Diffusion process. The quality of a reconstruction is measured by a multi-object energy model which takes into account both photo-consistency and semantic considerations (i.e., geometry and shape layout). The segmentation and sampling steps are embedded into an iterative refinement procedure which provides an increasingly accurate hybrid representation. Experimental results on complex urban structures and large scenes are presented and compared to state-of-the-art multiview stereo meshing algorithms.

Learning of perceptual grouping for object segmentation on RGB-D data.

Science.gov (United States)

Richtsfeld, Andreas; Mörwald, Thomas; Prankl, Johann; Zillich, Michael; Vincze, Markus

2014-01-01

Object segmentation of unknown objects with arbitrary shape in cluttered scenes is an ambitious goal in computer vision and became a great impulse with the introduction of cheap and powerful RGB-D sensors. We introduce a framework for segmenting RGB-D images where data is processed in a hierarchical fashion. After pre-clustering on pixel level parametric surface patches are estimated. Different relations between patch-pairs are calculated, which we derive from perceptual grouping principles, and support vector machine classification is employed to learn Perceptual Grouping. Finally, we show that object hypotheses generation with Graph-Cut finds a globally optimal solution and prevents wrong grouping. Our framework is able to segment objects, even if they are stacked or jumbled in cluttered scenes. We also tackle the problem of segmenting objects when they are partially occluded. The work is evaluated on publicly available object segmentation databases and also compared with state-of-the-art work of object segmentation.

Event-Based Color Segmentation With a High Dynamic Range Sensor

Directory of Open Access Journals (Sweden)

Alexandre Marcireau

2018-04-01

Full Text Available This paper introduces a color asynchronous neuromorphic event-based camera and a methodology to process color output from the device to perform color segmentation and tracking at the native temporal resolution of the sensor (down to one microsecond. Our color vision sensor prototype is a combination of three Asynchronous Time-based Image Sensors, sensitive to absolute color information. We devise a color processing algorithm leveraging this information. It is designed to be computationally cheap, thus showing how low level processing benefits from asynchronous acquisition and high temporal resolution data. The resulting color segmentation and tracking performance is assessed both with an indoor controlled scene and two outdoor uncontrolled scenes. The tracking's mean error to the ground truth for the objects of the outdoor scenes ranges from two to twenty pixels.

Assessment of synthetic image fidelity

Science.gov (United States)

Mitchell, Kevin D.; Moorhead, Ian R.; Gilmore, Marilyn A.; Watson, Graham H.; Thomson, Mitch; Yates, T.; Troscianko, Tomasz; Tolhurst, David J.

2000-07-01

Computer generated imagery is increasingly used for a wide variety of purposes ranging from computer games to flight simulators to camouflage and sensor assessment. The fidelity required for this imagery is dependent on the anticipated use - for example when used for camouflage design it must be physically correct spectrally and spatially. The rendering techniques used will also depend upon the waveband being simulated, spatial resolution of the sensor and the required frame rate. Rendering of natural outdoor scenes is particularly demanding, because of the statistical variation in materials and illumination, atmospheric effects and the complex geometric structures of objects such as trees. The accuracy of the simulated imagery has tended to be assessed subjectively in the past. First and second order statistics do not capture many of the essential characteristics of natural scenes. Direct pixel comparison would impose an unachievable demand on the synthetic imagery. For many applications, such as camouflage design, it is important that nay metrics used will work in both visible and infrared wavebands. We are investigating a variety of different methods of comparing real and synthetic imagery and comparing synthetic imagery rendered to different levels of fidelity. These techniques will include neural networks (ICA), higher order statistics and models of human contrast perception. This paper will present an overview of the analyses we have carried out and some initial results along with some preliminary conclusions regarding the fidelity of synthetic imagery.

A fusion network for semantic segmentation using RGB-D data

Science.gov (United States)

Yuan, Jiahui; Zhang, Kun; Xia, Yifan; Qi, Lin; Dong, Junyu

2018-04-01

Semantic scene parsing is considerable in many intelligent field, including perceptual robotics. For the past few years, pixel-wise prediction tasks like semantic segmentation with RGB images has been extensively studied and has reached very remarkable parsing levels, thanks to convolutional neural networks (CNNs) and large scene datasets. With the development of stereo cameras and RGBD sensors, it is expected that additional depth information will help improving accuracy. In this paper, we propose a semantic segmentation framework incorporating RGB and complementary depth information. Motivated by the success of fully convolutional networks (FCN) in semantic segmentation field, we design a fully convolutional networks consists of two branches which extract features from both RGB and depth data simultaneously and fuse them as the network goes deeper. Instead of aggregating multiple model, our goal is to utilize RGB data and depth data more effectively in a single model. We evaluate our approach on the NYU-Depth V2 dataset, which consists of 1449 cluttered indoor scenes, and achieve competitive results with the state-of-the-art methods.

Bilevel Optimization for Scene Segmentation of LiDAR Point Cloud

Directory of Open Access Journals (Sweden)

LI Minglei

2018-02-01

Full Text Available The segmentation of point clouds obtained by light detection and ranging (LiDAR systems is a critical step for many tasks,such as data organization,reconstruction and information extraction.In this paper,we propose a bilevel progressive optimization algorithm based on the local differentiability.First,we define the topological relation and distance metric of points in the framework of Riemannian geometry,and in the point-based level using k-means method generates over-segmentation results,e.g.super voxels.Then these voxels are formulated as nodes which consist a minimal spanning tree.High level features are extracted from voxel structures,and a graph-based optimization method is designed to yield the final adaptive segmentation results.The implementation experiments on real data demonstrate that our method is efficient and superior to state-of-the-art methods.

Metric Learning for Hyperspectral Image Segmentation

Science.gov (United States)

Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca

2011-01-01

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

Color-based free-space segmentation using online disparity-supervised learning

NARCIS (Netherlands)

Sanberg, W.P.; Dubbelman, G.; de With, P.H.N.

2015-01-01

This work contributes to vision processing for Advanced Driver Assist Systems (ADAS) and intelligent vehicle applications. We propose a color-only stixel segmentation framework to segment traffic scenes into free, drivable space and obstacles, which has a reduced latency to improve the real-time

Characteristics of nontrauma scene flights for air medical transport.

Science.gov (United States)

Krebs, Margaret G; Fletcher, Erica N; Werman, Howard; McKenzie, Lara B

2014-01-01

Little is known about the use of air medical transport for patients with medical, rather than traumatic, emergencies. This study describes the practices of air transport programs, with respect to nontrauma scene responses, in several areas throughout the United States and Canada. A descriptive, retrospective study was conducted of all nontrauma scene flights from 2008 and 2009. Flight information and patient demographic data were collected from 5 air transport programs. Descriptive statistics were used to examine indications for transport, Glasgow Coma Scale Scores, and loaded miles traveled. A total of 1,785 nontrauma scene flights were evaluated. The percentage of scene flights contributed by nontraumatic emergencies varied between programs, ranging from 0% to 44.3%. The most common indication for transport was cardiac, nonST-segment elevation myocardial infarction (22.9%). Cardiac arrest was the indication for transport in 2.5% of flights. One air transport program reported a high percentage (49.4) of neurologic, stroke, flights. The use of air transport for nontraumatic emergencies varied considerably between various air transport programs and regions. More research is needed to evaluate which nontraumatic emergencies benefit from air transport. National guidelines regarding the use of air transport for nontraumatic emergencies are needed. Copyright © 2014 Air Medical Journal Associates. Published by Elsevier Inc. All rights reserved.

Validity and reliability of naturalistic driving scene categorization Judgments from crowdsourcing.

Science.gov (United States)

Cabrall, Christopher D D; Lu, Zhenji; Kyriakidis, Miltos; Manca, Laura; Dijksterhuis, Chris; Happee, Riender; de Winter, Joost

2018-05-01

A common challenge with processing naturalistic driving data is that humans may need to categorize great volumes of recorded visual information. By means of the online platform CrowdFlower, we investigated the potential of crowdsourcing to categorize driving scene features (i.e., presence of other road users, straight road segments, etc.) at greater scale than a single person or a small team of researchers would be capable of. In total, 200 workers from 46 different countries participated in 1.5days. Validity and reliability were examined, both with and without embedding researcher generated control questions via the CrowdFlower mechanism known as Gold Test Questions (GTQs). By employing GTQs, we found significantly more valid (accurate) and reliable (consistent) identification of driving scene items from external workers. Specifically, at a small scale CrowdFlower Job of 48 three-second video segments, an accuracy (i.e., relative to the ratings of a confederate researcher) of 91% on items was found with GTQs compared to 78% without. A difference in bias was found, where without GTQs, external workers returned more false positives than with GTQs. At a larger scale CrowdFlower Job making exclusive use of GTQs, 12,862 three-second video segments were released for annotation. Infeasible (and self-defeating) to check the accuracy of each at this scale, a random subset of 1012 categorizations was validated and returned similar levels of accuracy (95%). In the small scale Job, where full video segments were repeated in triplicate, the percentage of unanimous agreement on the items was found significantly more consistent when using GTQs (90%) than without them (65%). Additionally, in the larger scale Job (where a single second of a video segment was overlapped by ratings of three sequentially neighboring segments), a mean unanimity of 94% was obtained with validated-as-correct ratings and 91% with non-validated ratings. Because the video segments overlapped in full for

A Virtual Environments Editor for Driving Scenes

Directory of Open Access Journals (Sweden)

Ronald R. Mourant

2003-12-01

Full Text Available The goal of this project was to enable the rapid creation of three-dimensional virtual driving environments. We designed and implemented a high-level scene editor that allows a user to construct a driving environment by pasting icons that represent 1 road segments, 2 road signs, 3 trees and 4 buildings. These icons represent two- and three-dimensional objects that have been predesigned. Icons can be placed in the scene at specific locations (x, y, and z coordinates. The editor includes the capability of a user to "drive" a vehicle using a computer mouse for steering, accelerating and braking. At any time during the process of building a virtual environment, a user may switch to "Run Mode" and inspect the three-dimensional scene by "driving" through it using the mouse. Adjustments and additions can be made to the virtual environment by going back to "Build Mode". Once a user is satisfied with the threedimensional virtual environment, it can be saved in a file. The file can used with Java3D software that enables the traversing of three-dimensional environments. The process of building virtual environments from predesigned icons can be applied to many other application areas. It will enable novice computer users to rapidly construct and use three-dimensional virtual environments.

3D Aware Correction and Completion of Depth Maps in Piecewise Planar Scenes

KAUST Repository

Thabet, Ali Kassem

2015-04-16

RGB-D sensors are popular in the computer vision community, especially for problems of scene understanding, semantic scene labeling, and segmentation. However, most of these methods depend on reliable input depth measurements, while discarding unreliable ones. This paper studies how reliable depth values can be used to correct the unreliable ones, and how to complete (or extend) the available depth data beyond the raw measurements of the sensor (i.e. infer depth at pixels with unknown depth values), given a prior model on the 3D scene. We consider piecewise planar environments in this paper, since many indoor scenes with man-made objects can be modeled as such. We propose a framework that uses the RGB-D sensor’s noise profile to adaptively and robustly fit plane segments (e.g. floor and ceiling) and iteratively complete the depth map, when possible. Depth completion is formulated as a discrete labeling problem (MRF) with hard constraints and solved efficiently using graph cuts. To regularize this problem, we exploit 3D and appearance cues that encourage pixels to take on depth values that will be compatible in 3D to the piecewise planar assumption. Extensive experiments, on a new large-scale and challenging dataset, show that our approach results in more accurate depth maps (with 20 % more depth values) than those recorded by the RGB-D sensor. Additional experiments on the NYUv2 dataset show that our method generates more 3D aware depth. These generated depth maps can also be used to improve the performance of a state-of-the-art RGB-D SLAM method.

[The segmentation of urinary cells--a first step in the automated processing in urine cytology (author's transl)].

Science.gov (United States)

Liedtke, C E; Aeikens, B

1980-01-01

By segmentation of cell images we understand the automated decomposition of microscopic cell scenes into nucleus, plasma and background. A segmentation is achieved by using information from the microscope image and prior knowledge about the content of the scene. Different algorithms have been investigated and applied to samples of urothelial cells. A particular algorithm based on a histogram approach which can be easily implemented in hardware is discussed in more detail.

Combining segmentation and attention: a new foveal attention model

Directory of Open Access Journals (Sweden)

Rebeca eMarfil

2014-08-01

Full Text Available Artificial vision systems cannot process all the information that they receive from the world in real time because it is highly expensive and inefficient in terms of computational cost. Inspired by biological perception systems, articial attention models pursuit to select only the relevant part of the scene. Besides, it is well established that the units of attention on human vision are not merely spatial but closely related to perceptual objects (proto-objects. This implies a strong bidirectional relationship between segmentation and attention processes. Therefore, while the segmentation process is the responsible to extract the proto-objects from the scene, attention can guide segmentation, arising the concept of foveal attention. When the focus of attention is deployed from one visual unit to another, the rest of the scene is perceived but at a lower resolution that the focused object. The result is a multi-resolution visual perception in which the fovea, a dimple on the central retina, provides the highest resolution vision. In this paper, a bottom-up foveal attention model is presented. In this model the input image is a foveal image represented using a Cartesian Foveal Geometry (CFG, which encodes the field of view of the sensor as a fovea (placed in the focus of attention surrounded by a set of concentric rings with decreasing resolution. Then multirresolution perceptual segmentation is performed by building a foveal polygon using the Bounded Irregular Pyramid (BIP. Bottom-up attention is enclosed in the same structure, allowing to set the fovea over the most salient image proto-object. Saliency is computed as a linear combination of multiple low level features such us colour and intensity contrast, symmetry, orientation and roundness. Obtained results from natural images show that the performance of the combination of hierarchical foveal segmentation and saliency estimation is good in terms of accuracy and speed.

Complex scenes and situations visualization in hierarchical learning algorithm with dynamic 3D NeoAxis engine

Science.gov (United States)

Graham, James; Ternovskiy, Igor V.

2013-06-01

We applied a two stage unsupervised hierarchical learning system to model complex dynamic surveillance and cyber space monitoring systems using a non-commercial version of the NeoAxis visualization software. The hierarchical scene learning and recognition approach is based on hierarchical expectation maximization, and was linked to a 3D graphics engine for validation of learning and classification results and understanding the human - autonomous system relationship. Scene recognition is performed by taking synthetically generated data and feeding it to a dynamic logic algorithm. The algorithm performs hierarchical recognition of the scene by first examining the features of the objects to determine which objects are present, and then determines the scene based on the objects present. This paper presents a framework within which low level data linked to higher-level visualization can provide support to a human operator and be evaluated in a detailed and systematic way.

Estimating the number of people in crowded scenes

Science.gov (United States)

Kim, Minjin; Kim, Wonjun; Kim, Changick

2011-01-01

This paper presents a method to estimate the number of people in crowded scenes without using explicit object segmentation or tracking. The proposed method consists of three steps as follows: (1) extracting space-time interest points using eigenvalues of the local spatio-temporal gradient matrix, (2) generating crowd regions based on space-time interest points, and (3) estimating the crowd density based on the multiple regression. In experimental results, the efficiency and robustness of our proposed method are demonstrated by using PETS 2009 dataset.

Depth estimation of complex geometry scenes from light fields

Science.gov (United States)

Si, Lipeng; Wang, Qing

2018-01-01

The surface camera (SCam) of light fields gathers angular sample rays passing through a 3D point. The consistency of SCams is evaluated to estimate the depth map of scene. But the consistency is affected by several limitations such as occlusions or non-Lambertian surfaces. To solve those limitations, the SCam is partitioned into two segments that one of them could satisfy the consistency constraint. The segmentation pattern of SCam is highly related to the texture of spatial patch, so we enforce a mask matching to describe the shape correlation between segments of SCam and spatial patch. To further address the ambiguity in textureless region, a global method with pixel-wise plane label is presented. Plane label inference at each pixel can recover not only depth value but also local geometry structure, that is suitable for light fields with sub-pixel disparities and continuous view variation. Our method is evaluated on public light field datasets and outperforms the state-of-the-art.

Near-Space TOPSAR Large-Scene Full-Aperture Imaging Scheme Based on Two-Step Processing

Directory of Open Access Journals (Sweden)

Qianghui Zhang

2016-07-01

Full Text Available Free of the constraints of orbit mechanisms, weather conditions and minimum antenna area, synthetic aperture radar (SAR equipped on near-space platform is more suitable for sustained large-scene imaging compared with the spaceborne and airborne counterparts. Terrain observation by progressive scans (TOPS, which is a novel wide-swath imaging mode and allows the beam of SAR to scan along the azimuth, can reduce the time of echo acquisition for large scene. Thus, near-space TOPS-mode SAR (NS-TOPSAR provides a new opportunity for sustained large-scene imaging. An efficient full-aperture imaging scheme for NS-TOPSAR is proposed in this paper. In this scheme, firstly, two-step processing (TSP is adopted to eliminate the Doppler aliasing of the echo. Then, the data is focused in two-dimensional frequency domain (FD based on Stolt interpolation. Finally, a modified TSP (MTSP is performed to remove the azimuth aliasing. Simulations are presented to demonstrate the validity of the proposed imaging scheme for near-space large-scene imaging application.

Scene incongruity and attention.

Science.gov (United States)

Mack, Arien; Clarke, Jason; Erol, Muge; Bert, John

2017-02-01

Does scene incongruity, (a mismatch between scene gist and a semantically incongruent object), capture attention and lead to conscious perception? We explored this question using 4 different procedures: Inattention (Experiment 1), Scene description (Experiment 2), Change detection (Experiment 3), and Iconic Memory (Experiment 4). We found no differences between scene incongruity and scene congruity in Experiments 1, 2, and 4, although in Experiment 3 change detection was faster for scenes containing an incongruent object. We offer an explanation for why the change detection results differ from the results of the other three experiments. In all four experiments, participants invariably failed to report the incongruity and routinely mis-described it by normalizing the incongruent object. None of the results supports the claim that semantic incongruity within a scene invariably captures attention and provide strong evidence of the dominant role of scene gist in determining what is perceived. Copyright © 2016 Elsevier Inc. All rights reserved.

PC Scene Generation

Science.gov (United States)

Buford, James A., Jr.; Cosby, David; Bunfield, Dennis H.; Mayhall, Anthony J.; Trimble, Darian E.

2007-04-01

AMRDEC has successfully tested hardware and software for Real-Time Scene Generation for IR and SAL Sensors on COTS PC based hardware and video cards. AMRDEC personnel worked with nVidia and Concurrent Computer Corporation to develop a Scene Generation system capable of frame rates of at least 120Hz while frame locked to an external source (such as a missile seeker) with no dropped frames. Latency measurements and image validation were performed using COTS and in-house developed hardware and software. Software for the Scene Generation system was developed using OpenSceneGraph.

Gamifying Video Object Segmentation.

Science.gov (United States)

Spampinato, Concetto; Palazzo, Simone; Giordano, Daniela

2017-10-01

Video object segmentation can be considered as one of the most challenging computer vision problems. Indeed, so far, no existing solution is able to effectively deal with the peculiarities of real-world videos, especially in cases of articulated motion and object occlusions; limitations that appear more evident when we compare the performance of automated methods with the human one. However, manually segmenting objects in videos is largely impractical as it requires a lot of time and concentration. To address this problem, in this paper we propose an interactive video object segmentation method, which exploits, on one hand, the capability of humans to identify correctly objects in visual scenes, and on the other hand, the collective human brainpower to solve challenging and large-scale tasks. In particular, our method relies on a game with a purpose to collect human inputs on object locations, followed by an accurate segmentation phase achieved by optimizing an energy function encoding spatial and temporal constraints between object regions as well as human-provided location priors. Performance analysis carried out on complex video benchmarks, and exploiting data provided by over 60 users, demonstrated that our method shows a better trade-off between annotation times and segmentation accuracy than interactive video annotation and automated video object segmentation approaches.

Segmentation of color images by chromaticity features using self-organizing maps

Directory of Open Access Journals (Sweden)

Farid García-Lamont

2016-05-01

Full Text Available Usually, the segmentation of color images is performed using cluster-based methods and the RGB space to represent the colors. The drawback with these methods is the a priori knowledge of the number of groups, or colors, in the image; besides, the RGB space issensitive to the intensity of the colors. Humans can identify different sections within a scene by the chromaticity of its colors of, as this is the feature humans employ to tell them apart. In this paper, we propose to emulate the human perception of color by training a self-organizing map (SOM with samples of chromaticity of different colors. The image to process is mapped to the HSV space because in this space the chromaticity is decoupled from the intensity, while in the RGB space this is not possible. Our proposal does not require knowing a priori the number of colors within a scene, and non-uniform illumination does not significantly affect the image segmentation. We present experimental results using some images from the Berkeley segmentation database by employing SOMs with different sizes, which are segmented successfully using only chromaticity features.

Content metamorphosis in synthetic holography

International Nuclear Information System (INIS)

Desbiens, Jacques

2013-01-01

A synthetic hologram is an optical system made of hundreds of images amalgamated in a structure of holographic cells. Each of these images represents a point of view on a three-dimensional space which makes us consider synthetic holography as a multiple points of view perspective system. In the composition of a computer graphics scene for a synthetic hologram, the field of view of the holographic image can be divided into several viewing zones. We can attribute these divisions to any object or image feature independently and operate different transformations on image content. In computer generated holography, we tend to consider content variations as a continuous animation much like a short movie. However, by composing sequential variations of image features in relation with spatial divisions, we can build new narrative forms distinct from linear cinematographic narration. When observers move freely and change their viewing positions, they travel from one field of view division to another. In synthetic holography, metamorphoses of image content are within the observer's path. In all imaging Medias, the transformation of image features in synchronisation with the observer's position is a rare occurrence. However, this is a predominant characteristic of synthetic holography. This paper describes some of my experimental works in the development of metamorphic holographic images.

An unsupervised strategy for biomedical image segmentation

Directory of Open Access Journals (Sweden)

Roberto Rodríguez

2010-09-01

Full Text Available Roberto Rodríguez1, Rubén Hernández21Digital Signal Processing Group, Institute of Cybernetics, Mathematics, and Physics, Havana, Cuba; 2Interdisciplinary Professional Unit of Engineering and Advanced Technology, IPN, MexicoAbstract: Many segmentation techniques have been published, and some of them have been widely used in different application problems. Most of these segmentation techniques have been motivated by specific application purposes. Unsupervised methods, which do not assume any prior scene knowledge can be learned to help the segmentation process, and are obviously more challenging than the supervised ones. In this paper, we present an unsupervised strategy for biomedical image segmentation using an algorithm based on recursively applying mean shift filtering, where entropy is used as a stopping criterion. This strategy is proven with many real images, and a comparison is carried out with manual segmentation. With the proposed strategy, errors less than 20% for false positives and 0% for false negatives are obtained.Keywords: segmentation, mean shift, unsupervised segmentation, entropy

An LG-graph-based early evaluation of segmented images

International Nuclear Information System (INIS)

Tsitsoulis, Athanasios; Bourbakis, Nikolaos

2012-01-01

Image segmentation is one of the first important parts of image analysis and understanding. Evaluation of image segmentation, however, is a very difficult task, mainly because it requires human intervention and interpretation. In this work, we propose a blind reference evaluation scheme based on regional local–global (RLG) graphs, which aims at measuring the amount and distribution of detail in images produced by segmentation algorithms. The main idea derives from the field of image understanding, where image segmentation is often used as a tool for scene interpretation and object recognition. Evaluation here derives from summarization of the structural information content and not from the assessment of performance after comparisons with a golden standard. Results show measurements for segmented images acquired from three segmentation algorithms, applied on different types of images (human faces/bodies, natural environments and structures (buildings)). (paper)

Super-Resolution for Synthetic Zooming

Directory of Open Access Journals (Sweden)

Li Xin

2006-01-01

Full Text Available Optical zooming is an important feature of imaging systems. In this paper, we investigate a low-cost signal processing alternative to optical zooming—synthetic zooming by super-resolution (SR techniques. Synthetic zooming is achieved by registering a sequence of low-resolution (LR images acquired at varying focal lengths and reconstructing the SR image at a larger focal length or increased spatial resolution. Under the assumptions of constant scene depth and zooming speed, we argue that the motion trajectories of all physical points are related to each other by a unique vanishing point and present a robust technique for estimating its D coordinate. Such a line-geometry-based registration is the foundation of SR for synthetic zooming. We address the issue of data inconsistency arising from the varying focal length of optical lens during the zooming process. To overcome the difficulty of data inconsistency, we propose a two-stage Delaunay-triangulation-based interpolation for fusing the LR image data. We also present a PDE-based nonlinear deblurring to accommodate the blindness and variation of sensor point spread functions. Simulation results with real-world images have verified the effectiveness of the proposed SR techniques for synthetic zooming.

Visual cues in low-level flight - Implications for pilotage, training, simulation, and enhanced/synthetic vision systems

Science.gov (United States)

Foyle, David C.; Kaiser, Mary K.; Johnson, Walter W.

1992-01-01

This paper reviews some of the sources of visual information that are available in the out-the-window scene and describes how these visual cues are important for routine pilotage and training, as well as the development of simulator visual systems and enhanced or synthetic vision systems for aircraft cockpits. It is shown how these visual cues may change or disappear under environmental or sensor conditions, and how the visual scene can be augmented by advanced displays to capitalize on the pilot's excellent ability to extract visual information from the visual scene.

Convolutional Neural Networks for SAR Image Segmentation

DEFF Research Database (Denmark)

Malmgren-Hansen, David; Nobel-Jørgensen, Morten

2015-01-01

Segmentation of Synthetic Aperture Radar (SAR) images has several uses, but it is a difficult task due to a number of properties related to SAR images. In this article we show how Convolutional Neural Networks (CNNs) can easily be trained for SAR image segmentation with good results. Besides...

Synthetic-aperture radar imaging through dispersive media

International Nuclear Information System (INIS)

Varslot, Trond; Morales, J Héctor; Cheney, Margaret

2010-01-01

In this paper we develop a method for synthetic-aperture radar (SAR) imaging through a dispersive medium. We consider the case when the sensor and scatterers are embedded in a known homogeneous dispersive material, the scene to be imaged lies on a known surface and the radar antenna flight path is an arbitrary but known smooth curve. The scattering is modeled using a linearized (Born) scalar model. We assume that the measurements are polluted with additive noise. Furthermore, we assume that we have prior knowledge about the power-spectral densities of the scene and the noise. This leads us to formulate the problem in a statistical framework. We develop a filtered-back-projection imaging algorithm in which we choose the filter according to the statistical properties of the scene and noise. We present numerical simulations for a case where the scene consists of point-like scatterers located on the ground, and demonstrate how the ability to resolve the targets depends on a quantity which we call the noise-to-target ratio. In our simulations, the dispersive material is modeled with the Fung–Ulaby equations for leafy vegetation. However, the method is also applicable to other dielectric materials where the dispersion is considered relevant in the frequency range of the transmitted signals

Categorization of natural dynamic audiovisual scenes.

Directory of Open Access Journals (Sweden)

Olli Rummukainen

Full Text Available This work analyzed the perceptual attributes of natural dynamic audiovisual scenes. We presented thirty participants with 19 natural scenes in a similarity categorization task, followed by a semi-structured interview. The scenes were reproduced with an immersive audiovisual display. Natural scene perception has been studied mainly with unimodal settings, which have identified motion as one of the most salient attributes related to visual scenes, and sound intensity along with pitch trajectories related to auditory scenes. However, controlled laboratory experiments with natural multimodal stimuli are still scarce. Our results show that humans pay attention to similar perceptual attributes in natural scenes, and a two-dimensional perceptual map of the stimulus scenes and perceptual attributes was obtained in this work. The exploratory results show the amount of movement, perceived noisiness, and eventfulness of the scene to be the most important perceptual attributes in naturalistically reproduced real-world urban environments. We found the scene gist properties openness and expansion to remain as important factors in scenes with no salient auditory or visual events. We propose that the study of scene perception should move forward to understand better the processes behind multimodal scene processing in real-world environments. We publish our stimulus scenes as spherical video recordings and sound field recordings in a publicly available database.

Scene Integration Without Awareness: No Conclusive Evidence for Processing Scene Congruency During Continuous Flash Suppression.

Science.gov (United States)

Moors, Pieter; Boelens, David; van Overwalle, Jaana; Wagemans, Johan

2016-07-01

A recent study showed that scenes with an object-background relationship that is semantically incongruent break interocular suppression faster than scenes with a semantically congruent relationship. These results implied that semantic relations between the objects and the background of a scene could be extracted in the absence of visual awareness of the stimulus. In the current study, we assessed the replicability of this finding and tried to rule out an alternative explanation dependent on low-level differences between the stimuli. Furthermore, we used a Bayesian analysis to quantify the evidence in favor of the presence or absence of a scene-congruency effect. Across three experiments, we found no convincing evidence for a scene-congruency effect or a modulation of scene congruency by scene inversion. These findings question the generalizability of previous observations and cast doubt on whether genuine semantic processing of object-background relationships in scenes can manifest during interocular suppression. © The Author(s) 2016.

Error Detection, Factorization and Correction for Multi-View Scene Reconstruction from Aerial Imagery

Energy Technology Data Exchange (ETDEWEB)

Hess-Flores, Mauricio [Univ. of California, Davis, CA (United States)

2011-11-10

reconstruction pre-processing, where an algorithm detects and discards frames that would lead to inaccurate feature matching, camera pose estimation degeneracies or mathematical instability in structure computation based on a residual error comparison between two different match motion models. The presented algorithms were designed for aerial video but have been proven to work across different scene types and camera motions, and for both real and synthetic scenes.

Efficacy of novel synthetic bone substitutes in the reconstruction of large segmental bone defects in sheep tibiae

International Nuclear Information System (INIS)

Li, Jiao Jiao; Roohani-Esfahani, Seyed-Iman; Dunstan, Colin R; Quach, Terrence; Zreiqat, Hala; Steck, Roland; Saifzadeh, Siamak; Pivonka, Peter

2016-01-01

The treatment of large bone defects, particularly those with segmental bone loss, remains a significant clinical challenge as current approaches involving surgery or bone grafting often do not yield satisfactory long-term outcomes. This study reports the evaluation of novel ceramic scaffolds applied as bone graft substitutes in a clinically relevant in vivo model. Baghdadite scaffolds, unmodified or modified with a polycaprolactone coating containing bioactive glass nanoparticles, were implanted into critical-sized segmental bone defects in sheep tibiae for 26 weeks. Radiographic, biomechanical, μ-CT and histological analyses showed that both unmodified and modified baghdadite scaffolds were able to withstand physiological loads at the defect site, and induced substantial bone formation in the absence of supplementation with cells or growth factors. Notably, all samples showed significant bridging of the critical-sized defect (average 80%) with evidence of bone infiltration and remodelling within the scaffold implant. The unmodified and modified baghdadite scaffolds achieved similar outcomes of defect repair, although the latter may have an initial mechanical advantage due to the nanocomposite coating. The baghdadite scaffolds evaluated in this study hold potential for use as purely synthetic bone graft substitutes in the treatment of large bone defects while circumventing the drawbacks of autografts and allografts. (paper)

Scene construction in schizophrenia.

Science.gov (United States)

Raffard, Stéphane; D'Argembeau, Arnaud; Bayard, Sophie; Boulenger, Jean-Philippe; Van der Linden, Martial

2010-09-01

Recent research has revealed that schizophrenia patients are impaired in remembering the past and imagining the future. In this study, we examined patients' ability to engage in scene construction (i.e., the process of mentally generating and maintaining a complex and coherent scene), which is a key part of retrieving past experiences and episodic future thinking. 24 participants with schizophrenia and 25 healthy controls were asked to imagine new fictitious experiences and described their mental representations of the scenes in as much detail as possible. Descriptions were scored according to various dimensions (e.g., sensory details, spatial reference), and participants also provided ratings of their subjective experience when imagining the scenes (e.g., their sense of presence, the perceived similarity of imagined events to past experiences). Imagined scenes contained less phenomenological details (d = 1.11) and were more fragmented (d = 2.81) in schizophrenia patients compared to controls. Furthermore, positive symptoms were positively correlated to the sense of presence (r = .43) and the perceived similarity of imagined events to past episodes (r = .47), whereas negative symptoms were negatively related to the overall richness of the imagined scenes (r = -.43). The results suggest that schizophrenic patients' impairments in remembering the past and imagining the future are, at least in part, due to deficits in the process of scene construction. The relationships between the characteristics of imagined scenes and positive and negative symptoms could be related to reality monitoring deficits and difficulties in strategic retrieval processes, respectively. Copyright 2010 APA, all rights reserved.

Magnetic Resonance–Based Automatic Air Segmentation for Generation of Synthetic Computed Tomography Scans in the Head Region

Energy Technology Data Exchange (ETDEWEB)

Zheng, Weili; Kim, Joshua P. [Department of Radiation Oncology, Henry Ford Health Systems, Detroit, Michigan (United States); Kadbi, Mo [Philips Healthcare, Cleveland, Ohio (United States); Movsas, Benjamin; Chetty, Indrin J. [Department of Radiation Oncology, Henry Ford Health Systems, Detroit, Michigan (United States); Glide-Hurst, Carri K., E-mail: churst2@hfhs.org [Department of Radiation Oncology, Henry Ford Health Systems, Detroit, Michigan (United States)

2015-11-01

Purpose: To incorporate a novel imaging sequence for robust air and tissue segmentation using ultrashort echo time (UTE) phase images and to implement an innovative synthetic CT (synCT) solution as a first step toward MR-only radiation therapy treatment planning for brain cancer. Methods and Materials: Ten brain cancer patients were scanned with a UTE/Dixon sequence and other clinical sequences on a 1.0 T open magnet with simulation capabilities. Bone-enhanced images were generated from a weighted combination of water/fat maps derived from Dixon images and inverted UTE images. Automated air segmentation was performed using unwrapped UTE phase maps. Segmentation accuracy was assessed by calculating segmentation errors (true-positive rate, false-positive rate, and Dice similarity indices using CT simulation (CT-SIM) as ground truth. The synCTs were generated using a voxel-based, weighted summation method incorporating T2, fluid attenuated inversion recovery (FLAIR), UTE1, and bone-enhanced images. Mean absolute error (MAE) characterized Hounsfield unit (HU) differences between synCT and CT-SIM. A dosimetry study was conducted, and differences were quantified using γ-analysis and dose-volume histogram analysis. Results: On average, true-positive rate and false-positive rate for the CT and MR-derived air masks were 80.8% ± 5.5% and 25.7% ± 6.9%, respectively. Dice similarity indices values were 0.78 ± 0.04 (range, 0.70-0.83). Full field of view MAE between synCT and CT-SIM was 147.5 ± 8.3 HU (range, 138.3-166.2 HU), with the largest errors occurring at bone–air interfaces (MAE 422.5 ± 33.4 HU for bone and 294.53 ± 90.56 HU for air). Gamma analysis revealed pass rates of 99.4% ± 0.04%, with acceptable treatment plan quality for the cohort. Conclusions: A hybrid MRI phase/magnitude UTE image processing technique was introduced that significantly improved bone and air contrast in MRI. Segmented air masks and bone-enhanced images were integrated

Magnetic Resonance–Based Automatic Air Segmentation for Generation of Synthetic Computed Tomography Scans in the Head Region

International Nuclear Information System (INIS)

Zheng, Weili; Kim, Joshua P.; Kadbi, Mo; Movsas, Benjamin; Chetty, Indrin J.; Glide-Hurst, Carri K.

2015-01-01

Purpose: To incorporate a novel imaging sequence for robust air and tissue segmentation using ultrashort echo time (UTE) phase images and to implement an innovative synthetic CT (synCT) solution as a first step toward MR-only radiation therapy treatment planning for brain cancer. Methods and Materials: Ten brain cancer patients were scanned with a UTE/Dixon sequence and other clinical sequences on a 1.0 T open magnet with simulation capabilities. Bone-enhanced images were generated from a weighted combination of water/fat maps derived from Dixon images and inverted UTE images. Automated air segmentation was performed using unwrapped UTE phase maps. Segmentation accuracy was assessed by calculating segmentation errors (true-positive rate, false-positive rate, and Dice similarity indices using CT simulation (CT-SIM) as ground truth. The synCTs were generated using a voxel-based, weighted summation method incorporating T2, fluid attenuated inversion recovery (FLAIR), UTE1, and bone-enhanced images. Mean absolute error (MAE) characterized Hounsfield unit (HU) differences between synCT and CT-SIM. A dosimetry study was conducted, and differences were quantified using γ-analysis and dose-volume histogram analysis. Results: On average, true-positive rate and false-positive rate for the CT and MR-derived air masks were 80.8% ± 5.5% and 25.7% ± 6.9%, respectively. Dice similarity indices values were 0.78 ± 0.04 (range, 0.70-0.83). Full field of view MAE between synCT and CT-SIM was 147.5 ± 8.3 HU (range, 138.3-166.2 HU), with the largest errors occurring at bone–air interfaces (MAE 422.5 ± 33.4 HU for bone and 294.53 ± 90.56 HU for air). Gamma analysis revealed pass rates of 99.4% ± 0.04%, with acceptable treatment plan quality for the cohort. Conclusions: A hybrid MRI phase/magnitude UTE image processing technique was introduced that significantly improved bone and air contrast in MRI. Segmented air masks and bone-enhanced images were integrated

Video segmentation using keywords

Science.gov (United States)

Ton-That, Vinh; Vong, Chi-Tai; Nguyen-Dao, Xuan-Truong; Tran, Minh-Triet

2018-04-01

At DAVIS-2016 Challenge, many state-of-art video segmentation methods achieve potential results, but they still much depend on annotated frames to distinguish between background and foreground. It takes a lot of time and efforts to create these frames exactly. In this paper, we introduce a method to segment objects from video based on keywords given by user. First, we use a real-time object detection system - YOLOv2 to identify regions containing objects that have labels match with the given keywords in the first frame. Then, for each region identified from the previous step, we use Pyramid Scene Parsing Network to assign each pixel as foreground or background. These frames can be used as input frames for Object Flow algorithm to perform segmentation on entire video. We conduct experiments on a subset of DAVIS-2016 dataset in half the size of its original size, which shows that our method can handle many popular classes in PASCAL VOC 2012 dataset with acceptable accuracy, about 75.03%. We suggest widely testing by combining other methods to improve this result in the future.

Joint Rendering and Segmentation of Free-Viewpoint Video

Directory of Open Access Journals (Sweden)

Ishii Masato

2010-01-01

Full Text Available Abstract This paper presents a method that jointly performs synthesis and object segmentation of free-viewpoint video using multiview video as the input. This method is designed to achieve robust segmentation from online video input without per-frame user interaction and precomputations. This method shares a calculation process between the synthesis and segmentation steps; the matching costs calculated through the synthesis step are adaptively fused with other cues depending on the reliability in the segmentation step. Since the segmentation is performed for arbitrary viewpoints directly, the extracted object can be superimposed onto another 3D scene with geometric consistency. We can observe that the object and new background move naturally along with the viewpoint change as if they existed together in the same space. In the experiments, our method can process online video input captured by a 25-camera array and show the result image at 4.55 fps.

Poly-Pattern Compressive Segmentation of ASTER Data for GIS

Science.gov (United States)

Myers, Wayne; Warner, Eric; Tutwiler, Richard

2007-01-01

Pattern-based segmentation of multi-band image data, such as ASTER, produces one-byte and two-byte approximate compressions. This is a dual segmentation consisting of nested coarser and finer level pattern mappings called poly-patterns. The coarser A-level version is structured for direct incorporation into geographic information systems in the manner of a raster map. GIs renderings of this A-level approximation are called pattern pictures which have the appearance of color enhanced images. The two-byte version consisting of thousands of B-level segments provides a capability for approximate restoration of the multi-band data in selected areas or entire scenes. Poly-patterns are especially useful for purposes of change detection and landscape analysis at multiple scales. The primary author has implemented the segmentation methodology in a public domain software suite.

Planarity constrained multi-view depth map reconstruction for urban scenes

Science.gov (United States)

Hou, Yaolin; Peng, Jianwei; Hu, Zhihua; Tao, Pengjie; Shan, Jie

2018-05-01

Multi-view depth map reconstruction is regarded as a suitable approach for 3D generation of large-scale scenes due to its flexibility and scalability. However, there are challenges when this technique is applied to urban scenes where apparent man-made regular shapes may present. To address this need, this paper proposes a planarity constrained multi-view depth (PMVD) map reconstruction method. Starting with image segmentation and feature matching for each input image, the main procedure is iterative optimization under the constraints of planar geometry and smoothness. A set of candidate local planes are first generated by an extended PatchMatch method. The image matching costs are then computed and aggregated by an adaptive-manifold filter (AMF), whereby the smoothness constraint is applied to adjacent pixels through belief propagation. Finally, multiple criteria are used to eliminate image matching outliers. (Vertical) aerial images, oblique (aerial) images and ground images are used for qualitative and quantitative evaluations. The experiments demonstrated that the PMVD outperforms the popular multi-view depth map reconstruction with an accuracy two times better for the aerial datasets and achieves an outcome comparable to the state-of-the-art for ground images. As expected, PMVD is able to preserve the planarity for piecewise flat structures in urban scenes and restore the edges in depth discontinuous areas.

Structured prediction for urban scene semantic segmentation with geographic contex

OpenAIRE

Volpi Michele; Ferrari Vittorio

2015-01-01

In this work we address the problem of semantic segmentation of urban remote sensing images into land cover maps. We propose to tackle this task by learning the geographic context of classes and use it to favor or discourage certain spatial configuration of label assignments. For this reason, we learn from training data two spatial priors enforcing different key aspects of the geographical space: local co-occurrence and relative location of land cover classes. We propose to embed these geogra...

Detecting anomalies in crowded scenes via locality-constrained affine subspace coding

Science.gov (United States)

Fan, Yaxiang; Wen, Gongjian; Qiu, Shaohua; Li, Deren

2017-07-01

Video anomaly event detection is the process of finding an abnormal event deviation compared with the majority of normal or usual events. The main challenges are the high structure redundancy and the dynamic changes in the scenes that are in surveillance videos. To address these problems, we present a framework for anomaly detection and localization in videos that is based on locality-constrained affine subspace coding (LASC) and a model updating procedure. In our algorithm, LASC attempts to reconstruct the test sample by its top-k nearest subspaces, which are obtained by segmenting the normal samples space using a clustering method. A sample with a large reconstruction cost is detected as abnormal by setting a threshold. To adapt to the scene changes over time, a model updating strategy is proposed. We experiment on two public datasets: the UCSD dataset and the Avenue dataset. The results demonstrate that our method achieves competitive performance at a 700 fps on a single desktop PC.

A Method of Sharing Tacit Knowledge by a Bulletin Board Link to Video Scene and an Evaluation in the Field of Nursing Skill

Science.gov (United States)

Shimada, Satoshi; Azuma, Shouzou; Teranaka, Sayaka; Kojima, Akira; Majima, Yukie; Maekawa, Yasuko

We developed the system that knowledge could be discovered and shared cooperatively in the organization based on the SECI model of knowledge management. This system realized three processes by the following method. (1)A video that expressed skill is segmented into a number of scenes according to its contents. Tacit knowledge is shared in each scene. (2)Tacit knowledge is extracted by bulletin board linked to each scene. (3)Knowledge is acquired by repeatedly viewing the video scene with the comment that shows the technical content to be practiced. We conducted experiments that the system was used by nurses working for general hospitals. Experimental results show that the nursing practical knack is able to be collected by utilizing bulletin board linked to video scene. Results of this study confirmed the possibility of expressing the tacit knowledge of nurses' empirical nursing skills sensitively with a clue of video images.

Underwater Scene Composition

Science.gov (United States)

Kim, Nanyoung

2009-01-01

In this article, the author describes an underwater scene composition for elementary-education majors. This project deals with watercolor with crayon or oil-pastel resist (medium); the beauty of nature represented by fish in the underwater scene (theme); texture and pattern (design elements); drawing simple forms (drawing skill); and composition…

Scene-Based Contextual Cueing in Pigeons

Science.gov (United States)

Wasserman, Edward A.; Teng, Yuejia; Brooks, Daniel I.

2014-01-01

Repeated pairings of a particular visual context with a specific location of a target stimulus facilitate target search in humans. We explored an animal model of such contextual cueing. Pigeons had to peck a target which could appear in one of four locations on color photographs of real-world scenes. On half of the trials, each of four scenes was consistently paired with one of four possible target locations; on the other half of the trials, each of four different scenes was randomly paired with the same four possible target locations. In Experiments 1 and 2, pigeons exhibited robust contextual cueing when the context preceded the target by 1 s to 8 s, with reaction times to the target being shorter on predictive-scene trials than on random-scene trials. Pigeons also responded more frequently during the delay on predictive-scene trials than on random-scene trials; indeed, during the delay on predictive-scene trials, pigeons predominately pecked toward the location of the upcoming target, suggesting that attentional guidance contributes to contextual cueing. In Experiment 3, involving left-right and top-bottom scene reversals, pigeons exhibited stronger control by global than by local scene cues. These results attest to the robustness and associative basis of contextual cueing in pigeons. PMID:25546098

Segmentation of Large Unstructured Point Clouds Using Octree-Based Region Growing and Conditional Random Fields

Science.gov (United States)

Bassier, M.; Bonduel, M.; Van Genechten, B.; Vergauwen, M.

2017-11-01

Point cloud segmentation is a crucial step in scene understanding and interpretation. The goal is to decompose the initial data into sets of workable clusters with similar properties. Additionally, it is a key aspect in the automated procedure from point cloud data to BIM. Current approaches typically only segment a single type of primitive such as planes or cylinders. Also, current algorithms suffer from oversegmenting the data and are often sensor or scene dependent. In this work, a method is presented to automatically segment large unstructured point clouds of buildings. More specifically, the segmentation is formulated as a graph optimisation problem. First, the data is oversegmented with a greedy octree-based region growing method. The growing is conditioned on the segmentation of planes as well as smooth surfaces. Next, the candidate clusters are represented by a Conditional Random Field after which the most likely configuration of candidate clusters is computed given a set of local and contextual features. The experiments prove that the used method is a fast and reliable framework for unstructured point cloud segmentation. Processing speeds up to 40,000 points per second are recorded for the region growing. Additionally, the recall and precision of the graph clustering is approximately 80%. Overall, nearly 22% of oversegmentation is reduced by clustering the data. These clusters will be classified and used as a basis for the reconstruction of BIM models.

FUSION SEGMENTATION METHOD BASED ON FUZZY THEORY FOR COLOR IMAGES

Directory of Open Access Journals (Sweden)

J. Zhao

2017-09-01

Full Text Available The image segmentation method based on two-dimensional histogram segments the image according to the thresholds of the intensity of the target pixel and the average intensity of its neighborhood. This method is essentially a hard-decision method. Due to the uncertainties when labeling the pixels around the threshold, the hard-decision method can easily get the wrong segmentation result. Therefore, a fusion segmentation method based on fuzzy theory is proposed in this paper. We use membership function to model the uncertainties on each color channel of the color image. Then, we segment the color image according to the fuzzy reasoning. The experiment results show that our proposed method can get better segmentation results both on the natural scene images and optical remote sensing images compared with the traditional thresholding method. The fusion method in this paper can provide new ideas for the information extraction of optical remote sensing images and polarization SAR images.

Segmentation of radiologic images with self-organizing maps: the segmentation problem transformed into a classification task

Science.gov (United States)

Pelikan, Erich; Vogelsang, Frank; Tolxdorff, Thomas

1996-04-01

The texture-based segmentation of x-ray images of focal bone lesions using topological maps is introduced. Texture characteristics are described by image-point correlation of feature images to feature vectors. For the segmentation, the topological map is labeled using an improved labeling strategy. Results of the technique are demonstrated on original and synthetic x-ray images and quantified with the aid of quality measures. In addition, a classifier-specific contribution analysis is applied for assessing the feature space.

Unsupervised Performance Evaluation of Image Segmentation

Directory of Open Access Journals (Sweden)

Chabrier Sebastien

2006-01-01

Full Text Available We present in this paper a study of unsupervised evaluation criteria that enable the quantification of the quality of an image segmentation result. These evaluation criteria compute some statistics for each region or class in a segmentation result. Such an evaluation criterion can be useful for different applications: the comparison of segmentation results, the automatic choice of the best fitted parameters of a segmentation method for a given image, or the definition of new segmentation methods by optimization. We first present the state of art of unsupervised evaluation, and then, we compare six unsupervised evaluation criteria. For this comparative study, we use a database composed of 8400 synthetic gray-level images segmented in four different ways. Vinet's measure (correct classification rate is used as an objective criterion to compare the behavior of the different criteria. Finally, we present the experimental results on the segmentation evaluation of a few gray-level natural images.

High-dynamic-range imaging for cloud segmentation

Science.gov (United States)

Dev, Soumyabrata; Savoy, Florian M.; Lee, Yee Hui; Winkler, Stefan

2018-04-01

Sky-cloud images obtained from ground-based sky cameras are usually captured using a fisheye lens with a wide field of view. However, the sky exhibits a large dynamic range in terms of luminance, more than a conventional camera can capture. It is thus difficult to capture the details of an entire scene with a regular camera in a single shot. In most cases, the circumsolar region is overexposed, and the regions near the horizon are underexposed. This renders cloud segmentation for such images difficult. In this paper, we propose HDRCloudSeg - an effective method for cloud segmentation using high-dynamic-range (HDR) imaging based on multi-exposure fusion. We describe the HDR image generation process and release a new database to the community for benchmarking. Our proposed approach is the first using HDR radiance maps for cloud segmentation and achieves very good results.

Colour application on mammography image segmentation

Science.gov (United States)

Embong, R.; Aziz, N. M. Nik Ab.; Karim, A. H. Abd; Ibrahim, M. R.

2017-09-01

The segmentation process is one of the most important steps in image processing and computer vision since it is vital in the initial stage of image analysis. Segmentation of medical images involves complex structures and it requires precise segmentation result which is necessary for clinical diagnosis such as the detection of tumour, oedema, and necrotic tissues. Since mammography images are grayscale, researchers are looking at the effect of colour in the segmentation process of medical images. Colour is known to play a significant role in the perception of object boundaries in non-medical colour images. Processing colour images require handling more data, hence providing a richer description of objects in the scene. Colour images contain ten percent (10%) additional edge information as compared to their grayscale counterparts. Nevertheless, edge detection in colour image is more challenging than grayscale image as colour space is considered as a vector space. In this study, we implemented red, green, yellow, and blue colour maps to grayscale mammography images with the purpose of testing the effect of colours on the segmentation of abnormality regions in the mammography images. We applied the segmentation process using the Fuzzy C-means algorithm and evaluated the percentage of average relative error of area for each colour type. The results showed that all segmentation with the colour map can be done successfully even for blurred and noisy images. Also the size of the area of the abnormality region is reduced when compare to the segmentation area without the colour map. The green colour map segmentation produced the smallest percentage of average relative error (10.009%) while yellow colour map segmentation gave the largest percentage of relative error (11.367%).

Event segmentation and seven types of narrative discontinuity in popular movies.

Science.gov (United States)

Cutting, James E

2014-06-01

Using a sample of 24 movies I investigate narrative shifts in location, characters, and time frame that do and do not align with viewer segmentations of events (scenes and subscenes) in popular movies. Taken independently these dimensions create eight categories, seven of change and one of nonchange. Data show that the more dimensions that are changed the more viewers agree on their segmentations, although the nonadditive variations across the seven change types are large and systematic. Dissolves aid segmentation but over the last 70 years they have been used less and less by filmmakers, except for two infrequent shift types. Locations and characters are strongly yoked, jointly accounting for most narrative shifts. There are also interactions of shift types over the 70-year span and across genres, as well as differences that affect the scale of the establishing shot in a new scene. In addition, several aspects of the narratives of individual movies affect the distributions of shift types. Together these results suggest that there are at least four different signatures of narrative shifts to be found in popular movies - general patterns across time, patterns of historical change, genre-specific patterns, and film-specific patterns. Copyright © 2014 The Author. Published by Elsevier B.V. All rights reserved.

Associative Processing Is Inherent in Scene Perception

Science.gov (United States)

Aminoff, Elissa M.; Tarr, Michael J.

2015-01-01

How are complex visual entities such as scenes represented in the human brain? More concretely, along what visual and semantic dimensions are scenes encoded in memory? One hypothesis is that global spatial properties provide a basis for categorizing the neural response patterns arising from scenes. In contrast, non-spatial properties, such as single objects, also account for variance in neural responses. The list of critical scene dimensions has continued to grow—sometimes in a contradictory manner—coming to encompass properties such as geometric layout, big/small, crowded/sparse, and three-dimensionality. We demonstrate that these dimensions may be better understood within the more general framework of associative properties. That is, across both the perceptual and semantic domains, features of scene representations are related to one another through learned associations. Critically, the components of such associations are consistent with the dimensions that are typically invoked to account for scene understanding and its neural bases. Using fMRI, we show that non-scene stimuli displaying novel associations across identities or locations recruit putatively scene-selective regions of the human brain (the parahippocampal/lingual region, the retrosplenial complex, and the transverse occipital sulcus/occipital place area). Moreover, we find that the voxel-wise neural patterns arising from these associations are significantly correlated with the neural patterns arising from everyday scenes providing critical evidence whether the same encoding principals underlie both types of processing. These neuroimaging results provide evidence for the hypothesis that the neural representation of scenes is better understood within the broader theoretical framework of associative processing. In addition, the results demonstrate a division of labor that arises across scene-selective regions when processing associations and scenes providing better understanding of the functional

Beyond scene gist: Objects guide search more than scene background.

Science.gov (United States)

Koehler, Kathryn; Eckstein, Miguel P

2017-06-01

Although the facilitation of visual search by contextual information is well established, there is little understanding of the independent contributions of different types of contextual cues in scenes. Here we manipulated 3 types of contextual information: object co-occurrence, multiple object configurations, and background category. We isolated the benefits of each contextual cue to target detectability, its impact on decision bias, confidence, and the guidance of eye movements. We find that object-based information guides eye movements and facilitates perceptual judgments more than scene background. The degree of guidance and facilitation of each contextual cue can be related to its inherent informativeness about the target spatial location as measured by human explicit judgments about likely target locations. Our results improve the understanding of the contributions of distinct contextual scene components to search and suggest that the brain's utilization of cues to guide eye movements is linked to the cue's informativeness about the target's location. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Feed-forward segmentation of figure-ground and assignment of border-ownership.

Directory of Open Access Journals (Sweden)

Hans Supèr

Full Text Available Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation. On the contrary, a role of feedforward projections in figure-ground segmentation is unknown. To have a better understanding of a role of feedforward connections in figure-ground organization, we constructed a feedforward spiking model using a biologically plausible neuron model. By means of surround inhibition our simple 3-layered model performs figure-ground segmentation and one-sided border-ownership coding. We propose that the visual system uses feed forward suppression for figure-ground segmentation and border-ownership assignment.

Feed-forward segmentation of figure-ground and assignment of border-ownership.

Science.gov (United States)

Supèr, Hans; Romeo, August; Keil, Matthias

2010-05-19

Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation. On the contrary, a role of feedforward projections in figure-ground segmentation is unknown. To have a better understanding of a role of feedforward connections in figure-ground organization, we constructed a feedforward spiking model using a biologically plausible neuron model. By means of surround inhibition our simple 3-layered model performs figure-ground segmentation and one-sided border-ownership coding. We propose that the visual system uses feed forward suppression for figure-ground segmentation and border-ownership assignment.

Stages As Models of Scene Geometry

NARCIS (Netherlands)

Nedović, V.; Smeulders, A.W.M.; Redert, A.; Geusebroek, J.M.

2010-01-01

Reconstruction of 3D scene geometry is an important element for scene understanding, autonomous vehicle and robot navigation, image retrieval, and 3D television. We propose accounting for the inherent structure of the visual world when trying to solve the scene reconstruction problem. Consequently,

Parallel Implementation of the Recursive Approximation of an Unsupervised Hierarchical Segmentation Algorithm. Chapter 5

Science.gov (United States)

Tilton, James C.; Plaza, Antonio J. (Editor); Chang, Chein-I. (Editor)

2008-01-01

The hierarchical image segmentation algorithm (referred to as HSEG) is a hybrid of hierarchical step-wise optimization (HSWO) and constrained spectral clustering that produces a hierarchical set of image segmentations. HSWO is an iterative approach to region grooving segmentation in which the optimal image segmentation is found at N(sub R) regions, given a segmentation at N(sub R+1) regions. HSEG's addition of constrained spectral clustering makes it a computationally intensive algorithm, for all but, the smallest of images. To counteract this, a computationally efficient recursive approximation of HSEG (called RHSEG) has been devised. Further improvements in processing speed are obtained through a parallel implementation of RHSEG. This chapter describes this parallel implementation and demonstrates its computational efficiency on a Landsat Thematic Mapper test scene.

When Does Repeated Search in Scenes Involve Memory? Looking at versus Looking for Objects in Scenes

Science.gov (United States)

Vo, Melissa L. -H.; Wolfe, Jeremy M.

2012-01-01

One might assume that familiarity with a scene or previous encounters with objects embedded in a scene would benefit subsequent search for those items. However, in a series of experiments we show that this is not the case: When participants were asked to subsequently search for multiple objects in the same scene, search performance remained…

Stereoscopy in cinematographic synthetic imagery

Science.gov (United States)

Eisenmann, Jonathan; Parent, Rick

2009-02-01

In this paper we present experiments and results pertaining to the perception of depth in stereoscopic viewing of synthetic imagery. In computer animation, typical synthetic imagery is highly textured and uses stylized illumination of abstracted material models by abstracted light source models. While there have been numerous studies concerning stereoscopic capabilities, conventions for staging and cinematography in stereoscopic movies have not yet been well-established. Our long-term goal is to measure the effectiveness of various cinematography techniques on the human visual system in a theatrical viewing environment. We would like to identify the elements of stereoscopic cinema that are important in terms of enhancing the viewer's understanding of a scene as well as providing guidelines for the cinematographer relating to storytelling. In these experiments we isolated stereoscopic effects by eliminating as many other visual cues as is reasonable. In particular, we aim to empirically determine what types of movement in synthetic imagery affect the perceptual depth sensing capabilities of our viewers. Using synthetic imagery, we created several viewing scenarios in which the viewer is asked to locate a target object's depth in a simple environment. The scenarios were specifically designed to compare the effectiveness of stereo viewing, camera movement, and object motion in aiding depth perception. Data were collected showing the error between the choice of the user and the actual depth value, and patterns were identified that relate the test variables to the viewer's perceptual depth accuracy in our theatrical viewing environment.

SEMANTIC SEGMENTATION OF BUILDING ELEMENTS USING POINT CLOUD HASHING

Directory of Open Access Journals (Sweden)

M. Chizhova

2018-05-01

Full Text Available For the interpretation of point clouds, the semantic definition of extracted segments from point clouds or images is a common problem. Usually, the semantic of geometrical pre-segmented point cloud elements are determined using probabilistic networks and scene databases. The proposed semantic segmentation method is based on the psychological human interpretation of geometric objects, especially on fundamental rules of primary comprehension. Starting from these rules the buildings could be quite well and simply classified by a human operator (e.g. architect into different building types and structural elements (dome, nave, transept etc., including particular building parts which are visually detected. The key part of the procedure is a novel method based on hashing where point cloud projections are transformed into binary pixel representations. A segmentation approach released on the example of classical Orthodox churches is suitable for other buildings and objects characterized through a particular typology in its construction (e.g. industrial objects in standardized enviroments with strict component design allowing clear semantic modelling.

Validation of the use of synthetic imagery for camouflage effectiveness assessment

Science.gov (United States)

Newman, Sarah; Gilmore, Marilyn A.; Moorhead, Ian R.; Filbee, David R.

2002-08-01

CAMEO-SIM was developed as a laboratory method to assess the effectiveness of aircraft camouflage schemes. It is a physically accurate synthetic image generator, rendering in any waveband between 0.4 and 14 microns. Camouflage schemes are assessed by displaying imagery to observers under controlled laboratory conditions or by analyzing the digital image and calculating the contrast statistics between the target and background. Code verification has taken place during development. However, validation of CAMEO-SIM is essential to ensure that the imagery produced is suitable to be used for camouflage effectiveness assessment. Real world characteristics are inherently variable, so exact pixel to pixel correlation is unnecessary. For camouflage effectiveness assessment it is more important to be confident that the comparative effects of different schemes are correct, but prediction of detection ranges is also desirable. Several different tests have been undertaken to validate CAMEO-SIM for the purpose of assessing camouflage effectiveness. Simple scenes have been modeled and measured. Thermal and visual properties of the synthetic and real scenes have been compared. This paper describes the validation tests and discusses the suitability of CAMEO-SIM for camouflage assessment.

Forensic 3D Scene Reconstruction

International Nuclear Information System (INIS)

LITTLE, CHARLES Q.; PETERS, RALPH R.; RIGDON, J. BRIAN; SMALL, DANIEL E.

1999-01-01

Traditionally law enforcement agencies have relied on basic measurement and imaging tools, such as tape measures and cameras, in recording a crime scene. A disadvantage of these methods is that they are slow and cumbersome. The development of a portable system that can rapidly record a crime scene with current camera imaging, 3D geometric surface maps, and contribute quantitative measurements such as accurate relative positioning of crime scene objects, would be an asset to law enforcement agents in collecting and recording significant forensic data. The purpose of this project is to develop a feasible prototype of a fast, accurate, 3D measurement and imaging system that would support law enforcement agents to quickly document and accurately record a crime scene

Filling Landsat ETM+ SLC-off gaps using a segmentation model approach

Science.gov (United States)

Maxwell, Susan

2004-01-01

The purpose of this article is to present a methodology for filling Landsat Scan Line Corrector (SLC)-off gaps with same-scene spectral data guided by a segmentation model. Failure of the SLC on the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) instrument resulted in a loss of approximately 25 percent of the spectral data. The missing data span across most of the image with scan gaps varying in size from two pixels near the center of the image to 14 pixels along the east and west edges. Even with the scan gaps, the radiometric and geometric qualities of the remaining portions of the image still meet design specifications and therefore contain useful information (see http:// landsat7.usgs.gov for additional information). The U.S. Geological Survey EROS Data Center (EDC) is evaluating several techniques to fill the gaps in SLC-off data to enhance the usability of the imagery (Howard and Lacasse 2004) (PE&RS, August 2004). The method presented here uses a segmentation model approach that allows for same-scene spectral data to be used to fill the gaps. The segment model is generated from a complete satellite image with no missing spectral data (e.g., Landsat 5, Landsat 7 SLCon, SPOT). The model is overlaid on the Landsat SLC-off image, and the missing data within the gaps are then estimated using SLC-off spectral data that intersect the segment boundary. A major advantage of this approach is that the gaps are filled using spectral data derived from the same SLC-off satellite image.

Scenes of the self, and trance

Directory of Open Access Journals (Sweden)

Jan M. Broekman

2014-02-01

Full Text Available Trance shows the Self as a process involved in all sorts and forms of life. A Western perspective on a self and its reifying tendencies is only one (or one series of those variations. The process character of the self does not allow any coherent theory but shows, in particular when confronted with trance, its variability in all regards. What is more: the Self is always first on the scene of itself―a situation in which it becomes a sign for itself. That particular semiotic feature is again not a unified one but leads, as the Self in view of itself does, to series of scenes with changing colors, circumstances and environments. Our first scene “Beyond Monotheism” shows semiotic importance in that a self as determining component of a trance-phenomenon must abolish its own referent and seems not able to answer the question, what makes trance a trance. The Pizzica is an example here. Other social features of trance appear in the second scene, US post traumatic psychological treatments included. Our third scene underlines structures of an unfolding self: beginning with ‘split-ego’ conclusions, a self’s engenderment appears dependent on linguistic events and on spoken words in the first place. A fourth scene explores that theme and explains modern forms of an ego ―in particular those inherent to ‘citizenship’ or a ‘corporation’. The legal consequences are concentrated in the fifth scene, which considers a legal subject by revealing its ‘standing’. Our sixth and final scene pertains to the relation between trance and commerce. All scenes tie together and show parallels between Pizzica, rights-based behavior, RAVE music versus disco, commerce and trance; they demonstrate the meaning of trance as a multifaceted social phenomenon.

Identifying Generalizable Image Segmentation Parameters for Urban Land Cover Mapping through Meta-Analysis and Regression Tree Modeling

Directory of Open Access Journals (Sweden)

Brian A. Johnson

2018-01-01

Full Text Available The advent of very high resolution (VHR satellite imagery and the development of Geographic Object-Based Image Analysis (GEOBIA have led to many new opportunities for fine-scale land cover mapping, especially in urban areas. Image segmentation is an important step in the GEOBIA framework, so great time/effort is often spent to ensure that computer-generated image segments closely match real-world objects of interest. In the remote sensing community, segmentation is frequently performed using the multiresolution segmentation (MRS algorithm, which is tuned through three user-defined parameters (the scale, shape/color, and compactness/smoothness parameters. The scale parameter (SP is the most important parameter and governs the average size of generated image segments. Existing automatic methods to determine suitable SPs for segmentation are scene-specific and often computationally intensive, so an approach to estimating appropriate SPs that is generalizable (i.e., not scene-specific could speed up the GEOBIA workflow considerably. In this study, we attempted to identify generalizable SPs for five common urban land cover types (buildings, vegetation, roads, bare soil, and water through meta-analysis and nonlinear regression tree (RT modeling. First, we performed a literature search of recent studies that employed GEOBIA for urban land cover mapping and extracted the MRS parameters used, the image properties (i.e., spatial and radiometric resolutions, and the land cover classes mapped. Using this data extracted from the literature, we constructed RT models for each land cover class to predict suitable SP values based on the: image spatial resolution, image radiometric resolution, shape/color parameter, and compactness/smoothness parameter. Based on a visual and quantitative analysis of results, we found that for all land cover classes except water, relatively accurate SPs could be identified using our RT modeling results. The main advantage of our

Lateralized discrimination of emotional scenes in peripheral vision.

Science.gov (United States)

Calvo, Manuel G; Rodríguez-Chinea, Sandra; Fernández-Martín, Andrés

2015-03-01

This study investigates whether there is lateralized processing of emotional scenes in the visual periphery, in the absence of eye fixations; and whether this varies with emotional valence (pleasant vs. unpleasant), specific emotional scene content (babies, erotica, human attack, mutilation, etc.), and sex of the viewer. Pairs of emotional (positive or negative) and neutral photographs were presented for 150 ms peripherally (≥6.5° away from fixation). Observers judged on which side the emotional picture was located. Low-level image properties, scene visual saliency, and eye movements were controlled. Results showed that (a) correct identification of the emotional scene exceeded the chance level; (b) performance was more accurate and faster when the emotional scene appeared in the left than in the right visual field; (c) lateralization was equivalent for females and males for pleasant scenes, but was greater for females and unpleasant scenes; and (d) lateralization occurred similarly for different emotional scene categories. These findings reveal discrimination between emotional and neutral scenes, and right brain hemisphere dominance for emotional processing, which is modulated by sex of the viewer and scene valence, and suggest that coarse affective significance can be extracted in peripheral vision.

Synthetic cathinones: a new public health problem.

Science.gov (United States)

Karila, Laurent; Megarbane, Bruno; Cottencin, Olivier; Lejoyeux, Michel

2015-01-01

New psychoactive substances (NPS) have completely modified the drug scene and the current landscape of addiction. Synthetic substances, such as substituted or synthetic cathinones, also known as « legal highs », are often produced and used to mimic the effects of controlled drugs such as cocaine, methylenedioxymethamphetamine (MDMA, ecstasy), and methamphetamine. The overwhelming majority of synthetic cathinones are produced in China and South East Asian countries. The Internet has emerged as the new marketplace for NPS, playing a major role in providing information on acquisition, synthesis, extraction, identification, and substance use. All these compounds are intentionally mislabeled and sold on-line under slang terms such as bath salts, plant food, plant feeders and research chemicals. They are sometimes labeled « not for human use » or « not tested for hazards or toxicity ». The rapid spread of NPS forces member countries of the European Union to adapt their response to the potential new dangers that may cause. To date, not only health actors but also the general public need to be clearly informed and aware of dangers resulting from NPS spread and use. Here, we review the major clinical effects of synthetic cathinones to highlight their impact on public health. A literature search was conducted from 2009 to 2014 based on PubMed, Google Scholar, Erowid, and governmental websites, using the following keywords alone or in combination: "new psychoactive substances", "synthetic cathinones", "substituted cathinones", "mephedrone", "methylone", "MDPV", "4-MEC", "addiction", and "substance use disorder".

Graph-based surface reconstruction from stereo pairs using image segmentation

Science.gov (United States)

Bleyer, Michael; Gelautz, Margrit

2005-01-01

This paper describes a novel stereo matching algorithm for epipolar rectified images. The method applies colour segmentation on the reference image. The use of segmentation makes the algorithm capable of handling large untextured regions, estimating precise depth boundaries and propagating disparity information to occluded regions, which are challenging tasks for conventional stereo methods. We model disparity inside a segment by a planar equation. Initial disparity segments are clustered to form a set of disparity layers, which are planar surfaces that are likely to occur in the scene. Assignments of segments to disparity layers are then derived by minimization of a global cost function via a robust optimization technique that employs graph cuts. The cost function is defined on the pixel level, as well as on the segment level. While the pixel level measures the data similarity based on the current disparity map and detects occlusions symmetrically in both views, the segment level propagates the segmentation information and incorporates a smoothness term. New planar models are then generated based on the disparity layers' spatial extents. Results obtained for benchmark and self-recorded image pairs indicate that the proposed method is able to compete with the best-performing state-of-the-art algorithms.

Stages as models of scene geometry.

Science.gov (United States)

Nedović, Vladimir; Smeulders, Arnold W M; Redert, André; Geusebroek, Jan-Mark

2010-09-01

Reconstruction of 3D scene geometry is an important element for scene understanding, autonomous vehicle and robot navigation, image retrieval, and 3D television. We propose accounting for the inherent structure of the visual world when trying to solve the scene reconstruction problem. Consequently, we identify geometric scene categorization as the first step toward robust and efficient depth estimation from single images. We introduce 15 typical 3D scene geometries called stages, each with a unique depth profile, which roughly correspond to a large majority of broadcast video frames. Stage information serves as a first approximation of global depth, narrowing down the search space in depth estimation and object localization. We propose different sets of low-level features for depth estimation, and perform stage classification on two diverse data sets of television broadcasts. Classification results demonstrate that stages can often be efficiently learned from low-dimensional image representations.

Iconic memory for the gist of natural scenes.

Science.gov (United States)

Clarke, Jason; Mack, Arien

2014-11-01

Does iconic memory contain the gist of multiple scenes? Three experiments were conducted. In the first, four scenes from different basic-level categories were briefly presented in one of two conditions: a cue or a no-cue condition. The cue condition was designed to provide an index of the contents of iconic memory of the display. Subjects were more sensitive to scene gist in the cue condition than in the no-cue condition. In the second, the scenes came from the same basic-level category. We found no difference in sensitivity between the two conditions. In the third, six scenes from different basic level categories were presented in the visual periphery. Subjects were more sensitive to scene gist in the cue condition. These results suggest that scene gist is contained in iconic memory even in the visual periphery; however, iconic representations are not sufficiently detailed to distinguish between scenes coming from the same category. Copyright © 2014 Elsevier Inc. All rights reserved.

Statistics of high-level scene context.

Science.gov (United States)

Greene, Michelle R

2013-01-01

CONTEXT IS CRITICAL FOR RECOGNIZING ENVIRONMENTS AND FOR SEARCHING FOR OBJECTS WITHIN THEM: contextual associations have been shown to modulate reaction time and object recognition accuracy, as well as influence the distribution of eye movements and patterns of brain activations. However, we have not yet systematically quantified the relationships between objects and their scene environments. Here I seek to fill this gap by providing descriptive statistics of object-scene relationships. A total of 48, 167 objects were hand-labeled in 3499 scenes using the LabelMe tool (Russell et al., 2008). From these data, I computed a variety of descriptive statistics at three different levels of analysis: the ensemble statistics that describe the density and spatial distribution of unnamed "things" in the scene; the bag of words level where scenes are described by the list of objects contained within them; and the structural level where the spatial distribution and relationships between the objects are measured. The utility of each level of description for scene categorization was assessed through the use of linear classifiers, and the plausibility of each level for modeling human scene categorization is discussed. Of the three levels, ensemble statistics were found to be the most informative (per feature), and also best explained human patterns of categorization errors. Although a bag of words classifier had similar performance to human observers, it had a markedly different pattern of errors. However, certain objects are more useful than others, and ceiling classification performance could be achieved using only the 64 most informative objects. As object location tends not to vary as a function of category, structural information provided little additional information. Additionally, these data provide valuable information on natural scene redundancy that can be exploited for machine vision, and can help the visual cognition community to design experiments guided by statistics

Semantic Reasoning for Scene Interpretation

DEFF Research Database (Denmark)

Jensen, Lars Baunegaard With; Baseski, Emre; Pugeault, Nicolas

2008-01-01

In this paper, we propose a hierarchical architecture for representing scenes, covering 2D and 3D aspects of visual scenes as well as the semantic relations between the different aspects. We argue that labeled graphs are a suitable representational framework for this representation and demonstrat...

The scene and the unseen: manipulating photographs for experiments on change blindness and scene memory: image manipulation for change blindness.

Science.gov (United States)

Ball, Felix; Elzemann, Anne; Busch, Niko A

2014-09-01

The change blindness paradigm, in which participants often fail to notice substantial changes in a scene, is a popular tool for studying scene perception, visual memory, and the link between awareness and attention. Some of the most striking and popular examples of change blindness have been demonstrated with digital photographs of natural scenes; in most studies, however, much simpler displays, such as abstract stimuli or "free-floating" objects, are typically used. Although simple displays have undeniable advantages, natural scenes remain a very useful and attractive stimulus for change blindness research. To assist researchers interested in using natural-scene stimuli in change blindness experiments, we provide here a step-by-step tutorial on how to produce changes in natural-scene images with a freely available image-processing tool (GIMP). We explain how changes in a scene can be made by deleting objects or relocating them within the scene or by changing the color of an object, in just a few simple steps. We also explain how the physical properties of such changes can be analyzed using GIMP and MATLAB (a high-level scientific programming tool). Finally, we present an experiment confirming that scenes manipulated according to our guidelines are effective in inducing change blindness and demonstrating the relationship between change blindness and the physical properties of the change and inter-individual differences in performance measures. We expect that this tutorial will be useful for researchers interested in studying the mechanisms of change blindness, attention, or visual memory using natural scenes.

Pooling Objects for Recognizing Scenes without Examples

NARCIS (Netherlands)

Kordumova, S.; Mensink, T.; Snoek, C.G.M.

2016-01-01

In this paper we aim to recognize scenes in images without using any scene images as training data. Different from attribute based approaches, we do not carefully select the training classes to match the unseen scene classes. Instead, we propose a pooling over ten thousand of off-the-shelf object

Correlated Topic Vector for Scene Classification.

Science.gov (United States)

Wei, Pengxu; Qin, Fei; Wan, Fang; Zhu, Yi; Jiao, Jianbin; Ye, Qixiang

2017-07-01

Scene images usually involve semantic correlations, particularly when considering large-scale image data sets. This paper proposes a novel generative image representation, correlated topic vector, to model such semantic correlations. Oriented from the correlated topic model, correlated topic vector intends to naturally utilize the correlations among topics, which are seldom considered in the conventional feature encoding, e.g., Fisher vector, but do exist in scene images. It is expected that the involvement of correlations can increase the discriminative capability of the learned generative model and consequently improve the recognition accuracy. Incorporated with the Fisher kernel method, correlated topic vector inherits the advantages of Fisher vector. The contributions to the topics of visual words have been further employed by incorporating the Fisher kernel framework to indicate the differences among scenes. Combined with the deep convolutional neural network (CNN) features and Gibbs sampling solution, correlated topic vector shows great potential when processing large-scale and complex scene image data sets. Experiments on two scene image data sets demonstrate that correlated topic vector improves significantly the deep CNN features, and outperforms existing Fisher kernel-based features.

Audio segmentation of broadcast news in the Albayzin-2010 evaluation: overview, results, and discussion

Directory of Open Access Journals (Sweden)

Butko Taras

2011-01-01

Full Text Available Abstract Recently, audio segmentation has attracted research interest because of its usefulness in several applications like audio indexing and retrieval, subtitling, monitoring of acoustic scenes, etc. Moreover, a previous audio segmentation stage may be useful to improve the robustness of speech technologies like automatic speech recognition and speaker diarization. In this article, we present the evaluation of broadcast news audio segmentation systems carried out in the context of the Albayzín-2010 evaluation campaign. That evaluation consisted of segmenting audio from the 3/24 Catalan TV channel into five acoustic classes: music, speech, speech over music, speech over noise, and the other. The evaluation results displayed the difficulty of this segmentation task. In this article, after presenting the database and metric, as well as the feature extraction methods and segmentation techniques used by the submitted systems, the experimental results are analyzed and compared, with the aim of gaining an insight into the proposed solutions, and looking for directions which are promising.

Foreground-background segmentation and attention: a change blindness study.

Science.gov (United States)

Mazza, Veronica; Turatto, Massimo; Umiltà, Carlo

2005-01-01

One of the most debated questions in visual attention research is what factors affect the deployment of attention in the visual scene? Segmentation processes are influential factors, providing candidate objects for further attentional selection, and the relevant literature has concentrated on how figure-ground segmentation mechanisms influence visual attention. However, another crucial process, namely foreground-background segmentation, seems to have been neglected. By using a change blindness paradigm, we explored whether attention is preferentially allocated to the foreground elements or to the background ones. The results indicated that unless attention was voluntarily deployed to the background, large changes in the color of its elements remained unnoticed. In contrast, minor changes in the foreground elements were promptly reported. Differences in change blindness between the two regions of the display indicate that attention is, by default, biased toward the foreground elements. This also supports the phenomenal observations made by Gestaltists, who demonstrated the greater salience of the foreground than the background.

Segmentation of foreground apple targets by fusing visual attention mechanism and growth rules of seed points

Energy Technology Data Exchange (ETDEWEB)

Qu, W.; Shang, W.; Shao, Y.; Wang, D.; Yu, X.; Song, H.

2015-07-01

Accurate segmentation of apple targets is one of the most important problems to be solved in the vision system of apple picking robots. This work aimed to solve the difficulties that background targets often bring to foreground targets segmentation, by fusing the visual attention mechanism and the growth rule of seed points. Background targets could be eliminated by extracting the ROI (region of interest) of apple targets; the ROI was roughly segmented on the HSV color space, and then each of the pixels was used as a seed growing point. The growth rule of the seed points was adopted to obtain the whole area of apple targets from seed growing points. The proposed method was tested with 20 images captured in a natural scene, including 54 foreground apple targets and approximately 84 background apple targets. Experimental results showed that the proposed method can remove background targets and focus on foreground targets, while the k-means algorithm and the chromatic aberration algorithm cannot. Additionally, its average segmentation error rate was 13.23%, which is 2.71% higher than that of the k-means algorithm and 2.95% lower than that of the chromatic aberration algorithm. In conclusion, the proposed method contributes to the vision system of apple-picking robots to locate foreground apple targets quickly and accurately under a natural scene. (Author)

Pyramidal approach to license plate segmentation

Science.gov (United States)

Postolache, Alexandru; Trecat, Jacques C.

1996-07-01

Car identification is a goal in traffic control, transport planning, travel time measurement, managing parking lot traffic and so on. Most car identification algorithms contain a standalone plate segmentation process followed by a plate contents reading. A pyramidal algorithm for license plate segmentation, looking for textured regions, has been developed on a PC based system running Unix. It can be used directly in applications not requiring real time. When input images are relatively small, real-time performance is in fact accomplished by the algorithm. When using large images, porting the algorithm to special digital signal processors can easily lead to preserving real-time performance. Experimental results, for stationary and moving cars in outdoor scenes, showed high accuracy and high scores in detecting the plate. The algorithm also deals with cases where many character strings are present in the image, and not only the one corresponding to the plate. This is done by the means of a constrained texture regions classification.

A hierarchical inferential method for indoor scene classification

Directory of Open Access Journals (Sweden)

Jiang Jingzhe

2017-12-01

Full Text Available Indoor scene classification forms a basis for scene interaction for service robots. The task is challenging because the layout and decoration of a scene vary considerably. Previous studies on knowledge-based methods commonly ignore the importance of visual attributes when constructing the knowledge base. These shortcomings restrict the performance of classification. The structure of a semantic hierarchy was proposed to describe similarities of different parts of scenes in a fine-grained way. Besides the commonly used semantic features, visual attributes were also introduced to construct the knowledge base. Inspired by the processes of human cognition and the characteristics of indoor scenes, we proposed an inferential framework based on the Markov logic network. The framework is evaluated on a popular indoor scene dataset, and the experimental results demonstrate its effectiveness.

Autonomous Segmentation of Outcrop Images Using Computer Vision and Machine Learning

Science.gov (United States)

Francis, R.; McIsaac, K.; Osinski, G. R.; Thompson, D. R.

2013-12-01

As planetary exploration missions become increasingly complex and capable, the motivation grows for improved autonomous science. New capabilities for onboard science data analysis may relieve radio-link data limits and provide greater throughput of scientific information. Adaptive data acquisition, storage and downlink may ultimately hold implications for mission design and operations. For surface missions, geology remains an essential focus, and the investigation of in place, exposed geological materials provides the greatest scientific insight and context for the formation and history of planetary materials and processes. The goal of this research program is to develop techniques for autonomous segmentation of images of rock outcrops. Recognition of the relationships between different geological units is the first step in mapping and interpreting a geological setting. Applications of automatic segmentation include instrument placement and targeting and data triage for downlink. Here, we report on the development of a new technique in which a photograph of a rock outcrop is processed by several elementary image processing techniques, generating a feature space which can be interrogated and classified. A distance metric learning technique (Multiclass Discriminant Analysis, or MDA) is tested as a means of finding the best numerical representation of the feature space. MDA produces a linear transformation that maximizes the separation between data points from different geological units. This ';training step' is completed on one or more images from a given locality. Then we apply the same transformation to improve the segmentation of new scenes containing similar materials to those used for training. The technique was tested using imagery from Mars analogue settings at the Cima volcanic flows in the Mojave Desert, California; impact breccias from the Sudbury impact structure in Ontario, Canada; and an outcrop showing embedded mineral veins in Gale Crater on Mars

Contextually guided very-high-resolution imagery classification with semantic segments

Science.gov (United States)

Zhao, Wenzhi; Du, Shihong; Wang, Qiao; Emery, William J.

2017-10-01

Contextual information, revealing relationships and dependencies between image objects, is one of the most important information for the successful interpretation of very-high-resolution (VHR) remote sensing imagery. Over the last decade, geographic object-based image analysis (GEOBIA) technique has been widely used to first divide images into homogeneous parts, and then to assign semantic labels according to the properties of image segments. However, due to the complexity and heterogeneity of VHR images, segments without semantic labels (i.e., semantic-free segments) generated with low-level features often fail to represent geographic entities (such as building roofs usually be partitioned into chimney/antenna/shadow parts). As a result, it is hard to capture contextual information across geographic entities when using semantic-free segments. In contrast to low-level features, "deep" features can be used to build robust segments with accurate labels (i.e., semantic segments) in order to represent geographic entities at higher levels. Based on these semantic segments, semantic graphs can be constructed to capture contextual information in VHR images. In this paper, semantic segments were first explored with convolutional neural networks (CNN) and a conditional random field (CRF) model was then applied to model the contextual information between semantic segments. Experimental results on two challenging VHR datasets (i.e., the Vaihingen and Beijing scenes) indicate that the proposed method is an improvement over existing image classification techniques in classification performance (overall accuracy ranges from 82% to 96%).

Autofocus algorithm for synthetic aperture radar imaging with large curvilinear apertures

Science.gov (United States)

Bleszynski, E.; Bleszynski, M.; Jaroszewicz, T.

2013-05-01

An approach to autofocusing for large curved synthetic aperture radar (SAR) apertures is presented. Its essential feature is that phase corrections are being extracted not directly from SAR images, but rather from reconstructed SAR phase-history data representing windowed patches of the scene, of sizes sufficiently small to allow the linearization of the forward- and back-projection formulae. The algorithm processes data associated with each patch independently and in two steps. The first step employs a phase-gradient-type method in which phase correction compensating (possibly rapid) trajectory perturbations are estimated from the reconstructed phase history for the dominant scattering point on the patch. The second step uses phase-gradient-corrected data and extracts the absolute phase value, removing in this way phase ambiguities and reducing possible imperfections of the first stage, and providing the distances between the sensor and the scattering point with accuracy comparable to the wavelength. The features of the proposed autofocusing method are illustrated in its applications to intentionally corrupted small-scene 2006 Gotcha data. The examples include the extraction of absolute phases (ranges) for selected prominent point targets. They are then used to focus the scene and determine relative target-target distances.

Simultaneous hierarchical segmentation and vectorization of satellite images through combined data sampling and anisotropic triangulation

Energy Technology Data Exchange (ETDEWEB)

Grazzini, Jacopo [Los Alamos National Laboratory; Prasad, Lakshman [Los Alamos National Laboratory; Dillard, Scott [PNNL

2010-10-21

The automatic detection, recognition , and segmentation of object classes in remote sensed images is of crucial importance for scene interpretation and understanding. However, it is a difficult task because of the high variability of satellite data. Indeed, the observed scenes usually exhibit a high degree of complexity, where complexity refers to the large variety of pictorial representations of objects with the same semantic meaning and also to the extensive amount of available det.ails. Therefore, there is still a strong demand for robust techniques for automatic information extraction and interpretation of satellite images. In parallel, there is a growing interest in techniques that can extract vector features directly from such imagery. In this paper, we investigate the problem of automatic hierarchical segmentation and vectorization of multispectral satellite images. We propose a new algorithm composed of the following steps: (i) a non-uniform sampling scheme extracting most salient pixels in the image, (ii) an anisotropic triangulation constrained by the sampled pixels taking into account both strength and directionality of local structures present in the image, (iii) a polygonal grouping scheme merging, through techniques based on perceptual information , the obtained segments to a smaller quantity of superior vectorial objects. Besides its computational efficiency, this approach provides a meaningful polygonal representation for subsequent image analysis and/or interpretation.

Visual search for arbitrary objects in real scenes

Science.gov (United States)

Alvarez, George A.; Rosenholtz, Ruth; Kuzmova, Yoana I.; Sherman, Ashley M.

2011-01-01

How efficient is visual search in real scenes? In searches for targets among arrays of randomly placed distractors, efficiency is often indexed by the slope of the reaction time (RT) × Set Size function. However, it may be impossible to define set size for real scenes. As an approximation, we hand-labeled 100 indoor scenes and used the number of labeled regions as a surrogate for set size. In Experiment 1, observers searched for named objects (a chair, bowl, etc.). With set size defined as the number of labeled regions, search was very efficient (~5 ms/item). When we controlled for a possible guessing strategy in Experiment 2, slopes increased somewhat (~15 ms/item), but they were much shallower than search for a random object among other distinctive objects outside of a scene setting (Exp. 3: ~40 ms/item). In Experiments 4–6, observers searched repeatedly through the same scene for different objects. Increased familiarity with scenes had modest effects on RTs, while repetition of target items had large effects (>500 ms). We propose that visual search in scenes is efficient because scene-specific forms of attentional guidance can eliminate most regions from the “functional set size” of items that could possibly be the target. PMID:21671156

Visual search for arbitrary objects in real scenes.

Science.gov (United States)

Wolfe, Jeremy M; Alvarez, George A; Rosenholtz, Ruth; Kuzmova, Yoana I; Sherman, Ashley M

2011-08-01

How efficient is visual search in real scenes? In searches for targets among arrays of randomly placed distractors, efficiency is often indexed by the slope of the reaction time (RT) × Set Size function. However, it may be impossible to define set size for real scenes. As an approximation, we hand-labeled 100 indoor scenes and used the number of labeled regions as a surrogate for set size. In Experiment 1, observers searched for named objects (a chair, bowl, etc.). With set size defined as the number of labeled regions, search was very efficient (~5 ms/item). When we controlled for a possible guessing strategy in Experiment 2, slopes increased somewhat (~15 ms/item), but they were much shallower than search for a random object among other distinctive objects outside of a scene setting (Exp. 3: ~40 ms/item). In Experiments 4-6, observers searched repeatedly through the same scene for different objects. Increased familiarity with scenes had modest effects on RTs, while repetition of target items had large effects (>500 ms). We propose that visual search in scenes is efficient because scene-specific forms of attentional guidance can eliminate most regions from the "functional set size" of items that could possibly be the target.

Coastal flood inundation monitoring with Satellite C-band and L-band Synthetic Aperture Radar data

Science.gov (United States)

Ramsey, Elijah W.; Rangoonwala, Amina; Bannister, Terri

2013-01-01

Satellite Synthetic Aperture Radar (SAR) was evaluated as a method to operationally monitor the occurrence and distribution of storm- and tidal-related flooding of spatially extensive coastal marshes within the north-central Gulf of Mexico. Maps representing the occurrence of marsh surface inundation were created from available Advanced Land Observation Satellite (ALOS) Phased Array type L-Band SAR (PALSAR) (L-band) (21 scenes with HH polarizations in Wide Beam [100 m]) data and Environmental Satellite (ENVISAT) Advanced SAR (ASAR) (C-band) data (24 scenes with VV and HH polarizations in Wide Swath [150 m]) during 2006-2009 covering 500 km of the Louisiana coastal zone. Mapping was primarily based on a decrease in backscatter between reference and target scenes, and as an extension of previous studies, the flood inundation mapping performance was assessed by the degree of correspondence between inundation mapping and inland water levels. Both PALSAR- and ASAR-based mapping at times were based on suboptimal reference scenes; however, ASAR performance seemed more sensitive to reference-scene quality and other types of scene variability. Related to water depth, PALSAR and ASAR mapping accuracies tended to be lower when water depths were shallow and increased as water levels decreased below or increased above the ground surface, but this pattern was more pronounced with ASAR. Overall, PALSAR-based inundation accuracies averaged 84% (n = 160), while ASAR-based mapping accuracies averaged 62% (n = 245).

Scene analysis in the natural environment

DEFF Research Database (Denmark)

Lewicki, Michael S; Olshausen, Bruno A; Surlykke, Annemarie

2014-01-01

The problem of scene analysis has been studied in a number of different fields over the past decades. These studies have led to important insights into problems of scene analysis, but not all of these insights are widely appreciated, and there remain critical shortcomings in current approaches th...... ill-posed problems, (2) the ability to integrate and store information across time and modality, (3) efficient recovery and representation of 3D scene structure, and (4) the use of optimal motor actions for acquiring information to progress toward behavioral goals....

The time course of natural scene perception with reduced attention.

Science.gov (United States)

Groen, Iris I A; Ghebreab, Sennay; Lamme, Victor A F; Scholte, H Steven

2016-02-01

Attention is thought to impose an informational bottleneck on vision by selecting particular information from visual scenes for enhanced processing. Behavioral evidence suggests, however, that some scene information is extracted even when attention is directed elsewhere. Here, we investigated the neural correlates of this ability by examining how attention affects electrophysiological markers of scene perception. In two electro-encephalography (EEG) experiments, human subjects categorized real-world scenes as manmade or natural (full attention condition) or performed tasks on unrelated stimuli in the center or periphery of the scenes (reduced attention conditions). Scene processing was examined in two ways: traditional trial averaging was used to assess the presence of a categorical manmade/natural distinction in event-related potentials, whereas single-trial analyses assessed whether EEG activity was modulated by scene statistics that are diagnostic of naturalness of individual scenes. The results indicated that evoked activity up to 250 ms was unaffected by reduced attention, showing intact categorical differences between manmade and natural scenes and strong modulations of single-trial activity by scene statistics in all conditions. Thus initial processing of both categorical and individual scene information remained intact with reduced attention. Importantly, however, attention did have profound effects on later evoked activity; full attention on the scene resulted in prolonged manmade/natural differences, increased neural sensitivity to scene statistics, and enhanced scene memory. These results show that initial processing of real-world scene information is intact with diminished attention but that the depth of processing of this information does depend on attention. Copyright © 2016 the American Physiological Society.

An Algorithm for Morphological Segmentation of Esperanto Words

Directory of Open Access Journals (Sweden)

Guinard Theresa

2016-04-01

Full Text Available Morphological analysis (finding the component morphemes of a word and tagging morphemes with part-of-speech information is a useful preprocessing step in many natural language processing applications, especially for synthetic languages. Compound words from the constructed language Esperanto are formed by straightforward agglutination, but for many words, there is more than one possible sequence of component morphemes. However, one segmentation is usually more semantically probable than the others. This paper presents a modified n-gram Markov model that finds the most probable segmentation of any Esperanto word, where the model’s states represent morpheme part-of-speech and semantic classes. The overall segmentation accuracy was over 98% for a set of presegmented dictionary words.

Interaction between scene-based and array-based contextual cueing.

Science.gov (United States)

Rosenbaum, Gail M; Jiang, Yuhong V

2013-07-01

Contextual cueing refers to the cueing of spatial attention by repeated spatial context. Previous studies have demonstrated distinctive properties of contextual cueing by background scenes and by an array of search items. Whereas scene-based contextual cueing reflects explicit learning of the scene-target association, array-based contextual cueing is supported primarily by implicit learning. In this study, we investigated the interaction between scene-based and array-based contextual cueing. Participants searched for a target that was predicted by both the background scene and the locations of distractor items. We tested three possible patterns of interaction: (1) The scene and the array could be learned independently, in which case cueing should be expressed even when only one cue was preserved; (2) the scene and array could be learned jointly, in which case cueing should occur only when both cues were preserved; (3) overshadowing might occur, in which case learning of the stronger cue should preclude learning of the weaker cue. In several experiments, we manipulated the nature of the contextual cues present during training and testing. We also tested explicit awareness of scenes, scene-target associations, and arrays. The results supported the overshadowing account: Specifically, scene-based contextual cueing precluded array-based contextual cueing when both were predictive of the location of a search target. We suggest that explicit, endogenous cues dominate over implicit cues in guiding spatial attention.

Semantic guidance of eye movements in real-world scenes.

Science.gov (United States)

Hwang, Alex D; Wang, Hsueh-Cheng; Pomplun, Marc

2011-05-25

The perception of objects in our visual world is influenced by not only their low-level visual features such as shape and color, but also their high-level features such as meaning and semantic relations among them. While it has been shown that low-level features in real-world scenes guide eye movements during scene inspection and search, the influence of semantic similarity among scene objects on eye movements in such situations has not been investigated. Here we study guidance of eye movements by semantic similarity among objects during real-world scene inspection and search. By selecting scenes from the LabelMe object-annotated image database and applying latent semantic analysis (LSA) to the object labels, we generated semantic saliency maps of real-world scenes based on the semantic similarity of scene objects to the currently fixated object or the search target. An ROC analysis of these maps as predictors of subjects' gaze transitions between objects during scene inspection revealed a preference for transitions to objects that were semantically similar to the currently inspected one. Furthermore, during the course of a scene search, subjects' eye movements were progressively guided toward objects that were semantically similar to the search target. These findings demonstrate substantial semantic guidance of eye movements in real-world scenes and show its importance for understanding real-world attentional control. Copyright © 2011 Elsevier Ltd. All rights reserved.

Gaussian multiscale aggregation applied to segmentation in hand biometrics.

Science.gov (United States)

de Santos Sierra, Alberto; Avila, Carmen Sánchez; Casanova, Javier Guerra; del Pozo, Gonzalo Bailador

2011-01-01

This paper presents an image segmentation algorithm based on Gaussian multiscale aggregation oriented to hand biometric applications. The method is able to isolate the hand from a wide variety of background textures such as carpets, fabric, glass, grass, soil or stones. The evaluation was carried out by using a publicly available synthetic database with 408,000 hand images in different backgrounds, comparing the performance in terms of accuracy and computational cost to two competitive segmentation methods existing in literature, namely Lossy Data Compression (LDC) and Normalized Cuts (NCuts). The results highlight that the proposed method outperforms current competitive segmentation methods with regard to computational cost, time performance, accuracy and memory usage.

Study on Detection and Localization Algorithm of Traffic Signs from Natural Scenes

Directory of Open Access Journals (Sweden)

Xian-Zhong Han

2014-08-01

Full Text Available Automatic detection and location of traffic signs is an important part of intelligent transportation, especially for unmanned vehicle technology research. For the morphological feature of China road traffic signs, we propose a traffic sign detection method based on color segmentation and shape analysis. Firstly, in order to solve the problems of traffic signs color cast, distortion, and cross-color in natural scenes, the images are processed by white balance, Retinex color enhancement, and affine transformation. Then, the type of traffic signs is discriminated and detected, according to the color and shape characteristics of traffic signs. The experimental results show that this method can effectively detect and recognize traffic signs.

In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation

Directory of Open Access Journals (Sweden)

Chunlei Xia

2015-08-01

Full Text Available In this paper, we present a challenging task of 3D segmentation of individual plant leaves from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to improve the robustness of plant leaf segmentation. The low cost RGB-D camera is utilized to capture depth and color image in fields. Mean shift clustering is applied to segment plant leaves in depth image. Plant leaves are extracted from the natural background by examining vegetation of the candidate segments produced by mean shift. Subsequently, individual leaves are segmented from occlusions by active contour models. Automatic initialization of the active contour models is implemented by calculating the center of divergence from the gradient vector field of depth image. The proposed segmentation scheme is tested through experiments under greenhouse conditions. The overall segmentation rate is 87.97% while segmentation rates for single and occluded leaves are 92.10% and 86.67%, respectively. Approximately half of the experimental results show segmentation rates of individual leaves higher than 90%. Nevertheless, the proposed method is able to segment individual leaves from heavy occlusions.

Multi- and hyperspectral scene modeling

Science.gov (United States)

Borel, Christoph C.; Tuttle, Ronald F.

2011-06-01

This paper shows how to use a public domain raytracer POV-Ray (Persistence Of Vision Raytracer) to render multiand hyper-spectral scenes. The scripting environment allows automatic changing of the reflectance and transmittance parameters. The radiosity rendering mode allows accurate simulation of multiple-reflections between surfaces and also allows semi-transparent surfaces such as plant leaves. We show that POV-Ray computes occlusion accurately using a test scene with two blocks under a uniform sky. A complex scene representing a plant canopy is generated using a few lines of script. With appropriate rendering settings, shadows cast by leaves are rendered in many bands. Comparing single and multiple reflection renderings, the effect of multiple reflections is clearly visible and accounts for 25% of the overall apparent canopy reflectance in the near infrared.

Study of system for segmentation of images and elaboration of algorithms for three dimensional scene reconstruction

International Nuclear Information System (INIS)

Bufacchi, A.; Tripi, A.

1995-09-01

The aim of this paper is the presentation of a series of methodologies to recognize and to obtain a three-dimensional reconstruction of an inner architectural scene, using a gray level image obtained using a TV camera. In the first part of the work, a series of methods used to find the edges in an effective way are critically compared, obtaining a binary image, and then the application of the Hough transform to such binary image to find the straight lines in the original image are discussed. In the second part, an algorithm is shown in order to find the vanishing points in such image

CLASSIFIER FUSION OF HIGH-RESOLUTION OPTICAL AND SYNTHETIC APERTURE RADAR (SAR SATELLITE IMAGERY FOR CLASSIFICATION IN URBAN AREA

Directory of Open Access Journals (Sweden)

T. Alipour Fard

2014-10-01

Full Text Available This study concerned with fusion of synthetic aperture radar and optical satellite imagery. Due to the difference in the underlying sensor technology, data from synthetic aperture radar (SAR and optical sensors refer to different properties of the observed scene and it is believed that when they are fused together, they complement each other to improve the performance of a particular application. In this paper, two category of features are generate and six classifier fusion operators implemented and evaluated. Implementation results show significant improvement in the classification accuracy.

Primal scene derivatives in the work of Yukio Mishima: the primal scene fantasy.

Science.gov (United States)

Turco, Ronald N

2002-01-01

This article discusses the preoccupation with fire, revenge, crucifixion, and other fantasies as they relate to the primal scene. The manifestations of these fantasies are demonstrated in a work of fiction by Yukio Mishima. The Temple of the Golden Pavillion. As is the case in other writings of Mishima there is a fusion of aggressive and libidinal drives and a preoccupation with death. The primal scene is directly connected with pyromania and destructive "acting out" of fantasies. This article is timely with regard to understanding contemporary events of cultural and national destruction.

Emotional and neutral scenes in competition: orienting, efficiency, and identification.

Science.gov (United States)

Calvo, Manuel G; Nummenmaa, Lauri; Hyönä, Jukka

2007-12-01

To investigate preferential processing of emotional scenes competing for limited attentional resources with neutral scenes, prime pictures were presented briefly (450 ms), peripherally (5.2 degrees away from fixation), and simultaneously (one emotional and one neutral scene) versus singly. Primes were followed by a mask and a probe for recognition. Hit rate was higher for emotional than for neutral scenes in the dual- but not in the single-prime condition, and A' sensitivity decreased for neutral but not for emotional scenes in the dual-prime condition. This preferential processing involved both selective orienting and efficient encoding, as revealed, respectively, by a higher probability of first fixation on--and shorter saccade latencies to--emotional scenes and by shorter fixation time needed to accurately identify emotional scenes, in comparison with neutral scenes.

Scene Integration for Online VR Advertising Clouds

Directory of Open Access Journals (Sweden)

Michael Kalochristianakis

2014-12-01

Full Text Available This paper presents a scene composition approach that allows the combinational use of standard three dimensional objects, called models, in order to create X3D scenes. The module is an integral part of a broader design aiming to construct large scale online advertising infrastructures that rely on virtual reality technologies. The architecture addresses a number of problems regarding remote rendering for low end devices and last but not least, the provision of scene composition and integration. Since viewers do not keep information regarding individual input models or scenes, composition requires the consideration of mechanisms that add state to viewing technologies. In terms of this work we extended a well-known, open source X3D authoring tool.

Three-dimensional measurement system for crime scene documentation

Science.gov (United States)

Adamczyk, Marcin; Hołowko, Elwira; Lech, Krzysztof; Michoński, Jakub; MÄ czkowski, Grzegorz; Bolewicki, Paweł; Januszkiewicz, Kamil; Sitnik, Robert

2017-10-01

Three dimensional measurements (such as photogrammetry, Time of Flight, Structure from Motion or Structured Light techniques) are becoming a standard in the crime scene documentation process. The usage of 3D measurement techniques provide an opportunity to prepare more insightful investigation and helps to show every trace in the context of the entire crime scene. In this paper we would like to present a hierarchical, three-dimensional measurement system that is designed for crime scenes documentation process. Our system reflects the actual standards in crime scene documentation process - it is designed to perform measurement in two stages. First stage of documentation, the most general, is prepared with a scanner with relatively low spatial resolution but also big measuring volume - it is used for the whole scene documentation. Second stage is much more detailed: high resolution but smaller size of measuring volume for areas that required more detailed approach. The documentation process is supervised by a specialised application CrimeView3D, that is a software platform for measurements management (connecting with scanners and carrying out measurements, automatic or semi-automatic data registration in the real time) and data visualisation (3D visualisation of documented scenes). It also provides a series of useful tools for forensic technicians: virtual measuring tape, searching for sources of blood spatter, virtual walk on the crime scene and many others. In this paper we present our measuring system and the developed software. We also provide an outcome from research on metrological validation of scanners that was performed according to VDI/VDE standard. We present a CrimeView3D - a software-platform that was developed to manage the crime scene documentation process. We also present an outcome from measurement sessions that were conducted on real crime scenes with cooperation with Technicians from Central Forensic Laboratory of Police.

The roles of scene gist and spatial dependency among objects in the semantic guidance of attention in real-world scenes.

Science.gov (United States)

Wu, Chia-Chien; Wang, Hsueh-Cheng; Pomplun, Marc

2014-12-01

A previous study (Vision Research 51 (2011) 1192-1205) found evidence for semantic guidance of visual attention during the inspection of real-world scenes, i.e., an influence of semantic relationships among scene objects on overt shifts of attention. In particular, the results revealed an observer bias toward gaze transitions between semantically similar objects. However, this effect is not necessarily indicative of semantic processing of individual objects but may be mediated by knowledge of the scene gist, which does not require object recognition, or by known spatial dependency among objects. To examine the mechanisms underlying semantic guidance, in the present study, participants were asked to view a series of displays with the scene gist excluded and spatial dependency varied. Our results show that spatial dependency among objects seems to be sufficient to induce semantic guidance. Scene gist, on the other hand, does not seem to affect how observers use semantic information to guide attention while viewing natural scenes. Extracting semantic information mainly based on spatial dependency may be an efficient strategy of the visual system that only adds little cognitive load to the viewing task. Copyright © 2014 Elsevier Ltd. All rights reserved.

A bio-inspired method and system for visual object-based attention and segmentation

Science.gov (United States)

Huber, David J.; Khosla, Deepak

2010-04-01

This paper describes a method and system of human-like attention and object segmentation in visual scenes that (1) attends to regions in a scene in their rank of saliency in the image, (2) extracts the boundary of an attended proto-object based on feature contours, and (3) can be biased to boost the attention paid to specific features in a scene, such as those of a desired target object in static and video imagery. The purpose of the system is to identify regions of a scene of potential importance and extract the region data for processing by an object recognition and classification algorithm. The attention process can be performed in a default, bottom-up manner or a directed, top-down manner which will assign a preference to certain features over others. One can apply this system to any static scene, whether that is a still photograph or imagery captured from video. We employ algorithms that are motivated by findings in neuroscience, psychology, and cognitive science to construct a system that is novel in its modular and stepwise approach to the problems of attention and region extraction, its application of a flooding algorithm to break apart an image into smaller proto-objects based on feature density, and its ability to join smaller regions of similar features into larger proto-objects. This approach allows many complicated operations to be carried out by the system in a very short time, approaching real-time. A researcher can use this system as a robust front-end to a larger system that includes object recognition and scene understanding modules; it is engineered to function over a broad range of situations and can be applied to any scene with minimal tuning from the user.

Moving through a multiplex holographic scene

Science.gov (United States)

Mrongovius, Martina

2013-02-01

This paper explores how movement can be used as a compositional element in installations of multiplex holograms. My holographic images are created from montages of hand-held video and photo-sequences. These spatially dynamic compositions are visually complex but anchored to landmarks and hints of the capturing process - such as the appearance of the photographer's shadow - to establish a sense of connection to the holographic scene. Moving around in front of the hologram, the viewer animates the holographic scene. A perception of motion then results from the viewer's bodily awareness of physical motion and the visual reading of dynamics within the scene or movement of perspective through a virtual suggestion of space. By linking and transforming the physical motion of the viewer with the visual animation, the viewer's bodily awareness - including proprioception, balance and orientation - play into the holographic composition. How multiplex holography can be a tool for exploring coupled, cross-referenced and transformed perceptions of movement is demonstrated with a number of holographic image installations. Through this process I expanded my creative composition practice to consider how dynamic and spatial scenes can be conveyed through the fragmented view of a multiplex hologram. This body of work was developed through an installation art practice and was the basis of my recently completed doctoral thesis: 'The Emergent Holographic Scene — compositions of movement and affect using multiplex holographic images'.

Synthetic tsunami waveform catalogs with kinematic constraints

Science.gov (United States)

Baptista, Maria Ana; Miranda, Jorge Miguel; Matias, Luis; Omira, Rachid

2017-07-01

In this study we present a comprehensive methodology to produce a synthetic tsunami waveform catalogue in the northeast Atlantic, east of the Azores islands. The method uses a synthetic earthquake catalogue compatible with plate kinematic constraints of the area. We use it to assess the tsunami hazard from the transcurrent boundary located between Iberia and the Azores, whose western part is known as the Gloria Fault. This study focuses only on earthquake-generated tsunamis. Moreover, we assume that the time and space distribution of the seismic events is known. To do this, we compute a synthetic earthquake catalogue including all fault parameters needed to characterize the seafloor deformation covering the time span of 20 000 years, which we consider long enough to ensure the representability of earthquake generation on this segment of the plate boundary. The computed time and space rupture distributions are made compatible with global kinematic plate models. We use the tsunami empirical Green's functions to efficiently compute the synthetic tsunami waveforms for the dataset of coastal locations, thus providing the basis for tsunami impact characterization. We present the results in the form of offshore wave heights for all coastal points in the dataset. Our results focus on the northeast Atlantic basin, showing that earthquake-induced tsunamis in the transcurrent segment of the Azores-Gibraltar plate boundary pose a minor threat to coastal areas north of Portugal and beyond the Strait of Gibraltar. However, in Morocco, the Azores, and the Madeira islands, we can expect wave heights between 0.6 and 0.8 m, leading to precautionary evacuation of coastal areas. The advantages of the method are its easy application to other regions and the low computation effort needed.

Monitoring coastal inundation with Synthetic Aperture Radar satellite data

Science.gov (United States)

Suzuoki, Yukihiro; Rangoonwala, Amina; Ramsey, Elijah W.

2011-01-01

Maps representing the presence and absence of surface inundation in the Louisiana coastal zone were created from available satellite scenes acquired by the Japanese Aerospace Exploration Agency's Advanced Land Observing Satellite and by the European Space Agency's Envisat from late 2006 through summer 2009. Detection of aboveground surface flooding relied on the well-documented and distinct signature of decreased backscatter in Synthetic Aperture Radar (SAR), which is indicative of inundated marsh in the Gulf of Mexico. Even though decreases in backscatter were distinctive, the multiplicity of possible interactions between changing flood depths and canopy height yielded complex SAR-based representations of the marshes.

IR characteristic simulation of city scenes based on radiosity model

Science.gov (United States)

Xiong, Xixian; Zhou, Fugen; Bai, Xiangzhi; Yu, Xiyu

2013-09-01

Reliable modeling for thermal infrared (IR) signatures of real-world city scenes is required for signature management of civil and military platforms. Traditional modeling methods generally assume that scene objects are individual entities during the physical processes occurring in infrared range. However, in reality, the physical scene involves convective and conductive interactions between objects as well as the radiations interactions between objects. A method based on radiosity model describes these complex effects. It has been developed to enable an accurate simulation for the radiance distribution of the city scenes. Firstly, the physical processes affecting the IR characteristic of city scenes were described. Secondly, heat balance equations were formed on the basis of combining the atmospheric conditions, shadow maps and the geometry of scene. Finally, finite difference method was used to calculate the kinetic temperature of object surface. A radiosity model was introduced to describe the scattering effect of radiation between surface elements in the scene. By the synthesis of objects radiance distribution in infrared range, we could obtain the IR characteristic of scene. Real infrared images and model predictions were shown and compared. The results demonstrate that this method can realistically simulate the IR characteristic of city scenes. It effectively displays the infrared shadow effects and the radiation interactions between objects in city scenes.

Gaussian Multiscale Aggregation Applied to Segmentation in Hand Biometrics

Directory of Open Access Journals (Sweden)

Gonzalo Bailador del Pozo

2011-11-01

Full Text Available This paper presents an image segmentation algorithm based on Gaussian multiscale aggregation oriented to hand biometric applications. The method is able to isolate the hand from a wide variety of background textures such as carpets, fabric, glass, grass, soil or stones. The evaluation was carried out by using a publicly available synthetic database with 408,000 hand images in different backgrounds, comparing the performance in terms of accuracy and computational cost to two competitive segmentation methods existing in literature, namely Lossy Data Compression (LDC and Normalized Cuts (NCuts. The results highlight that the proposed method outperforms current competitive segmentation methods with regard to computational cost, time performance, accuracy and memory usage.

Global scene layout modulates contextual learning in change detection

Directory of Open Access Journals (Sweden)

Markus eConci

2014-02-01

Full Text Available Change in the visual scene often goes unnoticed – a phenomenon referred to as ‘change blindness’. This study examined whether the hierarchical structure, i.e., the global-local layout of a scene can influence performance in a one-shot change detection paradigm. To this end, natural scenes of a laid breakfast table were presented, and observers were asked to locate the onset of a new local object. Importantly, the global structure of the scene was manipulated by varying the relations among objects in the scene layouts. The very same items were either presented as global-congruent (typical layouts or as global-incongruent (random arrangements. Change blindness was less severe for congruent than for incongruent displays, and this congruency benefit increased with the duration of the experiment. These findings show that global layouts are learned, supporting detection of local changes with enhanced efficiency. However, performance was not affected by scene congruency in a subsequent control experiment that required observers to localize a static discontinuity (i.e., an object that was missing from the repeated layouts. Our results thus show that learning of the global layout is particularly linked to the local objects. Taken together, our results reveal an effect of global precedence in natural scenes. We suggest that relational properties within the hierarchy of a natural scene are governed, in particular, by global image analysis, reducing change blindness for local objects through scene learning.

Global scene layout modulates contextual learning in change detection.

Science.gov (United States)

Conci, Markus; Müller, Hermann J

2014-01-01

Change in the visual scene often goes unnoticed - a phenomenon referred to as "change blindness." This study examined whether the hierarchical structure, i.e., the global-local layout of a scene can influence performance in a one-shot change detection paradigm. To this end, natural scenes of a laid breakfast table were presented, and observers were asked to locate the onset of a new local object. Importantly, the global structure of the scene was manipulated by varying the relations among objects in the scene layouts. The very same items were either presented as global-congruent (typical) layouts or as global-incongruent (random) arrangements. Change blindness was less severe for congruent than for incongruent displays, and this congruency benefit increased with the duration of the experiment. These findings show that global layouts are learned, supporting detection of local changes with enhanced efficiency. However, performance was not affected by scene congruency in a subsequent control experiment that required observers to localize a static discontinuity (i.e., an object that was missing from the repeated layouts). Our results thus show that learning of the global layout is particularly linked to the local objects. Taken together, our results reveal an effect of "global precedence" in natural scenes. We suggest that relational properties within the hierarchy of a natural scene are governed, in particular, by global image analysis, reducing change blindness for local objects through scene learning.

The primal scene and symbol formation.

Science.gov (United States)

Niedecken, Dietmut

2016-06-01

This article discusses the meaning of the primal scene for symbol formation by exploring its way of processing in a child's play. The author questions the notion that a sadomasochistic way of processing is the only possible one. A model of an alternative mode of processing is being presented. It is suggested that both ways of processing intertwine in the "fabric of life" (D. Laub). Two clinical vignettes, one from an analytic child psychotherapy and the other from the analysis of a 30 year-old female patient, illustrate how the primal scene is being played out in the form of a terzet. The author explores whether the sadomasochistic way of processing actually precedes the "primal scene as a terzet". She discusses if it could even be regarded as a precondition for the formation of the latter or, alternatively, if the "combined parent-figure" gives rise to ways of processing. The question is being left open. Finally, it is shown how both modes of experiencing the primal scene underlie the discoursive and presentative symbol formation, respectively. Copyright © 2015 Institute of Psychoanalysis.

Modeling global scene factors in attention

Science.gov (United States)

Torralba, Antonio

2003-07-01

Models of visual attention have focused predominantly on bottom-up approaches that ignored structured contextual and scene information. I propose a model of contextual cueing for attention guidance based on the global scene configuration. It is shown that the statistics of low-level features across the whole image can be used to prime the presence or absence of objects in the scene and to predict their location, scale, and appearance before exploring the image. In this scheme, visual context information can become available early in the visual processing chain, which allows modulation of the saliency of image regions and provides an efficient shortcut for object detection and recognition. 2003 Optical Society of America

Camera Motion and Surrounding Scene Appearance as Context for Action Recognition

KAUST Repository

Heilbron, Fabian Caba; Thabet, Ali Kassem; Niebles, Juan Carlos; Ghanem, Bernard

2015-01-01

This paper describes a framework for recognizing human actions in videos by incorporating a new set of visual cues that represent the context of the action. We develop a weak foreground-background segmentation approach in order to robustly extract not only foreground features that are focused on the actors, but also global camera motion and contextual scene information. Using dense point trajectories, our approach separates and describes the foreground motion from the background, represents the appearance of the extracted static background, and encodes the global camera motion that interestingly is shown to be discriminative for certain action classes. Our experiments on four challenging benchmarks (HMDB51, Hollywood2, Olympic Sports, and UCF50) show that our contextual features enable a significant performance improvement over state-of-the-art algorithms.

Camera Motion and Surrounding Scene Appearance as Context for Action Recognition

KAUST Repository

Heilbron, Fabian Caba

2015-04-17

This paper describes a framework for recognizing human actions in videos by incorporating a new set of visual cues that represent the context of the action. We develop a weak foreground-background segmentation approach in order to robustly extract not only foreground features that are focused on the actors, but also global camera motion and contextual scene information. Using dense point trajectories, our approach separates and describes the foreground motion from the background, represents the appearance of the extracted static background, and encodes the global camera motion that interestingly is shown to be discriminative for certain action classes. Our experiments on four challenging benchmarks (HMDB51, Hollywood2, Olympic Sports, and UCF50) show that our contextual features enable a significant performance improvement over state-of-the-art algorithms.

Simultaneous two-view epipolar geometry estimation and motion segmentation by 4D tensor voting.

Science.gov (United States)

Tong, Wai-Shun; Tang, Chi-Keung; Medioni, Gérard

2004-09-01

We address the problem of simultaneous two-view epipolar geometry estimation and motion segmentation from nonstatic scenes. Given a set of noisy image pairs containing matches of n objects, we propose an unconventional, efficient, and robust method, 4D tensor voting, for estimating the unknown n epipolar geometries, and segmenting the static and motion matching pairs into n independent motions. By considering the 4D isotropic and orthogonal joint image space, only two tensor voting passes are needed, and a very high noise to signal ratio (up to five) can be tolerated. Epipolar geometries corresponding to multiple, rigid motions are extracted in succession. Only two uncalibrated frames are needed, and no simplifying assumption (such as affine camera model or homographic model between images) other than the pin-hole camera model is made. Our novel approach consists of propagating a local geometric smoothness constraint in the 4D joint image space, followed by global consistency enforcement for extracting the fundamental matrices corresponding to independent motions. We have performed extensive experiments to compare our method with some representative algorithms to show that better performance on nonstatic scenes are achieved. Results on challenging data sets are presented.

47 CFR 80.1127 - On-scene communications.

Science.gov (United States)

2010-10-01

....1127 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) SAFETY AND SPECIAL RADIO SERVICES STATIONS IN THE MARITIME SERVICES Global Maritime Distress and Safety System (GMDSS) Operating Procedures for Distress and Safety Communications § 80.1127 On-scene communications. (a) On-scene communications...

Effect of synthetic cell-binding peptide on the healing of cortical segmental bone defects

International Nuclear Information System (INIS)

Cakmak, G.; Bolukbasi, S.; Simsek, A.; Senkoylu, A.; Erdem, O.; Yilmaz, G.

2006-01-01

To determine the effect of inorganic bone matric/Pepgen P-15 (ABM/P-15) on the healing of a critical sized segmental defect in a rat radius using a radiological and histological grading system. We carried out this study at the Research Laboratories, Gazi University School of Medicine in 2004. Critical sized segmental defects were created in the radius of 36 Wistar rats. Thirteen defects were filled with ABM/P-15 Flow (gel form), 12 defects were filled with ABM/P-15, and 11 defects were used as a control group. The rats were sacrified at the tenth week, and healing of the defects was evaluated radiographically and histologically. The usage of ABM/P-15 and ABM/P-15 Flow were demonstrated to improve healing of segmental bone defects compared with the control group. Statistical evaluation showed that there were significant differences between control sites, and the sites treated with P-15 and P-15 Flow (p=0.011). The highest radiological and histological grades were achieved by P-15. Segmental cortical bone defects may be treated with ABM/P-15 instead of bone allografts, and autografts. According to the radiological and histological parameters measured in this study, the implantation of ABM/P-15 resulted in optimum healing of the segmental cortical bone defects. Pepgen P-15 has a positive effect on bone healing, without any immunogenic features and disease transmission risk. Therefore, ABM/P-15 can also be used for orthopedic surgery. (author)

The occipital place area represents the local elements of scenes.

Science.gov (United States)

Kamps, Frederik S; Julian, Joshua B; Kubilius, Jonas; Kanwisher, Nancy; Dilks, Daniel D

2016-05-15

Neuroimaging studies have identified three scene-selective regions in human cortex: parahippocampal place area (PPA), retrosplenial complex (RSC), and occipital place area (OPA). However, precisely what scene information each region represents is not clear, especially for the least studied, more posterior OPA. Here we hypothesized that OPA represents local elements of scenes within two independent, yet complementary scene descriptors: spatial boundary (i.e., the layout of external surfaces) and scene content (e.g., internal objects). If OPA processes the local elements of spatial boundary information, then it should respond to these local elements (e.g., walls) themselves, regardless of their spatial arrangement. Indeed, we found that OPA, but not PPA or RSC, responded similarly to images of intact rooms and these same rooms in which the surfaces were fractured and rearranged, disrupting the spatial boundary. Next, if OPA represents the local elements of scene content information, then it should respond more when more such local elements (e.g., furniture) are present. Indeed, we found that OPA, but not PPA or RSC, responded more to multiple than single pieces of furniture. Taken together, these findings reveal that OPA analyzes local scene elements - both in spatial boundary and scene content representation - while PPA and RSC represent global scene properties. Copyright © 2016 Elsevier Inc. All rights reserved.

SAR Imagery Segmentation by Statistical Region Growing and Hierarchical Merging

Energy Technology Data Exchange (ETDEWEB)

Ushizima, Daniela Mayumi; Carvalho, E.A.; Medeiros, F.N.S.; Martins, C.I.O.; Marques, R.C.P.; Oliveira, I.N.S.

2010-05-22

This paper presents an approach to accomplish synthetic aperture radar (SAR) image segmentation, which are corrupted by speckle noise. Some ordinary segmentation techniques may require speckle filtering previously. Our approach performs radar image segmentation using the original noisy pixels as input data, eliminating preprocessing steps, an advantage over most of the current methods. The algorithm comprises a statistical region growing procedure combined with hierarchical region merging to extract regions of interest from SAR images. The region growing step over-segments the input image to enable region aggregation by employing a combination of the Kolmogorov-Smirnov (KS) test with a hierarchical stepwise optimization (HSWO) algorithm for the process coordination. We have tested and assessed the proposed technique on artificially speckled image and real SAR data containing different types of targets.

Accumulating and remembering the details of neutral and emotional natural scenes.

Science.gov (United States)

Melcher, David

2010-01-01

In contrast to our rich sensory experience with complex scenes in everyday life, the capacity of visual working memory is thought to be quite limited. Here our memory has been examined for the details of naturalistic scenes as a function of display duration, emotional valence of the scene, and delay before test. Individual differences in working memory and long-term memory for pictorial scenes were examined in experiment 1. The accumulation of memory for emotional scenes and the retention of these details in long-term memory were investigated in experiment 2. Although there were large individual differences in performance, memory for scene details generally exceeded the traditional working memory limit within a few seconds. Information about positive scenes was learned most quickly, while negative scenes showed the worst memory for details. The overall pattern of results was consistent with the idea that both short-term and long-term representations are mixed together in a medium-term 'online' memory for scenes.

3D Traffic Scene Understanding From Movable Platforms.

Science.gov (United States)

Geiger, Andreas; Lauer, Martin; Wojek, Christian; Stiller, Christoph; Urtasun, Raquel

2014-05-01

In this paper, we present a novel probabilistic generative model for multi-object traffic scene understanding from movable platforms which reasons jointly about the 3D scene layout as well as the location and orientation of objects in the scene. In particular, the scene topology, geometry, and traffic activities are inferred from short video sequences. Inspired by the impressive driving capabilities of humans, our model does not rely on GPS, lidar, or map knowledge. Instead, it takes advantage of a diverse set of visual cues in the form of vehicle tracklets, vanishing points, semantic scene labels, scene flow, and occupancy grids. For each of these cues, we propose likelihood functions that are integrated into a probabilistic generative model. We learn all model parameters from training data using contrastive divergence. Experiments conducted on videos of 113 representative intersections show that our approach successfully infers the correct layout in a variety of very challenging scenarios. To evaluate the importance of each feature cue, experiments using different feature combinations are conducted. Furthermore, we show how by employing context derived from the proposed method we are able to improve over the state-of-the-art in terms of object detection and object orientation estimation in challenging and cluttered urban environments.

Feature diagnosticity and task context shape activity in human scene-selective cortex.

Science.gov (United States)

Lowe, Matthew X; Gallivan, Jason P; Ferber, Susanne; Cant, Jonathan S

2016-01-15

Scenes are constructed from multiple visual features, yet previous research investigating scene processing has often focused on the contributions of single features in isolation. In the real world, features rarely exist independently of one another and likely converge to inform scene identity in unique ways. Here, we utilize fMRI and pattern classification techniques to examine the interactions between task context (i.e., attend to diagnostic global scene features; texture or layout) and high-level scene attributes (content and spatial boundary) to test the novel hypothesis that scene-selective cortex represents multiple visual features, the importance of which varies according to their diagnostic relevance across scene categories and task demands. Our results show for the first time that scene representations are driven by interactions between multiple visual features and high-level scene attributes. Specifically, univariate analysis of scene-selective cortex revealed that task context and feature diagnosticity shape activity differentially across scene categories. Examination using multivariate decoding methods revealed results consistent with univariate findings, but also evidence for an interaction between high-level scene attributes and diagnostic visual features within scene categories. Critically, these findings suggest visual feature representations are not distributed uniformly across scene categories but are shaped by task context and feature diagnosticity. Thus, we propose that scene-selective cortex constructs a flexible representation of the environment by integrating multiple diagnostically relevant visual features, the nature of which varies according to the particular scene being perceived and the goals of the observer. Copyright © 2015 Elsevier Inc. All rights reserved.

Maxwellian Eye Fixation during Natural Scene Perception

Directory of Open Access Journals (Sweden)

Jean Duchesne

2012-01-01

Full Text Available When we explore a visual scene, our eyes make saccades to jump rapidly from one area to another and fixate regions of interest to extract useful information. While the role of fixation eye movements in vision has been widely studied, their random nature has been a hitherto neglected issue. Here we conducted two experiments to examine the Maxwellian nature of eye movements during fixation. In Experiment 1, eight participants were asked to perform free viewing of natural scenes displayed on a computer screen while their eye movements were recorded. For each participant, the probability density function (PDF of eye movement amplitude during fixation obeyed the law established by Maxwell for describing molecule velocity in gas. Only the mean amplitude of eye movements varied with expertise, which was lower in experts than novice participants. In Experiment 2, two participants underwent fixed time, free viewing of natural scenes and of their scrambled version while their eye movements were recorded. Again, the PDF of eye movement amplitude during fixation obeyed Maxwell’s law for each participant and for each scene condition (normal or scrambled. The results suggest that eye fixation during natural scene perception describes a random motion regardless of top-down or of bottom-up processes.

Maxwellian Eye Fixation during Natural Scene Perception

Science.gov (United States)

Duchesne, Jean; Bouvier, Vincent; Guillemé, Julien; Coubard, Olivier A.

2012-01-01

When we explore a visual scene, our eyes make saccades to jump rapidly from one area to another and fixate regions of interest to extract useful information. While the role of fixation eye movements in vision has been widely studied, their random nature has been a hitherto neglected issue. Here we conducted two experiments to examine the Maxwellian nature of eye movements during fixation. In Experiment 1, eight participants were asked to perform free viewing of natural scenes displayed on a computer screen while their eye movements were recorded. For each participant, the probability density function (PDF) of eye movement amplitude during fixation obeyed the law established by Maxwell for describing molecule velocity in gas. Only the mean amplitude of eye movements varied with expertise, which was lower in experts than novice participants. In Experiment 2, two participants underwent fixed time, free viewing of natural scenes and of their scrambled version while their eye movements were recorded. Again, the PDF of eye movement amplitude during fixation obeyed Maxwell's law for each participant and for each scene condition (normal or scrambled). The results suggest that eye fixation during natural scene perception describes a random motion regardless of top-down or of bottom-up processes. PMID:23226987

Selective scene perception deficits in a case of topographical disorientation.

Science.gov (United States)

Robin, Jessica; Lowe, Matthew X; Pishdadian, Sara; Rivest, Josée; Cant, Jonathan S; Moscovitch, Morris

2017-07-01

Topographical disorientation (TD) is a neuropsychological condition characterized by an inability to find one's way, even in familiar environments. One common contributing cause of TD is landmark agnosia, a visual recognition impairment specific to scenes and landmarks. Although many cases of TD with landmark agnosia have been documented, little is known about the perceptual mechanisms which lead to selective deficits in recognizing scenes. In the present study, we test LH, a man who exhibits TD and landmark agnosia, on measures of scene perception that require selectively attending to either the configural or surface properties of a scene. Compared to healthy controls, LH demonstrates perceptual impairments when attending to the configuration of a scene, but not when attending to its surface properties, such as the pattern of the walls or whether the ground is sand or grass. In contrast, when focusing on objects instead of scenes, LH demonstrates intact perception of both geometric and surface properties. This study demonstrates that in a case of TD and landmark agnosia, the perceptual impairments are selective to the layout of scenes, providing insight into the mechanism of landmark agnosia and scene-selective perceptual processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hair testing to assess both known and unknown use of drugs amongst ecstasy users in the electronic dance music scene.

Science.gov (United States)

Palamar, Joseph J; Salomone, Alberto; Gerace, Enrico; Di Corcia, Daniele; Vincenti, Marco; Cleland, Charles M

2017-10-01

Data on both known and unknown drug use in the electronic dance music (EDM) scene is important to inform prevention and harm reduction. While surveys are the most common method of querying drug use, additional biological data can help validate use and detect unknown/unintentional use of drugs such as new psychoactive substances (NPS). We sought to determine the extent of both known and unknown use of various substances in this high-risk scene. We hair-tested 90 self-reported past-year ecstasy/MDMA/Molly users attending EDM parties in New York City during the summer of 2016 using UHPLC-MS/MS. Results were compared to self-reported past-year use. Three quarters (74.4%) tested positive for MDMA, a third (33.3%) tested positive for an NPS, and 27.8% tested positive specifically for one or more synthetic cathinones (e.g., butylone, ethylone, pentylone, methylone, alpha-PVP). Half (51.1%) of participants tested positive for a drug not self-reported, with most testing positive for synthetic cathinones (72.0%), methamphetamine (69.0%), other NPS stimulants (e.g., 4-FA, 5/6-APB; 66.7%), or new dissociatives (e.g., methoxetamine, diphenidine; 60.0%). Attending parties every other week or more often, reporting higher-frequency ecstasy pill use, having tested one's ecstasy, and having found out one's ecstasy was adulterated, were risk factors for testing positive for synthetic cathinones and NPS in general. Hair testing appears to be a valuable addition to drug epidemiology studies. Many EDM party attendees-even those who test their ecstasy-are unknowingly using NPS and/or other drugs. Prevention information and harm reduction may help reduce unknown/unintentional use. Copyright © 2017 Elsevier B.V. All rights reserved.

Crime Scenes as Augmented Reality

DEFF Research Database (Denmark)

Sandvik, Kjetil

2010-01-01

Using the concept of augmented reality, this article will investigate how places in various ways have become augmented by means of different mediatization strategies. Augmentation of reality implies an enhancement of the places' emotional character: a certain mood, atmosphere or narrative surplus......, physical damage: they are all readable and interpretable signs. As augmented reality the crime scene carries a narrative which at first is hidden and must be revealed. Due to the process of investigation and the detective's ability to reason and deduce, the crime scene as place is reconstructed as virtual...

Semi-Supervised Multitask Learning for Scene Recognition.

Science.gov (United States)

Lu, Xiaoqiang; Li, Xuelong; Mou, Lichao

2015-09-01

Scene recognition has been widely studied to understand visual information from the level of objects and their relationships. Toward scene recognition, many methods have been proposed. They, however, encounter difficulty to improve the accuracy, mainly due to two limitations: 1) lack of analysis of intrinsic relationships across different scales, say, the initial input and its down-sampled versions and 2) existence of redundant features. This paper develops a semi-supervised learning mechanism to reduce the above two limitations. To address the first limitation, we propose a multitask model to integrate scene images of different resolutions. For the second limitation, we build a model of sparse feature selection-based manifold regularization (SFSMR) to select the optimal information and preserve the underlying manifold structure of data. SFSMR coordinates the advantages of sparse feature selection and manifold regulation. Finally, we link the multitask model and SFSMR, and propose the semi-supervised learning method to reduce the two limitations. Experimental results report the improvements of the accuracy in scene recognition.

Perception of synthetic speech produced automatically by rule: Intelligibility of eight text-to-speech systems.

Science.gov (United States)

Greene, Beth G; Logan, John S; Pisoni, David B

1986-03-01

We present the results of studies designed to measure the segmental intelligibility of eight text-to-speech systems and a natural speech control, using the Modified Rhyme Test (MRT). Results indicated that the voices tested could be grouped into four categories: natural speech, high-quality synthetic speech, moderate-quality synthetic speech, and low-quality synthetic speech. The overall performance of the best synthesis system, DECtalk-Paul, was equivalent to natural speech only in terms of performance on initial consonants. The findings are discussed in terms of recent work investigating the perception of synthetic speech under more severe conditions. Suggestions for future research on improving the quality of synthetic speech are also considered.

Perception of synthetic speech produced automatically by rule: Intelligibility of eight text-to-speech systems

Science.gov (United States)

GREENE, BETH G.; LOGAN, JOHN S.; PISONI, DAVID B.

2012-01-01

We present the results of studies designed to measure the segmental intelligibility of eight text-to-speech systems and a natural speech control, using the Modified Rhyme Test (MRT). Results indicated that the voices tested could be grouped into four categories: natural speech, high-quality synthetic speech, moderate-quality synthetic speech, and low-quality synthetic speech. The overall performance of the best synthesis system, DECtalk-Paul, was equivalent to natural speech only in terms of performance on initial consonants. The findings are discussed in terms of recent work investigating the perception of synthetic speech under more severe conditions. Suggestions for future research on improving the quality of synthetic speech are also considered. PMID:23225916

Optimising Realism of Synthetic Agricultural Images using Cycle Generative Adversarial Networks

NARCIS (Netherlands)

Barth, R.; IJsselmuiden, J.M.M.; Hemming, J.; Henten, van E.J.

2017-01-01

A bottleneck of state-of-the-art machine learning methods, e.g. deep learning, for plant part image segmentation in agricultural robotics is the requirement of large manually annotated datasets. As a solution, large synthetic datasets including ground truth can be rendered that realistically reflect

Fast Edge Detection and Segmentation of Terrestrial Laser Scans Through Normal Variation Analysis

Science.gov (United States)

Che, E.; Olsen, M. J.

2017-09-01

Terrestrial Laser Scanning (TLS) utilizes light detection and ranging (lidar) to effectively and efficiently acquire point cloud data for a wide variety of applications. Segmentation is a common procedure of post-processing to group the point cloud into a number of clusters to simplify the data for the sequential modelling and analysis needed for most applications. This paper presents a novel method to rapidly segment TLS data based on edge detection and region growing. First, by computing the projected incidence angles and performing the normal variation analysis, the silhouette edges and intersection edges are separated from the smooth surfaces. Then a modified region growing algorithm groups the points lying on the same smooth surface. The proposed method efficiently exploits the gridded scan pattern utilized during acquisition of TLS data from most sensors and takes advantage of parallel programming to process approximately 1 million points per second. Moreover, the proposed segmentation does not require estimation of the normal at each point, which limits the errors in normal estimation propagating to segmentation. Both an indoor and outdoor scene are used for an experiment to demonstrate and discuss the effectiveness and robustness of the proposed segmentation method.

Political conservatism predicts asymmetries in emotional scene memory.

Science.gov (United States)

Mills, Mark; Gonzalez, Frank J; Giuseffi, Karl; Sievert, Benjamin; Smith, Kevin B; Hibbing, John R; Dodd, Michael D

2016-06-01

Variation in political ideology has been linked to differences in attention to and processing of emotional stimuli, with stronger responses to negative versus positive stimuli (negativity bias) the more politically conservative one is. As memory is enhanced by attention, such findings predict that memory for negative versus positive stimuli should similarly be enhanced the more conservative one is. The present study tests this prediction by having participants study 120 positive, negative, and neutral scenes in preparation for a subsequent memory test. On the memory test, the same 120 scenes were presented along with 120 new scenes and participants were to respond whether a scene was old or new. Results on the memory test showed that negative scenes were more likely to be remembered than positive scenes, though, this was true only for political conservatives. That is, a larger negativity bias was found the more conservative one was. The effect was sizeable, explaining 45% of the variance across subjects in the effect of emotion. These findings demonstrate that the relationship between political ideology and asymmetries in emotion processing extend to memory and, furthermore, suggest that exploring the extent to which subject variation in interactions among emotion, attention, and memory is predicted by conservatism may provide new insights into theories of political ideology. Published by Elsevier B.V.

Being There: (Re)Making the Assessment Scene

Science.gov (United States)

Gallagher, Chris W.

2011-01-01

I use Burkean analysis to show how neoliberalism undermines faculty assessment expertise and underwrites testing industry expertise in the current assessment scene. Contending that we cannot extricate ourselves from our limited agency in this scene until we abandon the familiar "stakeholder" theory of power, I propose a rewriting of the…

[Perception of objects and scenes in age-related macular degeneration].

Science.gov (United States)

Tran, T H C; Boucart, M

2012-01-01

Vision related quality of life questionnaires suggest that patients with AMD exhibit difficulties in finding objects and in mobility. In the natural environment, objects seldom appear in isolation. They appear in a spatial context which may obscure them in part or place obstacles in the patient's path. Furthermore, the luminance of a natural scene varies as a function of the hour of the day and the light source, which can alter perception. This study aims to evaluate recognition of objects and natural scenes by patients with AMD, by using photographs of such scenes. Studies demonstrate that AMD patients are able to categorize scenes as nature scenes or urban scenes and to discriminate indoor from outdoor scenes with a high degree of precision. They detect objects better in isolation, in color, or against a white background than in their natural contexts. These patients encounter more difficulties than normally sighted individuals in detecting objects in a low-contrast, black-and-white scene. These results may have implications for rehabilitation, for layout of texts and magazines for the reading-impaired and for the rearrangement of the spatial environment of older AMD patients in order to facilitate mobility, finding objects and reducing the risk of falls. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Inferring segmented dense motion layers using 5D tensor voting.

Science.gov (United States)

Min, Changki; Medioni, Gérard

2008-09-01

We present a novel local spatiotemporal approach to produce motion segmentation and dense temporal trajectories from an image sequence. A common representation of image sequences is a 3D spatiotemporal volume, (x,y,t), and its corresponding mathematical formalism is the fiber bundle. However, directly enforcing the spatiotemporal smoothness constraint is difficult in the fiber bundle representation. Thus, we convert the representation into a new 5D space (x,y,t,vx,vy) with an additional velocity domain, where each moving object produces a separate 3D smooth layer. The smoothness constraint is now enforced by extracting 3D layers using the tensor voting framework in a single step that solves both correspondence and segmentation simultaneously. Motion segmentation is achieved by identifying those layers, and the dense temporal trajectories are obtained by converting the layers back into the fiber bundle representation. We proceed to address three applications (tracking, mosaic, and 3D reconstruction) that are hard to solve from the video stream directly because of the segmentation and dense matching steps, but become straightforward with our framework. The approach does not make restrictive assumptions about the observed scene or camera motion and is therefore generally applicable. We present results on a number of data sets.

Real-Time Adaptive Foreground/Background Segmentation

Directory of Open Access Journals (Sweden)

Sridha Sridharan

2005-08-01

Full Text Available The automatic analysis of digital video scenes often requires the segmentation of moving objects from a static background. Historically, algorithms developed for this purpose have been restricted to small frame sizes, low frame rates, or offline processing. The simplest approach involves subtracting the current frame from the known background. However, as the background is rarely known beforehand, the key is how to learn and model it. This paper proposes a new algorithm that represents each pixel in the frame by a group of clusters. The clusters are sorted in order of the likelihood that they model the background and are adapted to deal with background and lighting variations. Incoming pixels are matched against the corresponding cluster group and are classified according to whether the matching cluster is considered part of the background. The algorithm has been qualitatively and quantitatively evaluated against three other well-known techniques. It demonstrated equal or better segmentation and proved capable of processing 320×240 PAL video at full frame rate using only 35%–40% of a 1.8 GHz Pentium 4 computer.

Construction and Optimization of Three-Dimensional Disaster Scenes within Mobile Virtual Reality

Directory of Open Access Journals (Sweden)

Ya Hu

2018-06-01

Full Text Available Because mobile virtual reality (VR is both mobile and immersive, three-dimensional (3D visualizations of disaster scenes based in mobile VR enable users to perceive and recognize disaster environments faster and better than is possible with other methods. To achieve immersion and prevent users from feeling dizzy, such visualizations require a high scene-rendering frame rate. However, the existing related visualization work cannot provide a sufficient solution for this purpose. This study focuses on the construction and optimization of a 3D disaster scene in order to satisfy the high frame-rate requirements for the rendering of 3D disaster scenes in mobile VR. First, the design of a plugin-free browser/server (B/S architecture for 3D disaster scene construction and visualization based in mobile VR is presented. Second, certain key technologies for scene optimization are discussed, including diverse modes of scene data representation, representation optimization of mobile scenes, and adaptive scheduling of mobile scenes. By means of these technologies, smartphones with various performance levels can achieve higher scene-rendering frame rates and improved visual quality. Finally, using a flood disaster as an example, a plugin-free prototype system was developed, and experiments were conducted. The experimental results demonstrate that a 3D disaster scene constructed via the methods addressed in this study has a sufficiently high scene-rendering frame rate to satisfy the requirements for rendering a 3D disaster scene in mobile VR.

Fixations on objects in natural scenes: dissociating importance from salience

Directory of Open Access Journals (Sweden)

Bernard Marius e’t Hart

2013-07-01

Full Text Available The relation of selective attention to understanding of natural scenes has been subject to intense behavioral research and computational modeling, and gaze is often used as a proxy for such attention. The probability of an image region to be fixated typically correlates with its contrast. However, this relation does not imply a causal role of contrast. Rather, contrast may relate to an object’s importance for a scene, which in turn drives attention. Here we operationalize importance by the probability that an observer names the object as characteristic for a scene. We modify luminance contrast of either a frequently named (common/important or a rarely named (rare/unimportant object, track the observers’ eye movements during scene viewing and ask them to provide keywords describing the scene immediately after.When no object is modified relative to the background, important objects draw more fixations than unimportant ones. Increases of contrast make an object more likely to be fixated, irrespective of whether it was important for the original scene, while decreases in contrast have little effect on fixations. Any contrast modification makes originally unimportant objects more important for the scene. Finally, important objects are fixated more centrally than unimportant objects, irrespective of contrast.Our data suggest a dissociation between object importance (relevance for the scene and salience (relevance for attention. If an object obeys natural scene statistics, important objects are also salient. However, when natural scene statistics are violated, importance and salience are differentially affected. Object salience is modulated by the expectation about object properties (e.g., formed by context or gist, and importance by the violation of such expectations. In addition, the dependence of fixated locations within an object on the object’s importance suggests an analogy to the effects of word frequency on landing positions in reading.

A statistical model for radar images of agricultural scenes

Science.gov (United States)

Frost, V. S.; Shanmugan, K. S.; Holtzman, J. C.; Stiles, J. A.

1982-01-01

The presently derived and validated statistical model for radar images containing many different homogeneous fields predicts the probability density functions of radar images of entire agricultural scenes, thereby allowing histograms of large scenes composed of a variety of crops to be described. Seasat-A SAR images of agricultural scenes are accurately predicted by the model on the basis of three assumptions: each field has the same SNR, all target classes cover approximately the same area, and the true reflectivity characterizing each individual target class is a uniformly distributed random variable. The model is expected to be useful in the design of data processing algorithms and for scene analysis using radar images.

Efficient Algorithms for Segmentation of Item-Set Time Series

Science.gov (United States)

Chundi, Parvathi; Rosenkrantz, Daniel J.

We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.

The neural bases of spatial frequency processing during scene perception

Science.gov (United States)

Kauffmann, Louise; Ramanoël, Stephen; Peyrin, Carole

2014-01-01

Theories on visual perception agree that scenes are processed in terms of spatial frequencies. Low spatial frequencies (LSF) carry coarse information whereas high spatial frequencies (HSF) carry fine details of the scene. However, how and where spatial frequencies are processed within the brain remain unresolved questions. The present review addresses these issues and aims to identify the cerebral regions differentially involved in low and high spatial frequency processing, and to clarify their attributes during scene perception. Results from a number of behavioral and neuroimaging studies suggest that spatial frequency processing is lateralized in both hemispheres, with the right and left hemispheres predominantly involved in the categorization of LSF and HSF scenes, respectively. There is also evidence that spatial frequency processing is retinotopically mapped in the visual cortex. HSF scenes (as opposed to LSF) activate occipital areas in relation to foveal representations, while categorization of LSF scenes (as opposed to HSF) activates occipital areas in relation to more peripheral representations. Concomitantly, a number of studies have demonstrated that LSF information may reach high-order areas rapidly, allowing an initial coarse parsing of the visual scene, which could then be sent back through feedback into the occipito-temporal cortex to guide finer HSF-based analysis. Finally, the review addresses spatial frequency processing within scene-selective regions areas of the occipito-temporal cortex. PMID:24847226

Contribution to the reconstruction of scenes made of cylindrical and polyhedral objects from sequences of images obtained by a moving camera

International Nuclear Information System (INIS)

Viala, Marc

1992-01-01

Environment perception is an important process which enables a robot to perform actions in an unknown scene. Although many sensors exist to 'give sight', the camera seems to play a leading part. This thesis deals with the reconstruction of scenes made of cylindrical and polyhedral objects from sequences of images provided by a moving camera. Two methods are presented. Both are based on the evolution of apparent contours of objects in a sequence. The first approach has been developed considering that camera motion is known. Despite the good results obtained by this method, the specific conditions it requires makes its use limited. In order to avoid an accurate evaluation of camera motion, we introduce another method allowing, at the same time, to estimate the object parameters and camera positions. In this approach, only is needed a 'poor' knowledge of camera displacements supplied by the control system of the robotic platform, in which the camera is embedded. An optimal integration of a priori information, as well as the dynamic feature of the state model to estimate, lead us to use the Kalman filter. Experiments conducted with synthetic and real images proved the reliability of these methods. Camera calibration set-up is also suggested to achieve the most accurate scene models resulting from reconstruction processes. (author) [fr

Detection of chromatic and luminance distortions in natural scenes.

Science.gov (United States)

Jennings, Ben J; Wang, Karen; Menzies, Samantha; Kingdom, Frederick A A

2015-09-01

A number of studies have measured visual thresholds for detecting spatial distortions applied to images of natural scenes. In one study, Bex [J. Vis.10(2), 1 (2010)10.1167/10.2.231534-7362] measured sensitivity to sinusoidal spatial modulations of image scale. Here, we measure sensitivity to sinusoidal scale distortions applied to the chromatic, luminance, or both layers of natural scene images. We first established that sensitivity does not depend on whether the undistorted comparison image was of the same or of a different scene. Next, we found that, when the luminance but not chromatic layer was distorted, performance was the same regardless of whether the chromatic layer was present, absent, or phase-scrambled; in other words, the chromatic layer, in whatever form, did not affect sensitivity to the luminance layer distortion. However, when the chromatic layer was distorted, sensitivity was higher when the luminance layer was intact compared to when absent or phase-scrambled. These detection threshold results complement the appearance of periodic distortions of the image scale: when the luminance layer is distorted visibly, the scene appears distorted, but when the chromatic layer is distorted visibly, there is little apparent scene distortion. We conclude that (a) observers have a built-in sense of how a normal image of a natural scene should appear, and (b) the detection of distortion in, as well as the apparent distortion of, natural scene images is mediated predominantly by the luminance layer and not chromatic layer.

A contrario line segment detection

CERN Document Server

von Gioi, Rafael Grompone

2014-01-01

The reliable detection of low-level image structures is an old and still challenging problem in computer vision. This?book leads a detailed tour through the LSD algorithm, a line segment detector designed to be fully automatic. Based on the a contrario framework, the algorithm works efficiently without the need of any parameter tuning. The design criteria are thoroughly explained and the algorithm's good and bad results are illustrated on real and synthetic images. The issues involved, as well as the strategies used, are common to many geometrical structure detection problems and some possible

Semi-automatic scene generation using the Digital Anatomist Foundational Model.

Science.gov (United States)

Wong, B A; Rosse, C; Brinkley, J F

1999-01-01

A recent survey shows that a major impediment to more widespread use of computers in anatomy education is the inability to directly manipulate 3-D models, and to relate these to corresponding textual information. In the University of Washington Digital Anatomist Project we have developed a prototype Web-based scene generation program that combines the symbolic Foundational Model of Anatomy with 3-D models. A Web user can browse the Foundational Model (FM), then click to request that a 3-D scene be created of an object and its parts or branches. The scene is rendered by a graphics server, and a snapshot is sent to the Web client. The user can then manipulate the scene, adding new structures, deleting structures, rotating the scene, zooming, and saving the scene as a VRML file. Applications such as this, when fully realized with fast rendering and more anatomical content, have the potential to significantly change the way computers are used in anatomy education.

Visual search for changes in scenes creates long-term, incidental memory traces.

Science.gov (United States)

Utochkin, Igor S; Wolfe, Jeremy M

2018-05-01

Humans are very good at remembering large numbers of scenes over substantial periods of time. But how good are they at remembering changes to scenes? In this study, we tested scene memory and change detection two weeks after initial scene learning. In Experiments 1-3, scenes were learned incidentally during visual search for change. In Experiment 4, observers explicitly memorized scenes. At test, after two weeks observers were asked to discriminate old from new scenes, to recall a change that they had detected in the study phase, or to detect a newly introduced change in the memorization experiment. Next, they performed a change detection task, usually looking for the same change as in the study period. Scene recognition memory was found to be similar in all experiments, regardless of the study task. In Experiment 1, more difficult change detection produced better scene memory. Experiments 2 and 3 supported a "depth-of-processing" account for the effects of initial search and change detection on incidental memory for scenes. Of most interest, change detection was faster during the test phase than during the study phase, even when the observer had no explicit memory of having found that change previously. This result was replicated in two of our three change detection experiments. We conclude that scenes can be encoded incidentally as well as explicitly and that changes in those scenes can leave measurable traces even if they are not explicitly recalled.

Scene reassembly after multimodal digitization and pipeline evaluation using photorealistic rendering

DEFF Research Database (Denmark)

Stets, Jonathan Dyssel; Dal Corso, Alessandro; Nielsen, Jannik Boll

2017-01-01

of the lighting environment. This enables pixelwise comparison of photographs of the real scene with renderings of the digital version of the scene. Such quantitative evaluation is useful for verifying acquired material appearance and reconstructed surface geometry, which is an important aspect of digital content......Transparent objects require acquisition modalities that are very different from the ones used for objects with more diffuse reflectance properties. Digitizing a scene where objects must be acquired with different modalities requires scene reassembly after reconstruction of the object surfaces....... This reassembly of a scene that was picked apart for scanning seems unexplored. We contribute with a multimodal digitization pipeline for scenes that require this step of reassembly. Our pipeline includes measurement of bidirectional reflectance distribution functions and high dynamic range imaging...

Dynamic Frames Based Generation of 3D Scenes and Applications

Directory of Open Access Journals (Sweden)

Danijel Radošević

2015-05-01

Full Text Available Modern graphic/programming tools like Unity enables the possibility of creating 3D scenes as well as making 3D scene based program applications, including full physical model, motion, sounds, lightning effects etc. This paper deals with the usage of dynamic frames based generator in the automatic generation of 3D scene and related source code. The suggested model enables the possibility to specify features of the 3D scene in a form of textual specification, as well as exporting such features from a 3D tool. This approach enables higher level of code generation flexibility and the reusability of the main code and scene artifacts in a form of textual templates. An example of the generated application is presented and discussed.

Visual search in scenes involves selective and non-selective pathways

Science.gov (United States)

Wolfe, Jeremy M; Vo, Melissa L-H; Evans, Karla K; Greene, Michelle R

2010-01-01

How do we find objects in scenes? For decades, visual search models have been built on experiments in which observers search for targets, presented among distractor items, isolated and randomly arranged on blank backgrounds. Are these models relevant to search in continuous scenes? This paper argues that the mechanisms that govern artificial, laboratory search tasks do play a role in visual search in scenes. However, scene-based information is used to guide search in ways that had no place in earlier models. Search in scenes may be best explained by a dual-path model: A “selective” path in which candidate objects must be individually selected for recognition and a “non-selective” path in which information can be extracted from global / statistical information. PMID:21227734

Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation

Energy Technology Data Exchange (ETDEWEB)

Akhbardeh, Alireza; Jacobs, Michael A. [Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205 (United States); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205 (United States) and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205 (United States)

2012-04-15

Purpose: Visualization of anatomical structures using radiological imaging methods is an important tool in medicine to differentiate normal from pathological tissue and can generate large amounts of data for a radiologist to read. Integrating these large data sets is difficult and time-consuming. A new approach uses both supervised and unsupervised advanced machine learning techniques to visualize and segment radiological data. This study describes the application of a novel hybrid scheme, based on combining wavelet transform and nonlinear dimensionality reduction (NLDR) methods, to breast magnetic resonance imaging (MRI) data using three well-established NLDR techniques, namely, ISOMAP, local linear embedding (LLE), and diffusion maps (DfM), to perform a comparative performance analysis. Methods: Twenty-five breast lesion subjects were scanned using a 3T scanner. MRI sequences used were T1-weighted, T2-weighted, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging. The hybrid scheme consisted of two steps: preprocessing and postprocessing of the data. The preprocessing step was applied for B{sub 1} inhomogeneity correction, image registration, and wavelet-based image compression to match and denoise the data. In the postprocessing step, MRI parameters were considered data dimensions and the NLDR-based hybrid approach was applied to integrate the MRI parameters into a single image, termed the embedded image. This was achieved by mapping all pixel intensities from the higher dimension to a lower dimensional (embedded) space. For validation, the authors compared the hybrid NLDR with linear methods of principal component analysis (PCA) and multidimensional scaling (MDS) using synthetic data. For the clinical application, the authors used breast MRI data, comparison was performed using the postcontrast DCE MRI image and evaluating the congruence of the segmented lesions. Results: The NLDR-based hybrid approach was able to define and segment

Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation

International Nuclear Information System (INIS)

Akhbardeh, Alireza; Jacobs, Michael A.

2012-01-01

Purpose: Visualization of anatomical structures using radiological imaging methods is an important tool in medicine to differentiate normal from pathological tissue and can generate large amounts of data for a radiologist to read. Integrating these large data sets is difficult and time-consuming. A new approach uses both supervised and unsupervised advanced machine learning techniques to visualize and segment radiological data. This study describes the application of a novel hybrid scheme, based on combining wavelet transform and nonlinear dimensionality reduction (NLDR) methods, to breast magnetic resonance imaging (MRI) data using three well-established NLDR techniques, namely, ISOMAP, local linear embedding (LLE), and diffusion maps (DfM), to perform a comparative performance analysis. Methods: Twenty-five breast lesion subjects were scanned using a 3T scanner. MRI sequences used were T1-weighted, T2-weighted, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging. The hybrid scheme consisted of two steps: preprocessing and postprocessing of the data. The preprocessing step was applied for B 1 inhomogeneity correction, image registration, and wavelet-based image compression to match and denoise the data. In the postprocessing step, MRI parameters were considered data dimensions and the NLDR-based hybrid approach was applied to integrate the MRI parameters into a single image, termed the embedded image. This was achieved by mapping all pixel intensities from the higher dimension to a lower dimensional (embedded) space. For validation, the authors compared the hybrid NLDR with linear methods of principal component analysis (PCA) and multidimensional scaling (MDS) using synthetic data. For the clinical application, the authors used breast MRI data, comparison was performed using the postcontrast DCE MRI image and evaluating the congruence of the segmented lesions. Results: The NLDR-based hybrid approach was able to define and segment both

Image segmentation by hierarchial agglomeration of polygons using ecological statistics

Science.gov (United States)

Prasad, Lakshman; Swaminarayan, Sriram

2013-04-23

A method for rapid hierarchical image segmentation based on perceptually driven contour completion and scene statistics is disclosed. The method begins with an initial fine-scale segmentation of an image, such as obtained by perceptual completion of partial contours into polygonal regions using region-contour correspondences established by Delaunay triangulation of edge pixels as implemented in VISTA. The resulting polygons are analyzed with respect to their size and color/intensity distributions and the structural properties of their boundaries. Statistical estimates of granularity of size, similarity of color, texture, and saliency of intervening boundaries are computed and formulated into logical (Boolean) predicates. The combined satisfiability of these Boolean predicates by a pair of adjacent polygons at a given segmentation level qualifies them for merging into a larger polygon representing a coarser, larger-scale feature of the pixel image and collectively obtains the next level of polygonal segments in a hierarchy of fine-to-coarse segmentations. The iterative application of this process precipitates textured regions as polygons with highly convolved boundaries and helps distinguish them from objects which typically have more regular boundaries. The method yields a multiscale decomposition of an image into constituent features that enjoy a hierarchical relationship with features at finer and coarser scales. This provides a traversable graph structure from which feature content and context in terms of other features can be derived, aiding in automated image understanding tasks. The method disclosed is highly efficient and can be used to decompose and analyze large images.

Radiative transfer model for heterogeneous 3-D scenes

Science.gov (United States)

Kimes, D. S.; Kirchner, J. A.

1982-01-01

A general mathematical framework for simulating processes in heterogeneous 3-D scenes is presented. Specifically, a model was designed and coded for application to radiative transfers in vegetative scenes. The model is unique in that it predicts (1) the directional spectral reflectance factors as a function of the sensor's azimuth and zenith angles and the sensor's position above the canopy, (2) the spectral absorption as a function of location within the scene, and (3) the directional spectral radiance as a function of the sensor's location within the scene. The model was shown to follow known physical principles of radiative transfer. Initial verification of the model as applied to a soybean row crop showed that the simulated directional reflectance data corresponded relatively well in gross trends to the measured data. However, the model can be greatly improved by incorporating more sophisticated and realistic anisotropic scattering algorithms

Two Distinct Scene-Processing Networks Connecting Vision and Memory.

Science.gov (United States)

Baldassano, Christopher; Esteva, Andre; Fei-Fei, Li; Beck, Diane M

2016-01-01

A number of regions in the human brain are known to be involved in processing natural scenes, but the field has lacked a unifying framework for understanding how these different regions are organized and interact. We provide evidence from functional connectivity and meta-analyses for a new organizational principle, in which scene processing relies upon two distinct networks that split the classically defined parahippocampal place area (PPA). The first network of strongly connected regions consists of the occipital place area/transverse occipital sulcus and posterior PPA, which contain retinotopic maps and are not strongly coupled to the hippocampus at rest. The second network consists of the caudal inferior parietal lobule, retrosplenial complex, and anterior PPA, which connect to the hippocampus (especially anterior hippocampus), and are implicated in both visual and nonvisual tasks, including episodic memory and navigation. We propose that these two distinct networks capture the primary functional division among scene-processing regions, between those that process visual features from the current view of a scene and those that connect information from a current scene view with a much broader temporal and spatial context. This new framework for understanding the neural substrates of scene-processing bridges results from many lines of research, and makes specific functional predictions.

Hierarchy-associated semantic-rule inference framework for classifying indoor scenes

Science.gov (United States)

Yu, Dan; Liu, Peng; Ye, Zhipeng; Tang, Xianglong; Zhao, Wei

2016-03-01

Typically, the initial task of classifying indoor scenes is challenging, because the spatial layout and decoration of a scene can vary considerably. Recent efforts at classifying object relationships commonly depend on the results of scene annotation and predefined rules, making classification inflexible. Furthermore, annotation results are easily affected by external factors. Inspired by human cognition, a scene-classification framework was proposed using the empirically based annotation (EBA) and a match-over rule-based (MRB) inference system. The semantic hierarchy of images is exploited by EBA to construct rules empirically for MRB classification. The problem of scene classification is divided into low-level annotation and high-level inference from a macro perspective. Low-level annotation involves detecting the semantic hierarchy and annotating the scene with a deformable-parts model and a bag-of-visual-words model. In high-level inference, hierarchical rules are extracted to train the decision tree for classification. The categories of testing samples are generated from the parts to the whole. Compared with traditional classification strategies, the proposed semantic hierarchy and corresponding rules reduce the effect of a variable background and improve the classification performance. The proposed framework was evaluated on a popular indoor scene dataset, and the experimental results demonstrate its effectiveness.

Cognitive organization of roadway scenes : an empirical study.

NARCIS (Netherlands)

Gundy, C.M.

1995-01-01

This report describes six studies investigating the cognitive organization of roadway scenes. These scenes were represented by still photographs taken on a number of roads outside of built-up areas. Seventy-eight drivers, stratified by age and sex to simulate the Dutch driving population,

A view not to be missed: Salient scene content interferes with cognitive restoration

Science.gov (United States)

Van der Jagt, Alexander P. N.; Craig, Tony; Brewer, Mark J.; Pearson, David G.

2017-01-01

Attention Restoration Theory (ART) states that built scenes place greater load on attentional resources than natural scenes. This is explained in terms of "hard" and "soft" fascination of built and natural scenes. Given a lack of direct empirical evidence for this assumption we propose that perceptual saliency of scene content can function as an empirically derived indicator of fascination. Saliency levels were established by measuring speed of scene category detection using a Go/No-Go detection paradigm. Experiment 1 shows that built scenes are more salient than natural scenes. Experiment 2 replicates these findings using greyscale images, ruling out a colour-based response strategy, and additionally shows that built objects in natural scenes affect saliency to a greater extent than the reverse. Experiment 3 demonstrates that the saliency of scene content is directly linked to cognitive restoration using an established restoration paradigm. Overall, these findings demonstrate an important link between the saliency of scene content and related cognitive restoration. PMID:28723975

A view not to be missed: Salient scene content interferes with cognitive restoration.

Directory of Open Access Journals (Sweden)

Alexander P N Van der Jagt

Full Text Available Attention Restoration Theory (ART states that built scenes place greater load on attentional resources than natural scenes. This is explained in terms of "hard" and "soft" fascination of built and natural scenes. Given a lack of direct empirical evidence for this assumption we propose that perceptual saliency of scene content can function as an empirically derived indicator of fascination. Saliency levels were established by measuring speed of scene category detection using a Go/No-Go detection paradigm. Experiment 1 shows that built scenes are more salient than natural scenes. Experiment 2 replicates these findings using greyscale images, ruling out a colour-based response strategy, and additionally shows that built objects in natural scenes affect saliency to a greater extent than the reverse. Experiment 3 demonstrates that the saliency of scene content is directly linked to cognitive restoration using an established restoration paradigm. Overall, these findings demonstrate an important link between the saliency of scene content and related cognitive restoration.

Performance Benefits with Scene-Linked HUD Symbology: An Attentional Phenomenon?

Science.gov (United States)

Levy, Jonathan L.; Foyle, David C.; McCann, Robert S.; Null, Cynthia H. (Technical Monitor)

1999-01-01

Previous research has shown that in a simulated flight task, navigating a path defined by ground markers while maintaining a target altitude is more accurate when an altitude indicator appears in a virtual "scenelinked" format (projected symbology moving as if it were part of the out-the-window environment) compared to the fixed-location, superimposed format found on present-day HUDs (Foyle, McCann & Shelden, 1995). One explanation of the scene-linked performance advantage is that attention can be divided between scene-linked symbology and the outside world more efficiently than between standard (fixed-position) HUD symbology and the outside world. The present study tested two alternative explanations by manipulating the location of the scene-linked HUD symbology relative to the ground path markers. Scene-linked symbology yielded better ground path-following performance than standard fixed-location superimposed symbology regardless of whether the scene-linked symbology appeared directly along the ground path or at various distances off the path. The results support the explanation that the performance benefits found with scene-linked symbology are attentional.

Scene complexity: influence on perception, memory, and development in the medial temporal lobe

Directory of Open Access Journals (Sweden)

Xiaoqian J Chai

2010-03-01

Full Text Available Regions in the medial temporal lobe (MTL and prefrontal cortex (PFC are involved in memory formation for scenes in both children and adults. The development in children and adolescents of successful memory encoding for scenes has been associated with increased activation in PFC, but not MTL, regions. However, evidence suggests that a functional subregion of the MTL that supports scene perception, located in the parahippocampal gyrus (PHG, goes through a prolonged maturation process. Here we tested the hypothesis that maturation of scene perception supports the development of memory for complex scenes. Scenes were characterized by their levels of complexity defined by the number of unique object categories depicted in the scene. Recognition memory improved with age, in participants ages 8-24, for high, but not low, complexity scenes. High-complexity compared to low-complexity scenes activated a network of regions including the posterior PHG. The difference in activations for high- versus low- complexity scenes increased with age in the right posterior PHG. Finally, activations in right posterior PHG were associated with age-related increases in successful memory formation for high-, but not low-, complexity scenes. These results suggest that functional maturation of the right posterior PHG plays a critical role in the development of enduring long-term recollection for high-complexity scenes.

Crime Scene Investigation.

Science.gov (United States)

Harris, Barbara; Kohlmeier, Kris; Kiel, Robert D.

Casting students in grades 5 through 12 in the roles of reporters, lawyers, and detectives at the scene of a crime, this interdisciplinary activity involves participants in the intrigue and drama of crime investigation. Using a hands-on, step-by-step approach, students work in teams to investigate a crime and solve a mystery. Through role-playing…

SCEGRAM: An image database for semantic and syntactic inconsistencies in scenes.

Science.gov (United States)

Öhlschläger, Sabine; Võ, Melissa Le-Hoa

2017-10-01

Our visual environment is not random, but follows compositional rules according to what objects are usually found where. Despite the growing interest in how such semantic and syntactic rules - a scene grammar - enable effective attentional guidance and object perception, no common image database containing highly-controlled object-scene modifications has been publically available. Such a database is essential in minimizing the risk that low-level features drive high-level effects of interest, which is being discussed as possible source of controversial study results. To generate the first database of this kind - SCEGRAM - we took photographs of 62 real-world indoor scenes in six consistency conditions that contain semantic and syntactic (both mild and extreme) violations as well as their combinations. Importantly, always two scenes were paired, so that an object was semantically consistent in one scene (e.g., ketchup in kitchen) and inconsistent in the other (e.g., ketchup in bathroom). Low-level salience did not differ between object-scene conditions and was generally moderate. Additionally, SCEGRAM contains consistency ratings for every object-scene condition, as well as object-absent scenes and object-only images. Finally, a cross-validation using eye-movements replicated previous results of longer dwell times for both semantic and syntactic inconsistencies compared to consistent controls. In sum, the SCEGRAM image database is the first to contain well-controlled semantic and syntactic object-scene inconsistencies that can be used in a broad range of cognitive paradigms (e.g., verbal and pictorial priming, change detection, object identification, etc.) including paradigms addressing developmental aspects of scene grammar. SCEGRAM can be retrieved for research purposes from http://www.scenegrammarlab.com/research/scegram-database/ .

Changing scenes: memory for naturalistic events following change blindness.

Science.gov (United States)

Mäntylä, Timo; Sundström, Anna

2004-11-01

Research on scene perception indicates that viewers often fail to detect large changes to scene regions when these changes occur during a visual disruption such as a saccade or a movie cut. In two experiments, we examined whether this relative inability to detect changes would produce systematic biases in event memory. In Experiment 1, participants decided whether two successively presented images were the same or different, followed by a memory task, in which they recalled the content of the viewed scene. In Experiment 2, participants viewed a short video, in which an actor carried out a series of daily activities, and central scenes' attributes were changed during a movie cut. A high degree of change blindness was observed in both experiments, and these effects were related to scene complexity (Experiment 1) and level of retrieval support (Experiment 2). Most important, participants reported the changed, rather than the initial, event attributes following a failure in change detection. These findings suggest that attentional limitations during encoding contribute to biases in episodic memory.

Sensory substitution: the spatial updating of auditory scenes ‘mimics’ the spatial updating of visual scenes

Directory of Open Access Journals (Sweden)

Achille ePasqualotto

2016-04-01

Full Text Available Visual-to-auditory sensory substitution is used to convey visual information through audition, and it was initially created to compensate for blindness; it consists of software converting the visual images captured by a video-camera into the equivalent auditory images, or ‘soundscapes’. Here, it was used by blindfolded sighted participants to learn the spatial position of simple shapes depicted in images arranged on the floor. Very few studies have used sensory substitution to investigate spatial representation, while it has been widely used to investigate object recognition. Additionally, with sensory substitution we could study the performance of participants actively exploring the environment through audition, rather than passively localising sound sources. Blindfolded participants egocentrically learnt the position of six images by using sensory substitution and then a judgement of relative direction task (JRD was used to determine how this scene was represented. This task consists of imagining being in a given location, oriented in a given direction, and pointing towards the required image. Before performing the JRD task, participants explored a map that provided allocentric information about the scene. Although spatial exploration was egocentric, surprisingly we found that performance in the JRD task was better for allocentric perspectives. This suggests that the egocentric representation of the scene was updated. This result is in line with previous studies using visual and somatosensory scenes, thus supporting the notion that different sensory modalities produce equivalent spatial representation(s. Moreover, our results have practical implications to improve training methods with sensory substitution devices.

Segmentation of fluorescence microscopy cell images using unsupervised mining.

Science.gov (United States)

Du, Xian; Dua, Sumeet

2010-05-28

The accurate measurement of cell and nuclei contours are critical for the sensitive and specific detection of changes in normal cells in several medical informatics disciplines. Within microscopy, this task is facilitated using fluorescence cell stains, and segmentation is often the first step in such approaches. Due to the complex nature of cell issues and problems inherent to microscopy, unsupervised mining approaches of clustering can be incorporated in the segmentation of cells. In this study, we have developed and evaluated the performance of multiple unsupervised data mining techniques in cell image segmentation. We adapt four distinctive, yet complementary, methods for unsupervised learning, including those based on k-means clustering, EM, Otsu's threshold, and GMAC. Validation measures are defined, and the performance of the techniques is evaluated both quantitatively and qualitatively using synthetic and recently published real data. Experimental results demonstrate that k-means, Otsu's threshold, and GMAC perform similarly, and have more precise segmentation results than EM. We report that EM has higher recall values and lower precision results from under-segmentation due to its Gaussian model assumption. We also demonstrate that these methods need spatial information to segment complex real cell images with a high degree of efficacy, as expected in many medical informatics applications.

Mental Layout Extrapolations Prime Spatial Processing of Scenes

Science.gov (United States)

Gottesman, Carmela V.

2011-01-01

Four experiments examined whether scene processing is facilitated by layout representation, including layout that was not perceived but could be predicted based on a previous partial view (boundary extension). In a priming paradigm (after Sanocki, 2003), participants judged objects' distances in photographs. In Experiment 1, full scenes (target),…

Automated breast segmentation in ultrasound computer tomography SAFT images

Science.gov (United States)

Hopp, T.; You, W.; Zapf, M.; Tan, W. Y.; Gemmeke, H.; Ruiter, N. V.

2017-03-01

Ultrasound Computer Tomography (USCT) is a promising new imaging system for breast cancer diagnosis. An essential step before further processing is to remove the water background from the reconstructed images. In this paper we present a fully-automated image segmentation method based on three-dimensional active contours. The active contour method is extended by applying gradient vector flow and encoding the USCT aperture characteristics as additional weighting terms. A surface detection algorithm based on a ray model is developed to initialize the active contour, which is iteratively deformed to capture the breast outline in USCT reflection images. The evaluation with synthetic data showed that the method is able to cope with noisy images, and is not influenced by the position of the breast and the presence of scattering objects within the breast. The proposed method was applied to 14 in-vivo images resulting in an average surface deviation from a manual segmentation of 2.7 mm. We conclude that automated segmentation of USCT reflection images is feasible and produces results comparable to a manual segmentation. By applying the proposed method, reproducible segmentation results can be obtained without manual interaction by an expert.

Colour agnosia impairs the recognition of natural but not of non-natural scenes.

Science.gov (United States)

Nijboer, Tanja C W; Van Der Smagt, Maarten J; Van Zandvoort, Martine J E; De Haan, Edward H F

2007-03-01

Scene recognition can be enhanced by appropriate colour information, yet the level of visual processing at which colour exerts its effects is still unclear. It has been suggested that colour supports low-level sensory processing, while others have claimed that colour information aids semantic categorization and recognition of objects and scenes. We investigated the effect of colour on scene recognition in a case of colour agnosia, M.A.H. In a scene identification task, participants had to name images of natural or non-natural scenes in six different formats. Irrespective of scene format, M.A.H. was much slower on the natural than on the non-natural scenes. As expected, neither M.A.H. nor control participants showed any difference in performance for the non-natural scenes. However, for the natural scenes, appropriate colour facilitated scene recognition in control participants (i.e., shorter reaction times), whereas M.A.H.'s performance did not differ across formats. Our data thus support the hypothesis that the effect of colour occurs at the level of learned associations.

Graphics processing unit (GPU) real-time infrared scene generation

Science.gov (United States)

Christie, Chad L.; Gouthas, Efthimios (Themie); Williams, Owen M.

2007-04-01

VIRSuite, the GPU-based suite of software tools developed at DSTO for real-time infrared scene generation, is described. The tools include the painting of scene objects with radiometrically-associated colours, translucent object generation, polar plot validation and versatile scene generation. Special features include radiometric scaling within the GPU and the presence of zoom anti-aliasing at the core of VIRSuite. Extension of the zoom anti-aliasing construct to cover target embedding and the treatment of translucent objects is described.

Semantic guidance of eye movements in real-world scenes

OpenAIRE

Hwang, Alex D.; Wang, Hsueh-Cheng; Pomplun, Marc

2011-01-01

The perception of objects in our visual world is influenced by not only their low-level visual features such as shape and color, but also their high-level features such as meaning and semantic relations among them. While it has been shown that low-level features in real-world scenes guide eye movements during scene inspection and search, the influence of semantic similarity among scene objects on eye movements in such situations has not been investigated. Here we study guidance of eye movemen...

Picture models for 2-scene comics creating system

Directory of Open Access Journals (Sweden)

Miki UENO

2015-03-01

Full Text Available Recently, computer understanding pictures and stories becomes one of the most important research topics in computer science. However, there are few researches about human like understanding by computers because pictures have not certain format and contain more lyric aspect than that of natural laguage. For picture understanding, a comic is the suitable target because it is consisted by clear and simple plot of stories and separated scenes.In this paper, we propose 2 different types of picture models for 2-scene comics creating system. We also show the method of the application of 2-scene comics creating system by means of proposed picture model.

Matte painting in stereoscopic synthetic imagery

Science.gov (United States)

Eisenmann, Jonathan; Parent, Rick

2010-02-01

While there have been numerous studies concerning human perception in stereoscopic environments, rules of thumb for cinematography in stereoscopy have not yet been well-established. To that aim, we present experiments and results of subject testing in a stereoscopic environment, similar to that of a theater (i.e. large flat screen without head-tracking). In particular we wish to empirically identify thresholds at which different types of backgrounds, referred to in the computer animation industry as matte paintings, can be used while still maintaining the illusion of seamless perspective and depth for a particular scene and camera shot. In monoscopic synthetic imagery, any type of matte painting that maintains proper perspective lines, depth cues, and coherent lighting and textures saves in production costs while still maintaining the illusion of an alternate cinematic reality. However, in stereoscopic synthetic imagery, a 2D matte painting that worked in monoscopy may fail to provide the intended illusion of depth because the viewer has added depth information provided by stereopsis. We intend to observe two stereoscopic perceptual thresholds in this study which will provide practical guidelines indicating when to use each of three types of matte paintings. We ran subject tests in two virtual testing environments, each with varying conditions. Data were collected showing how the choices of the users matched the correct response, and the resulting perceptual threshold patterns are discussed below.

Scene Categorization in Alzheimer's Disease: A Saccadic Choice Task

Directory of Open Access Journals (Sweden)

Quentin Lenoble

2015-01-01

Full Text Available Aims: We investigated the performance in scene categorization of patients with Alzheimer's disease (AD using a saccadic choice task. Method: 24 patients with mild AD, 28 age-matched controls and 26 young people participated in the study. The participants were presented pairs of coloured photographs and were asked to make a saccadic eye movement to the picture corresponding to the target scene (natural vs. urban, indoor vs. outdoor. Results: The patients' performance did not differ from chance for natural scenes. Differences between young and older controls and patients with AD were found in accuracy but not saccadic latency. Conclusions: The results are interpreted in terms of cerebral reorganization in the prefrontal and temporo-occipital cortex of patients with AD, but also in terms of impaired processing of visual global properties of scenes.

Defining spatial relations in a specific ontology for automated scene creation

Directory of Open Access Journals (Sweden)

D. Contraş

2013-06-01

Full Text Available This paper presents the approach of building an ontology for automatic scene generation. Every scene contains various elements (backgrounds, characters, objects which are spatially interrelated. The article focuses on these spatial and temporal relationships of the elements constituting a scene.

The Wide and Unpredictable Scope of Synthetic Cannabinoids Toxicity

Directory of Open Access Journals (Sweden)

Jose Orsini

2015-01-01

Full Text Available Drug use and abuse continue to be a large public health concern worldwide. Over the past decade, novel or atypical drugs have emerged and become increasingly popular. In the recent past, compounds similar to tetrahydrocannabinoid (THC, the active ingredient of marijuana, have been synthetically produced and offered commercially as legal substances. Since the initial communications of their abuse in 2008, few case reports have been published illustrating the misuse of these substances with signs and symptoms of intoxication. Even though synthetic cannabinoids have been restricted, they are still readily available across USA and their use has been dramatically increasing, with a concomitant increment in reports to poison control centers and emergency department (ED visits. We describe a case of acute hypoxemic/hypercapnic respiratory failure as a consequence of acute congestive heart failure (CHF developed from myocardial stunning resulting from a non-ST-segment elevation myocardial infarction (MI following the consumption of synthetic cannabinoids.

A hierarchical probabilistic model for rapid object categorization in natural scenes.

Directory of Open Access Journals (Sweden)

Xiaofu He

Full Text Available Humans can categorize objects in complex natural scenes within 100-150 ms. This amazing ability of rapid categorization has motivated many computational models. Most of these models require extensive training to obtain a decision boundary in a very high dimensional (e.g., ∼6,000 in a leading model feature space and often categorize objects in natural scenes by categorizing the context that co-occurs with objects when objects do not occupy large portions of the scenes. It is thus unclear how humans achieve rapid scene categorization.To address this issue, we developed a hierarchical probabilistic model for rapid object categorization in natural scenes. In this model, a natural object category is represented by a coarse hierarchical probability distribution (PD, which includes PDs of object geometry and spatial configuration of object parts. Object parts are encoded by PDs of a set of natural object structures, each of which is a concatenation of local object features. Rapid categorization is performed as statistical inference. Since the model uses a very small number (∼100 of structures for even complex object categories such as animals and cars, it requires little training and is robust in the presence of large variations within object categories and in their occurrences in natural scenes. Remarkably, we found that the model categorized animals in natural scenes and cars in street scenes with a near human-level performance. We also found that the model located animals and cars in natural scenes, thus overcoming a flaw in many other models which is to categorize objects in natural context by categorizing contextual features. These results suggest that coarse PDs of object categories based on natural object structures and statistical operations on these PDs may underlie the human ability to rapidly categorize scenes.

Scene perception in posterior cortical atrophy: categorization, description and fixation patterns.

Science.gov (United States)

Shakespeare, Timothy J; Yong, Keir X X; Frost, Chris; Kim, Lois G; Warrington, Elizabeth K; Crutch, Sebastian J

2013-01-01

Partial or complete Balint's syndrome is a core feature of the clinico-radiological syndrome of posterior cortical atrophy (PCA), in which individuals experience a progressive deterioration of cortical vision. Although multi-object arrays are frequently used to detect simultanagnosia in the clinical assessment and diagnosis of PCA, to date there have been no group studies of scene perception in patients with the syndrome. The current study involved three linked experiments conducted in PCA patients and healthy controls. Experiment 1 evaluated the accuracy and latency of complex scene perception relative to individual faces and objects (color and grayscale) using a categorization paradigm. PCA patients were both less accurate (faces < scenes < objects) and slower (scenes < objects < faces) than controls on all categories, with performance strongly associated with their level of basic visual processing impairment; patients also showed a small advantage for color over grayscale stimuli. Experiment 2 involved free description of real world scenes. PCA patients generated fewer features and more misperceptions than controls, though perceptual errors were always consistent with the patient's global understanding of the scene (whether correct or not). Experiment 3 used eye tracking measures to compare patient and control eye movements over initial and subsequent fixations of scenes. Patients' fixation patterns were significantly different to those of young and age-matched controls, with comparable group differences for both initial and subsequent fixations. Overall, these findings describe the variability in everyday scene perception exhibited by individuals with PCA, and indicate the importance of exposure duration in the perception of complex scenes.

Scene perception in Posterior Cortical Atrophy: categorisation, description and fixation patterns

Directory of Open Access Journals (Sweden)

Timothy J Shakespeare

2013-10-01

Full Text Available Partial or complete Balint’s syndrome is a core feature of the clinico-radiological syndrome of posterior cortical atrophy (PCA, in which individuals experience a progressive deterioration of cortical vision. Although multi-object arrays are frequently used to detect simultanagnosia in the clinical assessment and diagnosis of PCA, to date there have been no group studies of scene perception in patients with the syndrome. The current study involved three linked experiments conducted in PCA patients and healthy controls. Experiment 1 evaluated the accuracy and latency of complex scene perception relative to individual faces and objects (colour and greyscale using a categorisation paradigm. PCA patients were both less accurate (faces<scenesscenesscenes. PCA patients generated fewer features and more misperceptions than controls, though perceptual errors were always consistent with the patient’s global understanding of the scene (whether correct or not. Experiment 3 used eye tracking measures to compare patient and control eye movements over initial and subsequent fixations of scenes. Patients’ fixation patterns were significantly different to those of young and age-matched controls, with comparable group differences for both initial and subsequent fixations. Overall, these findings describe the variability in everyday scene perception exhibited by individuals with PCA, and indicate the importance of exposure duration in the perception of complex scenes.

System and method for extracting dominant orientations from a scene

Science.gov (United States)

Straub, Julian; Rosman, Guy; Freifeld, Oren; Leonard, John J.; Fisher, III; , John W.

2017-05-30

In one embodiment, a method of identifying the dominant orientations of a scene comprises representing a scene as a plurality of directional vectors. The scene may comprise a three-dimensional representation of a scene, and the plurality of directional vectors may comprise a plurality of surface normals. The method further comprises determining, based on the plurality of directional vectors, a plurality of orientations describing the scene. The determined plurality of orientations explains the directionality of the plurality of directional vectors. In certain embodiments, the plurality of orientations may have independent axes of rotation. The plurality of orientations may be determined by representing the plurality of directional vectors as lying on a mathematical representation of a sphere, and inferring the parameters of a statistical model to adapt the plurality of orientations to explain the positioning of the plurality of directional vectors lying on the mathematical representation of the sphere.

AR goggles make crime scene investigation a desk job

OpenAIRE

Aron, Jacob; NORTHFIELD, Dean

2012-01-01

CRIME scene investigators could one day help solve murders without leaving the office. A pair of augmented reality glasses could allow local police to virtually tag objects in a crime scene, and build a clean record of the scene in 3D video before evidence is removed for processing.\\ud The system, being developed by Oytun Akman and colleagues at the Delft University of Technology in the Netherlands, consists of a head-mounted display receiving 3D video from a pair of attached cameras controll...

Oculomotor capture during real-world scene viewing depends on cognitive load.

Science.gov (United States)

Matsukura, Michi; Brockmole, James R; Boot, Walter R; Henderson, John M

2011-03-25

It has been claimed that gaze control during scene viewing is largely governed by stimulus-driven, bottom-up selection mechanisms. Recent research, however, has strongly suggested that observers' top-down control plays a dominant role in attentional prioritization in scenes. A notable exception to this strong top-down control is oculomotor capture, where visual transients in a scene draw the eyes. One way to test whether oculomotor capture during scene viewing is independent of an observer's top-down goal setting is to reduce observers' cognitive resource availability. In the present study, we examined whether increasing observers' cognitive load influences the frequency and speed of oculomotor capture during scene viewing. In Experiment 1, we tested whether increasing observers' cognitive load modulates the degree of oculomotor capture by a new object suddenly appeared in a scene. Similarly, in Experiment 2, we tested whether increasing observers' cognitive load modulates the degree of oculomotor capture by an object's color change. In both experiments, the degree of oculomotor capture decreased as observers' cognitive resources were reduced. These results suggest that oculomotor capture during scene viewing is dependent on observers' top-down selection mechanisms. Copyright © 2011 Elsevier Ltd. All rights reserved.

Gay and Lesbian Scene in Metelkova

Directory of Open Access Journals (Sweden)

Nataša Velikonja

2013-09-01

Full Text Available The article deals with the development of the gay and lesbian scene in ACC Metelkova, while specifying the preliminary aspects of establishing and building gay and lesbian activism associated with spatial issues. The struggle for space or occupying public space is vital for the gay and lesbian scene, as it provides not only the necessary socializing opportunities for gays and lesbians, but also does away with the historical hiding of homosexuality in the closet, in seclusion and silence. Because of their autonomy and long-term, continuous existence, homo-clubs at Metelkova contributed to the consolidation of the gay and lesbian scene in Slovenia and significantly improved the opportunities for cultural, social and political expression of gays and lesbians. Such a synthesis of the cultural, social and political, further intensified in Metelkova, and characterizes the gay and lesbian community in Slovenia from the very outset of gay and lesbian activism in 1984. It is this long-term synthesis that keeps this community in Slovenia so vital and politically resilient.

The result of surgical interventions in women with recurrent prolapse of the vagina posterior segment

Directory of Open Access Journals (Sweden)

R. M. Banakhevich

2014-06-01

Full Text Available Aim. 44 women with recurrent genital prolapse of the posterior segment of the vagina were examined and treated. Results of different types of synthetic implants were evaluated. Methods and results. 26 patients underwent transvaginal mesh with implant. In 18 patients implant Prolift posterior™ was used. The paper presents the features of the application and possible complications of the use of synthetic implants to correct the fascial defects of the posterior vaginal wall. Intraoperative bleeding after Prolift posterior™ installing were observed in 5.6 % of patients, that was lower than in the control group –7,7% (p<0,05. Extensive subcutaneous hematoma was observed in 88,7% of patients after installation of the Prolift posterior™, in the comparison group – in 15,4% of patients. Wounding anterior rectal wall was observed only in 1 (5,6% case when Prolift posterior™was installed. Conclusion. The analysis of the causes of postoperative complications and their prevention methods proposed. Recurrence after surgery with the use of synthetic materials in the operated segment was not observed.

Generation of realistic scene using illuminant estimation and mixed chromatic adaptation

Science.gov (United States)

Kim, Jae-Chul; Hong, Sang-Gi; Kim, Dong-Ho; Park, Jong-Hyun

2003-12-01

The algorithm of combining a real image with a virtual model was proposed to increase the reality of synthesized images. Currently, synthesizing a real image with a virtual model facilitated the surface reflection model and various geometric techniques. In the current methods, the characteristics of various illuminants in the real image are not sufficiently considered. In addition, despite the chromatic adaptation plays a vital role for accommodating different illuminants in the two media viewing conditions, it is not taken into account in the existing methods. Thus, it is hardly to get high-quality synthesized images. In this paper, we proposed the two-phase image synthesis algorithm. First, the surface reflectance of the maximum high-light region (MHR) was estimated using the three eigenvectors obtained from the principal component analysis (PCA) applied to the surface reflectances of 1269 Munsell samples. The combined spectral value, i.e., the product of surface reflectance and the spectral power distributions (SPDs) of an illuminant, of MHR was then estimated using the three eigenvectors obtained from PCA applied to the products of surface reflectances of Munsell 1269 samples and the SPDs of four CIE Standard Illuminants (A, C, D50, D65). By dividing the average combined spectral values of MHR by the average surface reflectances of MHR, we could estimate the illuminant of a real image. Second, the mixed chromatic adaptation (S-LMS) using an estimated and an external illuminants was applied to the virtual-model image. For evaluating the proposed algorithm, experiments with synthetic and real scenes were performed. It was shown that the proposed method was effective in synthesizing the real and the virtual scenes under various illuminants.

Cement bond evaluation method in horizontal wells using segmented bond tool

Science.gov (United States)

Song, Ruolong; He, Li

2018-06-01

Most of the existing cement evaluation technologies suffer from tool eccentralization due to gravity in highly deviated wells and horizontal wells. This paper proposes a correction method to lessen the effects of tool eccentralization on evaluation results of cement bond using segmented bond tool, which has an omnidirectional sonic transmitter and eight segmented receivers evenly arranged around the tool 2 ft from the transmitter. Using 3-D finite difference parallel numerical simulation method, we investigate the logging responses of centred and eccentred segmented bond tool in a variety of bond conditions. From the numerical results, we find that the tool eccentricity and channel azimuth can be estimated from measured sector amplitude. The average of the sector amplitude when the tool is eccentred can be corrected to the one when the tool is centred. Then the corrected amplitude will be used to calculate the channel size. The proposed method is applied to both synthetic and field data. For synthetic data, it turns out that this method can estimate the tool eccentricity with small error and the bond map is improved after correction. For field data, the tool eccentricity has a good agreement with the measured well deviation angle. Though this method still suffers from the low accuracy of calculating channel azimuth, the credibility of corrected bond map is improved especially in horizontal wells. It gives us a choice to evaluate the bond condition for horizontal wells using existing logging tool. The numerical results in this paper can provide aids for understanding measurements of segmented tool in both vertical and horizontal wells.

Integration of heterogeneous features for remote sensing scene classification

Science.gov (United States)

Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang

2018-01-01

Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.

Simulator scene display evaluation device

Science.gov (United States)

Haines, R. F. (Inventor)

1986-01-01

An apparatus for aligning and calibrating scene displays in an aircraft simulator has a base on which all of the instruments for the aligning and calibrating are mounted. Laser directs beam at double right prism which is attached to pivoting support on base. The pivot point of the prism is located at the design eye point (DEP) of simulator during the aligning and calibrating. The objective lens in the base is movable on a track to follow the laser beam at different angles within the field of vision at the DEP. An eyepiece and a precision diopter are movable into a position behind the prism during the scene evaluation. A photometer or illuminometer is pivotable about the pivot into and out of position behind the eyepiece.

Parallel programming of saccades during natural scene viewing: evidence from eye movement positions.

Science.gov (United States)

Wu, Esther X W; Gilani, Syed Omer; van Boxtel, Jeroen J A; Amihai, Ido; Chua, Fook Kee; Yen, Shih-Cheng

2013-10-24

Previous studies have shown that saccade plans during natural scene viewing can be programmed in parallel. This evidence comes mainly from temporal indicators, i.e., fixation durations and latencies. In the current study, we asked whether eye movement positions recorded during scene viewing also reflect parallel programming of saccades. As participants viewed scenes in preparation for a memory task, their inspection of the scene was suddenly disrupted by a transition to another scene. We examined whether saccades after the transition were invariably directed immediately toward the center or were contingent on saccade onset times relative to the transition. The results, which showed a dissociation in eye movement behavior between two groups of saccades after the scene transition, supported the parallel programming account. Saccades with relatively long onset times (>100 ms) after the transition were directed immediately toward the center of the scene, probably to restart scene exploration. Saccades with short onset times (programming of saccades during scene viewing. Additionally, results from the analyses of intersaccadic intervals were also consistent with the parallel programming hypothesis.

Synchronous contextual irregularities affect early scene processing: replication and extension.

Science.gov (United States)

Mudrik, Liad; Shalgi, Shani; Lamy, Dominique; Deouell, Leon Y

2014-04-01

Whether contextual regularities facilitate perceptual stages of scene processing is widely debated, and empirical evidence is still inconclusive. Specifically, it was recently suggested that contextual violations affect early processing of a scene only when the incongruent object and the scene are presented a-synchronously, creating expectations. We compared event-related potentials (ERPs) evoked by scenes that depicted a person performing an action using either a congruent or an incongruent object (e.g., a man shaving with a razor or with a fork) when scene and object were presented simultaneously. We also explored the role of attention in contextual processing by using a pre-cue to direct subjects׳ attention towards or away from the congruent/incongruent object. Subjects׳ task was to determine how many hands the person in the picture used in order to perform the action. We replicated our previous findings of frontocentral negativity for incongruent scenes that started ~ 210 ms post stimulus presentation, even earlier than previously found. Surprisingly, this incongruency ERP effect was negatively correlated with the reaction times cost on incongruent scenes. The results did not allow us to draw conclusions about the role of attention in detecting the regularity, due to a weak attention manipulation. By replicating the 200-300 ms incongruity effect with a new group of subjects at even earlier latencies than previously reported, the results strengthen the evidence for contextual processing during this time window even when simultaneous presentation of the scene and object prevent the formation of prior expectations. We discuss possible methodological limitations that may account for previous failures to find this an effect, and conclude that contextual information affects object model selection processes prior to full object identification, with semantic knowledge activation stages unfolding only later on. Copyright © 2014 Elsevier Ltd. All rights reserved.

Motivational Objects in Natural Scenes (MONS: A Database of >800 Objects

Directory of Open Access Journals (Sweden)

Judith Schomaker

2017-09-01

Full Text Available In daily life, we are surrounded by objects with pre-existing motivational associations. However, these are rarely controlled for in experiments with natural stimuli. Research on natural stimuli would therefore benefit from stimuli with well-defined motivational properties; in turn, such stimuli also open new paths in research on motivation. Here we introduce a database of Motivational Objects in Natural Scenes (MONS. The database consists of 107 scenes. Each scene contains 2 to 7 objects placed at approximately equal distance from the scene center. Each scene was photographed creating 3 versions, with one object (“critical object” being replaced to vary the overall motivational value of the scene (appetitive, aversive, and neutral, while maintaining high visual similarity between the three versions. Ratings on motivation, valence, arousal and recognizability were obtained using internet-based questionnaires. Since the main objective was to provide stimuli of well-defined motivational value, three motivation scales were used: (1 Desire to own the object; (2 Approach/Avoid; (3 Desire to interact with the object. Three sets of ratings were obtained in independent sets of observers: for all 805 objects presented on a neutral background, for 321 critical objects presented in their scene context, and for the entire scenes. On the basis of the motivational ratings, objects were subdivided into aversive, neutral, and appetitive categories. The MONS database will provide a standardized basis for future studies on motivational value under realistic conditions.

Motivational Objects in Natural Scenes (MONS): A Database of >800 Objects.

Science.gov (United States)

Schomaker, Judith; Rau, Elias M; Einhäuser, Wolfgang; Wittmann, Bianca C

2017-01-01

In daily life, we are surrounded by objects with pre-existing motivational associations. However, these are rarely controlled for in experiments with natural stimuli. Research on natural stimuli would therefore benefit from stimuli with well-defined motivational properties; in turn, such stimuli also open new paths in research on motivation. Here we introduce a database of Motivational Objects in Natural Scenes (MONS). The database consists of 107 scenes. Each scene contains 2 to 7 objects placed at approximately equal distance from the scene center. Each scene was photographed creating 3 versions, with one object ("critical object") being replaced to vary the overall motivational value of the scene (appetitive, aversive, and neutral), while maintaining high visual similarity between the three versions. Ratings on motivation, valence, arousal and recognizability were obtained using internet-based questionnaires. Since the main objective was to provide stimuli of well-defined motivational value, three motivation scales were used: (1) Desire to own the object; (2) Approach/Avoid; (3) Desire to interact with the object. Three sets of ratings were obtained in independent sets of observers: for all 805 objects presented on a neutral background, for 321 critical objects presented in their scene context, and for the entire scenes. On the basis of the motivational ratings, objects were subdivided into aversive, neutral, and appetitive categories. The MONS database will provide a standardized basis for future studies on motivational value under realistic conditions.

Fast Segmentation and Classification of Very High Resolution Remote Sensing Data Using SLIC Superpixels

Directory of Open Access Journals (Sweden)

Ovidiu Csillik

2017-03-01

Full Text Available Speed and accuracy are important factors when dealing with time-constraint events for disaster, risk, and crisis-management support. Object-based image analysis can be a time consuming task in extracting information from large images because most of the segmentation algorithms use the pixel-grid for the initial object representation. It would be more natural and efficient to work with perceptually meaningful entities that are derived from pixels using a low-level grouping process (superpixels. Firstly, we tested a new workflow for image segmentation of remote sensing data, starting the multiresolution segmentation (MRS, using ESP2 tool from the superpixel level and aiming at reducing the amount of time needed to automatically partition relatively large datasets of very high resolution remote sensing data. Secondly, we examined whether a Random Forest classification based on an oversegmentation produced by a Simple Linear Iterative Clustering (SLIC superpixel algorithm performs similarly with reference to a traditional object-based classification regarding accuracy. Tests were applied on QuickBird and WorldView-2 data with different extents, scene content complexities, and number of bands to assess how the computational time and classification accuracy are affected by these factors. The proposed segmentation approach is compared with the traditional one, starting the MRS from the pixel level, regarding geometric accuracy of the objects and the computational time. The computational time was reduced in all cases, the biggest improvement being from 5 h 35 min to 13 min, for a WorldView-2 scene with eight bands and an extent of 12.2 million pixels, while the geometric accuracy is kept similar or slightly better. SLIC superpixel-based classification had similar or better overall accuracy values when compared to MRS-based classification, but the results were obtained in a fast manner and avoiding the parameterization of the MRS. These two approaches

Segmentation of DTI based on tensorial morphological gradient

Science.gov (United States)

Rittner, Leticia; de Alencar Lotufo, Roberto

2009-02-01

This paper presents a segmentation technique for diffusion tensor imaging (DTI). This technique is based on a tensorial morphological gradient (TMG), defined as the maximum dissimilarity over the neighborhood. Once this gradient is computed, the tensorial segmentation problem becomes an scalar one, which can be solved by conventional techniques, such as watershed transform and thresholding. Similarity functions, namely the dot product, the tensorial dot product, the J-divergence and the Frobenius norm, were compared, in order to understand their differences regarding the measurement of tensor dissimilarities. The study showed that the dot product and the tensorial dot product turned out to be inappropriate for computation of the TMG, while the Frobenius norm and the J-divergence were both capable of measuring tensor dissimilarities, despite the distortion of Frobenius norm, since it is not an affine invariant measure. In order to validate the TMG as a solution for DTI segmentation, its computation was performed using distinct similarity measures and structuring elements. TMG results were also compared to fractional anisotropy. Finally, synthetic and real DTI were used in the method validation. Experiments showed that the TMG enables the segmentation of DTI by watershed transform or by a simple choice of a threshold. The strength of the proposed segmentation method is its simplicity and robustness, consequences of TMG computation. It enables the use, not only of well-known algorithms and tools from the mathematical morphology, but also of any other segmentation method to segment DTI, since TMG computation transforms tensorial images in scalar ones.

A comparison of several computational auditory scene analysis (CASA) techniques for monaural speech segregation.

Science.gov (United States)

Zeremdini, Jihen; Ben Messaoud, Mohamed Anouar; Bouzid, Aicha

2015-09-01

Humans have the ability to easily separate a composed speech and to form perceptual representations of the constituent sources in an acoustic mixture thanks to their ears. Until recently, researchers attempt to build computer models of high-level functions of the auditory system. The problem of the composed speech segregation is still a very challenging problem for these researchers. In our case, we are interested in approaches that are addressed to the monaural speech segregation. For this purpose, we study in this paper the computational auditory scene analysis (CASA) to segregate speech from monaural mixtures. CASA is the reproduction of the source organization achieved by listeners. It is based on two main stages: segmentation and grouping. In this work, we have presented, and compared several studies that have used CASA for speech separation and recognition.

Cortical Representations of Speech in a Multitalker Auditory Scene.

Science.gov (United States)

Puvvada, Krishna C; Simon, Jonathan Z

2017-09-20

The ability to parse a complex auditory scene into perceptual objects is facilitated by a hierarchical auditory system. Successive stages in the hierarchy transform an auditory scene of multiple overlapping sources, from peripheral tonotopically based representations in the auditory nerve, into perceptually distinct auditory-object-based representations in the auditory cortex. Here, using magnetoencephalography recordings from men and women, we investigate how a complex acoustic scene consisting of multiple speech sources is represented in distinct hierarchical stages of the auditory cortex. Using systems-theoretic methods of stimulus reconstruction, we show that the primary-like areas in the auditory cortex contain dominantly spectrotemporal-based representations of the entire auditory scene. Here, both attended and ignored speech streams are represented with almost equal fidelity, and a global representation of the full auditory scene with all its streams is a better candidate neural representation than that of individual streams being represented separately. We also show that higher-order auditory cortical areas, by contrast, represent the attended stream separately and with significantly higher fidelity than unattended streams. Furthermore, the unattended background streams are more faithfully represented as a single unsegregated background object rather than as separated objects. Together, these findings demonstrate the progression of the representations and processing of a complex acoustic scene up through the hierarchy of the human auditory cortex. SIGNIFICANCE STATEMENT Using magnetoencephalography recordings from human listeners in a simulated cocktail party environment, we investigate how a complex acoustic scene consisting of multiple speech sources is represented in separate hierarchical stages of the auditory cortex. We show that the primary-like areas in the auditory cortex use a dominantly spectrotemporal-based representation of the entire auditory

Improved content aware scene retargeting for retinitis pigmentosa patients

Directory of Open Access Journals (Sweden)

Al-Atabany Walid I

2010-09-01

Full Text Available Abstract Background In this paper we present a novel scene retargeting technique to reduce the visual scene while maintaining the size of the key features. The algorithm is scalable to implementation onto portable devices, and thus, has potential for augmented reality systems to provide visual support for those with tunnel vision. We therefore test the efficacy of our algorithm on shrinking the visual scene into the remaining field of view for those patients. Methods Simple spatial compression of visual scenes makes objects appear further away. We have therefore developed an algorithm which removes low importance information, maintaining the size of the significant features. Previous approaches in this field have included seam carving, which removes low importance seams from the scene, and shrinkability which dynamically shrinks the scene according to a generated importance map. The former method causes significant artifacts and the latter is inefficient. In this work we have developed a new algorithm, combining the best aspects of both these two previous methods. In particular, our approach is to generate a shrinkability importance map using as seam based approach. We then use it to dynamically shrink the scene in similar fashion to the shrinkability method. Importantly, we have implemented it so that it can be used in real time without prior knowledge of future frames. Results We have evaluated and compared our algorithm to the seam carving and image shrinkability approaches from a content preservation perspective and a compression quality perspective. Also our technique has been evaluated and tested on a trial included 20 participants with simulated tunnel vision. Results show the robustness of our method at reducing scenes up to 50% with minimal distortion. We also demonstrate efficacy in its use for those with simulated tunnel vision of 22 degrees of field of view or less. Conclusions Our approach allows us to perform content aware video

Separate and simultaneous adjustment of light qualities in a real scene

NARCIS (Netherlands)

Xia, L.; Pont, S.C.; Heynderickx, I.E.J.R.

2017-01-01

Humans are able to estimate light field properties in a scene in that they have expectations of the objects' appearance inside it. Previously, we probed such expectations in a real scene by asking whether a "probe object" fitted a real scene with regard to its lighting. But how well are observers

SEGMENTATION OF POLARIMETRIC SAR IMAGES USIG WAVELET TRANSFORMATION AND TEXTURE FEATURES

Directory of Open Access Journals (Sweden)

A. Rezaeian

2015-12-01

Full Text Available Polarimetric Synthetic Aperture Radar (PolSAR sensors can collect useful observations from earth’s surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT. Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

Segmentation of Polarimetric SAR Images Usig Wavelet Transformation and Texture Features

Science.gov (United States)

Rezaeian, A.; Homayouni, S.; Safari, A.

2015-12-01

Polarimetric Synthetic Aperture Radar (PolSAR) sensors can collect useful observations from earth's surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR) are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT). Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM) and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

Recognizing the Stranger: Recognition Scenes in the Gospel of John

DEFF Research Database (Denmark)

Larsen, Kasper Bro

Recognizing the Stranger is the first monographic study of recognition scenes and motifs in the Gospel of John. The recognition type-scene (anagnōrisis) was a common feature in ancient drama and narrative, highly valued by Aristotle as a touching moment of truth, e.g., in Oedipus’ tragic self...... structures of the type-scene in order to show how Jesus’ true identity can be recognized behind the half-mask of his human appearance....

Segmentation Based Classification of 3D Urban Point Clouds: A Super-Voxel Based Approach with Evaluation

Directory of Open Access Journals (Sweden)

Laurent Trassoudaine

2013-03-01

Full Text Available Segmentation and classification of urban range data into different object classes have several challenges due to certain properties of the data, such as density variation, inconsistencies due to missing data and the large data size that require heavy computation and large memory. A method to classify urban scenes based on a super-voxel segmentation of sparse 3D data obtained from LiDAR sensors is presented. The 3D point cloud is first segmented into voxels, which are then characterized by several attributes transforming them into super-voxels. These are joined together by using a link-chain method rather than the usual region growing algorithm to create objects. These objects are then classified using geometrical models and local descriptors. In order to evaluate the results, a new metric that combines both segmentation and classification results simultaneously is presented. The effects of voxel size and incorporation of RGB color and laser reflectance intensity on the classification results are also discussed. The method is evaluated on standard data sets using different metrics to demonstrate its efficacy.

SAR Raw Data Generation for Complex Airport Scenes

Directory of Open Access Journals (Sweden)

Jia Li

2014-10-01

Full Text Available The method of generating the SAR raw data of complex airport scenes is studied in this paper. A formulation of the SAR raw signal model of airport scenes is given. Via generating the echoes from the background, aircrafts and buildings, respectively, the SAR raw data of the unified SAR imaging geometry is obtained from their vector additions. The multipath scattering and the shadowing between the background and different ground covers of standing airplanes and buildings are analyzed. Based on the scattering characteristics, coupling scattering models and SAR raw data models of different targets are given, respectively. A procedure is given to generate the SAR raw data of airport scenes. The SAR images from the simulated raw data demonstrate the validity of the proposed method.

Multiple Active Contours Guided by Differential Evolution for Medical Image Segmentation

Science.gov (United States)

Cruz-Aceves, I.; Avina-Cervantes, J. G.; Lopez-Hernandez, J. M.; Rostro-Gonzalez, H.; Garcia-Capulin, C. H.; Torres-Cisneros, M.; Guzman-Cabrera, R.

2013-01-01

This paper presents a new image segmentation method based on multiple active contours guided by differential evolution, called MACDE. The segmentation method uses differential evolution over a polar coordinate system to increase the exploration and exploitation capabilities regarding the classical active contour model. To evaluate the performance of the proposed method, a set of synthetic images with complex objects, Gaussian noise, and deep concavities is introduced. Subsequently, MACDE is applied on datasets of sequential computed tomography and magnetic resonance images which contain the human heart and the human left ventricle, respectively. Finally, to obtain a quantitative and qualitative evaluation of the medical image segmentations compared to regions outlined by experts, a set of distance and similarity metrics has been adopted. According to the experimental results, MACDE outperforms the classical active contour model and the interactive Tseng method in terms of efficiency and robustness for obtaining the optimal control points and attains a high accuracy segmentation. PMID:23983809

Multiple Active Contours Guided by Differential Evolution for Medical Image Segmentation

Directory of Open Access Journals (Sweden)

I. Cruz-Aceves

2013-01-01

Full Text Available This paper presents a new image segmentation method based on multiple active contours guided by differential evolution, called MACDE. The segmentation method uses differential evolution over a polar coordinate system to increase the exploration and exploitation capabilities regarding the classical active contour model. To evaluate the performance of the proposed method, a set of synthetic images with complex objects, Gaussian noise, and deep concavities is introduced. Subsequently, MACDE is applied on datasets of sequential computed tomography and magnetic resonance images which contain the human heart and the human left ventricle, respectively. Finally, to obtain a quantitative and qualitative evaluation of the medical image segmentations compared to regions outlined by experts, a set of distance and similarity metrics has been adopted. According to the experimental results, MACDE outperforms the classical active contour model and the interactive Tseng method in terms of efficiency and robustness for obtaining the optimal control points and attains a high accuracy segmentation.

Effects of aging on neural connectivity underlying selective memory for emotional scenes.

Science.gov (United States)

Waring, Jill D; Addis, Donna Rose; Kensinger, Elizabeth A

2013-02-01

Older adults show age-related reductions in memory for neutral items within complex visual scenes, but just like young adults, older adults exhibit a memory advantage for emotional items within scenes compared with the background scene information. The present study examined young and older adults' encoding-stage effective connectivity for selective memory of emotional items versus memory for both the emotional item and its background. In a functional magnetic resonance imaging (fMRI) study, participants viewed scenes containing either positive or negative items within neutral backgrounds. Outside the scanner, participants completed a memory test for items and backgrounds. Irrespective of scene content being emotionally positive or negative, older adults had stronger positive connections among frontal regions and from frontal regions to medial temporal lobe structures than did young adults, especially when items and backgrounds were subsequently remembered. These results suggest there are differences between young and older adults' connectivity accompanying the encoding of emotional scenes. Older adults may require more frontal connectivity to encode all elements of a scene rather than just encoding the emotional item. Published by Elsevier Inc.

Scene text recognition in mobile applications by character descriptor and structure configuration.

Science.gov (United States)

Yi, Chucai; Tian, Yingli

2014-07-01

Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection, our previously proposed algorithms are applied to obtain text regions from scene image. First, we design a discriminative character descriptor by combining several state-of-the-art feature detectors and descriptors. Second, we model character structure at each character class by designing stroke configuration maps. Our algorithm design is compatible with the application of scene text extraction in smart mobile devices. An Android-based demo system is developed to show the effectiveness of our proposed method on scene text information extraction from nearby objects. The demo system also provides us some insight into algorithm design and performance improvement of scene text extraction. The evaluation results on benchmark data sets demonstrate that our proposed scheme of text recognition is comparable with the best existing methods.

Synthetic vision systems: operational considerations simulation experiment

Science.gov (United States)

Kramer, Lynda J.; Williams, Steven P.; Bailey, Randall E.; Glaab, Louis J.

2007-04-01

Synthetic vision is a computer-generated image of the external scene topography that is generated from aircraft attitude, high-precision navigation information, and data of the terrain, obstacles, cultural features, and other required flight information. A synthetic vision system (SVS) enhances this basic functionality with real-time integrity to ensure the validity of the databases, perform obstacle detection and independent navigation accuracy verification, and provide traffic surveillance. Over the last five years, NASA and its industry partners have developed and deployed SVS technologies for commercial, business, and general aviation aircraft which have been shown to provide significant improvements in terrain awareness and reductions in the potential for Controlled-Flight-Into-Terrain incidents / accidents compared to current generation cockpit technologies. It has been hypothesized that SVS displays can greatly improve the safety and operational flexibility of flight in Instrument Meteorological Conditions (IMC) to a level comparable to clear-day Visual Meteorological Conditions (VMC), regardless of actual weather conditions or time of day. An experiment was conducted to evaluate SVS and SVS-related technologies as well as the influence of where the information is provided to the pilot (e.g., on a Head-Up or Head-Down Display) for consideration in defining landing minima based upon aircraft and airport equipage. The "operational considerations" evaluated under this effort included reduced visibility, decision altitudes, and airport equipage requirements, such as approach lighting systems, for SVS-equipped aircraft. Subjective results from the present study suggest that synthetic vision imagery on both head-up and head-down displays may offer benefits in situation awareness; workload; and approach and landing performance in the visibility levels, approach lighting systems, and decision altitudes tested.

Synthetic Vision Systems - Operational Considerations Simulation Experiment

Science.gov (United States)

Kramer, Lynda J.; Williams, Steven P.; Bailey, Randall E.; Glaab, Louis J.

2007-01-01

Synthetic vision is a computer-generated image of the external scene topography that is generated from aircraft attitude, high-precision navigation information, and data of the terrain, obstacles, cultural features, and other required flight information. A synthetic vision system (SVS) enhances this basic functionality with real-time integrity to ensure the validity of the databases, perform obstacle detection and independent navigation accuracy verification, and provide traffic surveillance. Over the last five years, NASA and its industry partners have developed and deployed SVS technologies for commercial, business, and general aviation aircraft which have been shown to provide significant improvements in terrain awareness and reductions in the potential for Controlled-Flight-Into-Terrain incidents/accidents compared to current generation cockpit technologies. It has been hypothesized that SVS displays can greatly improve the safety and operational flexibility of flight in Instrument Meteorological Conditions (IMC) to a level comparable to clear-day Visual Meteorological Conditions (VMC), regardless of actual weather conditions or time of day. An experiment was conducted to evaluate SVS and SVS-related technologies as well as the influence of where the information is provided to the pilot (e.g., on a Head-Up or Head-Down Display) for consideration in defining landing minima based upon aircraft and airport equipage. The "operational considerations" evaluated under this effort included reduced visibility, decision altitudes, and airport equipage requirements, such as approach lighting systems, for SVS-equipped aircraft. Subjective results from the present study suggest that synthetic vision imagery on both head-up and head-down displays may offer benefits in situation awareness; workload; and approach and landing performance in the visibility levels, approach lighting systems, and decision altitudes tested.

Radio Wave Propagation Scene Partitioning for High-Speed Rails

Directory of Open Access Journals (Sweden)

Bo Ai

2012-01-01

Full Text Available Radio wave propagation scene partitioning is necessary for wireless channel modeling. As far as we know, there are no standards of scene partitioning for high-speed rail (HSR scenarios, and therefore we propose the radio wave propagation scene partitioning scheme for HSR scenarios in this paper. Based on our measurements along the Wuhan-Guangzhou HSR, Zhengzhou-Xian passenger-dedicated line, Shijiazhuang-Taiyuan passenger-dedicated line, and Beijing-Tianjin intercity line in China, whose operation speeds are above 300 km/h, and based on the investigations on Beijing South Railway Station, Zhengzhou Railway Station, Wuhan Railway Station, Changsha Railway Station, Xian North Railway Station, Shijiazhuang North Railway Station, Taiyuan Railway Station, and Tianjin Railway Station, we obtain an overview of HSR propagation channels and record many valuable measurement data for HSR scenarios. On the basis of these measurements and investigations, we partitioned the HSR scene into twelve scenarios. Further work on theoretical analysis based on radio wave propagation mechanisms, such as reflection and diffraction, may lead us to develop the standard of radio wave propagation scene partitioning for HSR. Our work can also be used as a basis for the wireless channel modeling and the selection of some key techniques for HSR systems.

Unconscious analyses of visual scenes based on feature conjunctions.

Science.gov (United States)

Tachibana, Ryosuke; Noguchi, Yasuki

2015-06-01

To efficiently process a cluttered scene, the visual system analyzes statistical properties or regularities of visual elements embedded in the scene. It is controversial, however, whether those scene analyses could also work for stimuli unconsciously perceived. Here we show that our brain performs the unconscious scene analyses not only using a single featural cue (e.g., orientation) but also based on conjunctions of multiple visual features (e.g., combinations of color and orientation information). Subjects foveally viewed a stimulus array (duration: 50 ms) where 4 types of bars (red-horizontal, red-vertical, green-horizontal, and green-vertical) were intermixed. Although a conscious perception of those bars was inhibited by a subsequent mask stimulus, the brain correctly analyzed the information about color, orientation, and color-orientation conjunctions of those invisible bars. The information of those features was then used for the unconscious configuration analysis (statistical processing) of the central bars, which induced a perceptual bias and illusory feature binding in visible stimuli at peripheral locations. While statistical analyses and feature binding are normally 2 key functions of the visual system to construct coherent percepts of visual scenes, our results show that a high-level analysis combining those 2 functions is correctly performed by unconscious computations in the brain. (c) 2015 APA, all rights reserved).

Video segmentation and camera motion characterization using compressed data

Science.gov (United States)

Milanese, Ruggero; Deguillaume, Frederic; Jacot-Descombes, Alain

1997-10-01

We address the problem of automatically extracting visual indexes from videos, in order to provide sophisticated access methods to the contents of a video server. We focus on tow tasks, namely the decomposition of a video clip into uniform segments, and the characterization of each shot by camera motion parameters. For the first task we use a Bayesian classification approach to detecting scene cuts by analyzing motion vectors. For the second task a least- squares fitting procedure determines the pan/tilt/zoom camera parameters. In order to guarantee the highest processing speed, all techniques process and analyze directly MPEG-1 motion vectors, without need for video decompression. Experimental results are reported for a database of news video clips.

Emotional Scene Content Drives the Saccade Generation System Reflexively

Science.gov (United States)

Nummenmaa, Lauri; Hyona, Jukka; Calvo, Manuel G.

2009-01-01

The authors assessed whether parafoveal perception of emotional content influences saccade programming. In Experiment 1, paired emotional and neutral scenes were presented to parafoveal vision. Participants performed voluntary saccades toward either of the scenes according to an imperative signal (color cue). Saccadic reaction times were faster…

SAMPEG: a scene-adaptive parallel MPEG-2 software encoder

NARCIS (Netherlands)

Farin, D.S.; Mache, N.; With, de P.H.N.; Girod, B.; Bouman, C.A.; Steinbach, E.G.

2001-01-01

This paper presents a fully software-based MPEG-2 encoder architecture, which uses scene-change detection to optimize the Group-of-Picture (GOP) structure for the actual video sequence. This feature enables easy, lossless edit cuts at scene-change positions and it also improves overall picture

Robust segmentation of focal lesions on multi-sequence MRI in multiple sclerosis

International Nuclear Information System (INIS)

Garcia-Lorenzo, Daniel

2010-01-01

Multiple sclerosis (MS) affects around 80.000 people in France. Magnetic resonance imaging (MRI) is an essential tool for diagnosis of MS and MRI-derived surrogate markers such as MS lesion volumes are often used as measures in MS clinical trials for the development of new treatments. The manual segmentation of these MS lesions is a time-consuming task that shows high inter- and intra-rater variability. We developed an automatic work flow for the segmentation of focal MS lesions on MRI. The segmentation method is based on the robust estimation of a parametric model of the intensities of the brain; lesions are detected as outliers to the model. We proposed two methods to include spatial information in the segmentation using mean shift and graph cut. We performed a quantitative evaluation of our work flow using synthetic and clinical images of two different centers to verify its accuracy and robustness. (author)

Review of On-Scene Management of Mass-Casualty Attacks

Directory of Open Access Journals (Sweden)

Annelie Holgersson

2016-02-01

Full Text Available Background: The scene of a mass-casualty attack (MCA entails a crime scene, a hazardous space, and a great number of people needing medical assistance. Public transportation has been the target of such attacks and involves a high probability of generating mass casualties. The review aimed to investigate challenges for on-scene responses to MCAs and suggestions made to counter these challenges, with special attention given to attacks on public transportation and associated terminals. Methods: Articles were found through PubMed and Scopus, “relevant articles” as defined by the databases, and a manual search of references. Inclusion criteria were that the article referred to attack(s and/or a public transportation-related incident and issues concerning formal on-scene response. An appraisal of the articles’ scientific quality was conducted based on an evidence hierarchy model developed for the study. Results: One hundred and five articles were reviewed. Challenges for command and coordination on scene included establishing leadership, inter-agency collaboration, multiple incident sites, and logistics. Safety issues entailed knowledge and use of personal protective equipment, risk awareness and expectations, cordons, dynamic risk assessment, defensive versus offensive approaches, and joining forces. Communication concerns were equipment shortfalls, dialoguing, and providing information. Assessment problems were scene layout and interpreting environmental indicators as well as understanding setting-driven needs for specialist skills and resources. Triage and treatment difficulties included differing triage systems, directing casualties, uncommon injuries, field hospitals, level of care, providing psychological and pediatric care. Transportation hardships included scene access, distance to hospitals, and distribution of casualties. Conclusion: Commonly encountered challenges during unintentional incidents were added to during MCAs

Clandestine laboratory scene investigation and processing using portable GC/MS

Science.gov (United States)

Matejczyk, Raymond J.

1997-02-01

This presentation describes the use of portable gas chromatography/mass spectrometry for on-scene investigation and processing of clandestine laboratories. Clandestine laboratory investigations present special problems to forensic investigators. These crime scenes contain many chemical hazards that must be detected, identified and collected as evidence. Gas chromatography/mass spectrometry performed on-scene with a rugged, portable unit is capable of analyzing a variety of matrices for drugs and chemicals used in the manufacture of illicit drugs, such as methamphetamine. Technologies used to detect various materials at a scene have particular applications but do not address the wide range of samples, chemicals, matrices and mixtures that exist in clan labs. Typical analyses performed by GC/MS are for the purpose of positively establishing the identity of starting materials, chemicals and end-product collected from clandestine laboratories. Concerns for the public and investigator safety and the environment are also important factors for rapid on-scene data generation. Here is described the implementation of a portable multiple-inlet GC/MS system designed for rapid deployment to a scene to perform forensic investigations of clandestine drug manufacturing laboratories. GC/MS has long been held as the 'gold standard' in performing forensic chemical analyses. With the capability of GC/MS to separate and produce a 'chemical fingerprint' of compounds, it is utilized as an essential technique for detecting and positively identifying chemical evidence. Rapid and conclusive on-scene analysis of evidence will assist the forensic investigators in collecting only pertinent evidence thereby reducing the amount of evidence to be transported, reducing chain of custody concerns, reducing costs and hazards, maintaining sample integrity and speeding the completion of the investigative process.

Viewing nature scenes positively affects recovery of autonomic function following acute-mental stress.

Science.gov (United States)

Brown, Daniel K; Barton, Jo L; Gladwell, Valerie F

2013-06-04

A randomized crossover study explored whether viewing different scenes prior to a stressor altered autonomic function during the recovery from the stressor. The two scenes were (a) nature (composed of trees, grass, fields) or (b) built (composed of man-made, urban scenes lacking natural characteristics) environments. Autonomic function was assessed using noninvasive techniques of heart rate variability; in particular, time domain analyses evaluated parasympathetic activity, using root-mean-square of successive differences (RMSSD). During stress, secondary cardiovascular markers (heart rate, systolic and diastolic blood pressure) showed significant increases from baseline which did not differ between the two viewing conditions. Parasympathetic activity, however, was significantly higher in recovery following the stressor in the viewing scenes of nature condition compared to viewing scenes depicting built environments (RMSSD; 50.0 ± 31.3 vs 34.8 ± 14.8 ms). Thus, viewing nature scenes prior to a stressor alters autonomic activity in the recovery period. The secondary aim was to examine autonomic function during viewing of the two scenes. Standard deviation of R-R intervals (SDRR), as change from baseline, during the first 5 min of viewing nature scenes was greater than during built scenes. Overall, this suggests that nature can elicit improvements in the recovery process following a stressor.

A NEW FRAMEWORK FOR OBJECT-BASED IMAGE ANALYSIS BASED ON SEGMENTATION SCALE SPACE AND RANDOM FOREST CLASSIFIER

Directory of Open Access Journals (Sweden)

A. Hadavand

2015-12-01

Full Text Available In this paper a new object-based framework is developed for automate scale selection in image segmentation. The quality of image objects have an important impact on further analyses. Due to the strong dependency of segmentation results to the scale parameter, choosing the best value for this parameter, for each class, becomes a main challenge in object-based image analysis. We propose a new framework which employs pixel-based land cover map to estimate the initial scale dedicated to each class. These scales are used to build segmentation scale space (SSS, a hierarchy of image objects. Optimization of SSS, respect to NDVI and DSM values in each super object is used to get the best scale in local regions of image scene. Optimized SSS segmentations are finally classified to produce the final land cover map. Very high resolution aerial image and digital surface model provided by ISPRS 2D semantic labelling dataset is used in our experiments. The result of our proposed method is comparable to those of ESP tool, a well-known method to estimate the scale of segmentation, and marginally improved the overall accuracy of classification from 79% to 80%.

Cybersickness in the presence of scene rotational movements along different axes.

Science.gov (United States)

Lo, W T; So, R H

2001-02-01

Compelling scene movements in a virtual reality (VR) system can cause symptoms of motion sickness (i.e., cybersickness). A within-subject experiment has been conducted to investigate the effects of scene oscillations along different axes on the level of cybersickness. Sixteen male participants were exposed to four 20-min VR simulation sessions. The four sessions used the same virtual environment but with scene oscillations along different axes, i.e., pitch, yaw, roll, or no oscillation (speed: 30 degrees/s, range: +/- 60 degrees). Verbal ratings of the level of nausea were taken at 5-min intervals during the sessions and sickness symptoms were also measured before and after the sessions using the Simulator Sickness Questionnaire (SSQ). In the presence of scene oscillation, both nausea ratings and SSQ scores increased at significantly higher rates than with no oscillation. While individual participants exhibited different susceptibilities to nausea associated with VR simulation containing scene oscillations along different rotational axes, the overall effects of axis among our group of 16 randomly selected participants were not significant. The main effects of, and interactions among, scene oscillation, duration, and participants are discussed in the paper.

Segmentation of high-resolution InSar data of tropical forest using Fourier parameterised deformable models

NARCIS (Netherlands)

Varekamp, C.; Hoekman, D.H.

2001-01-01

Currently, tree maps are produced from field measurements that are time consuming and expensive. Application of existing techniques based on aerial photography is often hindered by cloud cover. This has initiated research into the segmentation of high resolution airborne interferometric Synthetic

The strategic marketing planning – General Framework for Customer Segmentation

Directory of Open Access Journals (Sweden)

Alina Elena OPRESCU

2014-03-01

Full Text Available Any approach that involves the use of strategic resources of an organisation requires a responsible approach, a behaviour that enables it to properly integrate itself into the dynamic of the business environment. This articles addresses in a synthetic manner, the issues of specific integration efforts for customers’ segmentation in the strategic marketing planning. The essential activity for any organisation wishing to optimise its response to the market, the customer segmentation will fully benefit from the framework provided by the strategic marketing planning. Being a sequential process, it not only allows time optimisation of the entire marketing activity but it also leads to accuracy of the strategic planning and its stages.

Framework of passive millimeter-wave scene simulation based on material classification

Science.gov (United States)

Park, Hyuk; Kim, Sung-Hyun; Lee, Ho-Jin; Kim, Yong-Hoon; Ki, Jae-Sug; Yoon, In-Bok; Lee, Jung-Min; Park, Soon-Jun

2006-05-01

Over the past few decades, passive millimeter-wave (PMMW) sensors have emerged as useful implements in transportation and military applications such as autonomous flight-landing system, smart weapons, night- and all weather vision system. As an efficient way to predict the performance of a PMMW sensor and apply it to system, it is required to test in SoftWare-In-the-Loop (SWIL). The PMMW scene simulation is a key component for implementation of this simulator. However, there is no commercial on-the-shelf available to construct the PMMW scene simulation; only there have been a few studies on this technology. We have studied the PMMW scene simulation method to develop the PMMW sensor SWIL simulator. This paper describes the framework of the PMMW scene simulation and the tentative results. The purpose of the PMMW scene simulation is to generate sensor outputs (or image) from a visible image and environmental conditions. We organize it into four parts; material classification mapping, PMMW environmental setting, PMMW scene forming, and millimeter-wave (MMW) sensorworks. The background and the objects in the scene are classified based on properties related with MMW radiation and reflectivity. The environmental setting part calculates the following PMMW phenomenology; atmospheric propagation and emission including sky temperature, weather conditions, and physical temperature. Then, PMMW raw images are formed with surface geometry. Finally, PMMW sensor outputs are generated from PMMW raw images by applying the sensor characteristics such as an aperture size and noise level. Through the simulation process, PMMW phenomenology and sensor characteristics are simulated on the output scene. We have finished the design of framework of the simulator, and are working on implementation in detail. As a tentative result, the flight observation was simulated in specific conditions. After implementation details, we plan to increase the reliability of the simulation by data collecting

Line grouping using perceptual saliency and structure prediction for car detection in traffic scenes

Science.gov (United States)

Denasi, Sandra; Quaglia, Giorgio

1993-08-01

Autonomous and guide assisted vehicles make a heavy use of computer vision techniques to perceive the environment where they move. In this context, the European PROMETHEUS program is carrying on activities in order to develop autonomous vehicle monitoring that assists people to achieve safer driving. Car detection is one of the topics that are faced by the program. Our contribution proposes the development of this task in two stages: the localization of areas of interest and the formulation of object hypotheses. In particular, the present paper proposes a new approach that builds structural descriptions of objects from edge segmentations by using geometrical organization. This approach has been applied to the detection of cars in traffic scenes. We have analyzed images taken from a moving vehicle in order to formulate obstacle hypotheses: preliminary results confirm the efficiency of the method.

Segmentation of High Angular Resolution Diffusion MRI using Sparse Riemannian Manifold Clustering

Science.gov (United States)

Wright, Margaret J.; Thompson, Paul M.; Vidal, René

2015-01-01

We address the problem of segmenting high angular resolution diffusion imaging (HARDI) data into multiple regions (or fiber tracts) with distinct diffusion properties. We use the orientation distribution function (ODF) to represent HARDI data and cast the problem as a clustering problem in the space of ODFs. Our approach integrates tools from sparse representation theory and Riemannian geometry into a graph theoretic segmentation framework. By exploiting the Riemannian properties of the space of ODFs, we learn a sparse representation for each ODF and infer the segmentation by applying spectral clustering to a similarity matrix built from these representations. In cases where regions with similar (resp. distinct) diffusion properties belong to different (resp. same) fiber tracts, we obtain the segmentation by incorporating spatial and user-specified pairwise relationships into the formulation. Experiments on synthetic data evaluate the sensitivity of our method to image noise and the presence of complex fiber configurations, and show its superior performance compared to alternative segmentation methods. Experiments on phantom and real data demonstrate the accuracy of the proposed method in segmenting simulated fibers, as well as white matter fiber tracts of clinical importance in the human brain. PMID:24108748

Hydrological AnthropoScenes

Science.gov (United States)

Cudennec, Christophe

2016-04-01

The Anthropocene concept encapsulates the planetary-scale changes resulting from accelerating socio-ecological transformations, beyond the stratigraphic definition actually in debate. The emergence of multi-scale and proteiform complexity requires inter-discipline and system approaches. Yet, to reduce the cognitive challenge of tackling this complexity, the global Anthropocene syndrome must now be studied from various topical points of view, and grounded at regional and local levels. A system approach should allow to identify AnthropoScenes, i.e. settings where a socio-ecological transformation subsystem is clearly coherent within boundaries and displays explicit relationships with neighbouring/remote scenes and within a nesting architecture. Hydrology is a key topical point of view to be explored, as it is important in many aspects of the Anthropocene, either with water itself being a resource, hazard or transport force; or through the network, connectivity, interface, teleconnection, emergence and scaling issues it determines. We will schematically exemplify these aspects with three contrasted hydrological AnthropoScenes in Tunisia, France and Iceland; and reframe therein concepts of the hydrological change debate. Bai X., van der Leeuw S., O'Brien K., Berkhout F., Biermann F., Brondizio E., Cudennec C., Dearing J., Duraiappah A., Glaser M., Revkin A., Steffen W., Syvitski J., 2016. Plausible and desirable futures in the Anthropocene: A new research agenda. Global Environmental Change, in press, http://dx.doi.org/10.1016/j.gloenvcha.2015.09.017 Brondizio E., O'Brien K., Bai X., Biermann F., Steffen W., Berkhout F., Cudennec C., Lemos M.C., Wolfe A., Palma-Oliveira J., Chen A. C-T. Re-conceptualizing the Anthropocene: A call for collaboration. Global Environmental Change, in review. Montanari A., Young G., Savenije H., Hughes D., Wagener T., Ren L., Koutsoyiannis D., Cudennec C., Grimaldi S., Blöschl G., Sivapalan M., Beven K., Gupta H., Arheimer B., Huang Y

Hierarchical Model for the Similarity Measurement of a Complex Holed-Region Entity Scene

Directory of Open Access Journals (Sweden)

Zhanlong Chen

2017-11-01

Full Text Available Complex multi-holed-region entity scenes (i.e., sets of random region with holes are common in spatial database systems, spatial query languages, and the Geographic Information System (GIS. A multi-holed-region (region with an arbitrary number of holes is an abstraction of the real world that primarily represents geographic objects that have more than one interior boundary, such as areas that contain several lakes or lakes that contain islands. When the similarity of the two complex holed-region entity scenes is measured, the number of regions in the scenes and the number of holes in the regions are usually different between the two scenes, which complicates the matching relationships of holed-regions and holes. The aim of this research is to develop several holed-region similarity metrics and propose a hierarchical model to measure comprehensively the similarity between two complex holed-region entity scenes. The procedure first divides a complex entity scene into three layers: a complex scene, a micro-spatial-scene, and a simple entity (hole. The relationships between the adjacent layers are considered to be sets of relationships, and each level of similarity measurements is nested with the adjacent one. Next, entity matching is performed from top to bottom, while the similarity results are calculated from local to global. In addition, we utilize position graphs to describe the distribution of the holed-regions and subsequently describe the directions between the holes using a feature matrix. A case study that uses the Great Lakes in North America in 1986 and 2015 as experimental data illustrates the entire similarity measurement process between two complex holed-region entity scenes. The experimental results show that the hierarchical model accounts for the relationships of the different layers in the entire complex holed-region entity scene. The model can effectively calculate the similarity of complex holed-region entity scenes, even if the

Learning object-to-class kernels for scene classification.

Science.gov (United States)

Zhang, Lei; Zhen, Xiantong; Shao, Ling

2014-08-01

High-level image representations have drawn increasing attention in visual recognition, e.g., scene classification, since the invention of the object bank. The object bank represents an image as a response map of a large number of pretrained object detectors and has achieved superior performance for visual recognition. In this paper, based on the object bank representation, we propose the object-to-class (O2C) distances to model scene images. In particular, four variants of O2C distances are presented, and with the O2C distances, we can represent the images using the object bank by lower-dimensional but more discriminative spaces, called distance spaces, which are spanned by the O2C distances. Due to the explicit computation of O2C distances based on the object bank, the obtained representations can possess more semantic meanings. To combine the discriminant ability of the O2C distances to all scene classes, we further propose to kernalize the distance representation for the final classification. We have conducted extensive experiments on four benchmark data sets, UIUC-Sports, Scene-15, MIT Indoor, and Caltech-101, which demonstrate that the proposed approaches can significantly improve the original object bank approach and achieve the state-of-the-art performance.

The role of memory for visual search in scenes.

Science.gov (United States)

Le-Hoa Võ, Melissa; Wolfe, Jeremy M

2015-03-01

Many daily activities involve looking for something. The ease with which these searches are performed often allows one to forget that searching represents complex interactions between visual attention and memory. Although a clear understanding exists of how search efficiency will be influenced by visual features of targets and their surrounding distractors or by the number of items in the display, the role of memory in search is less well understood. Contextual cueing studies have shown that implicit memory for repeated item configurations can facilitate search in artificial displays. When searching more naturalistic environments, other forms of memory come into play. For instance, semantic memory provides useful information about which objects are typically found where within a scene, and episodic scene memory provides information about where a particular object was seen the last time a particular scene was viewed. In this paper, we will review work on these topics, with special emphasis on the role of memory in guiding search in organized, real-world scenes. © 2015 New York Academy of Sciences.

The time course of natural scene perception with reduced attention

NARCIS (Netherlands)

Groen, I.I.A.; Ghebreab, S.; Lamme, V.A.F.; Scholte, H.S.

Attention is thought to impose an informational bottleneck on vision by selecting particular information from visual scenes for enhanced processing. Behavioral evidence suggests, however, that some scene information is extracted even when attention is directed elsewhere. Here, we investigated the

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification

Directory of Open Access Journals (Sweden)

Yunlong Yu

2018-01-01

Full Text Available One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references.

Research on hyperspectral dynamic scene and image sequence simulation

Science.gov (United States)

Sun, Dandan; Liu, Fang; Gao, Jiaobo; Sun, Kefeng; Hu, Yu; Li, Yu; Xie, Junhu; Zhang, Lei

2016-10-01

This paper presents a simulation method of hyperspectral dynamic scene and image sequence for hyperspectral equipment evaluation and target detection algorithm. Because of high spectral resolution, strong band continuity, anti-interference and other advantages, in recent years, hyperspectral imaging technology has been rapidly developed and is widely used in many areas such as optoelectronic target detection, military defense and remote sensing systems. Digital imaging simulation, as a crucial part of hardware in loop simulation, can be applied to testing and evaluation hyperspectral imaging equipment with lower development cost and shorter development period. Meanwhile, visual simulation can produce a lot of original image data under various conditions for hyperspectral image feature extraction and classification algorithm. Based on radiation physic model and material characteristic parameters this paper proposes a generation method of digital scene. By building multiple sensor models under different bands and different bandwidths, hyperspectral scenes in visible, MWIR, LWIR band, with spectral resolution 0.01μm, 0.05μm and 0.1μm have been simulated in this paper. The final dynamic scenes have high real-time and realistic, with frequency up to 100 HZ. By means of saving all the scene gray data in the same viewpoint image sequence is obtained. The analysis results show whether in the infrared band or the visible band, the grayscale variations of simulated hyperspectral images are consistent with the theoretical analysis results.

Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks

Science.gov (United States)

Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Oliva, Aude

2017-01-01

Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical process. Following an early signal for lower-level visual analysis of single scenes at ~100 ms, we found a marker of real-world scene size, i.e. spatial layout processing, at ~250 ms indexing neural representations robust to changes in unrelated scene properties and viewing conditions. For a quantitative model of how scene size representations may arise in the brain, we compared MEG data to a deep neural network model trained on scene classification. Representations of scene size emerged intrinsically in the model, and resolved emerging neural scene size representation. Together our data provide a first description of an electrophysiological signal for layout processing in humans, and suggest that deep neural networks are a promising framework to investigate how spatial layout representations emerge in the human brain. PMID:27039703

Recognition and attention guidance during contextual cueing in real-world scenes: evidence from eye movements.

Science.gov (United States)

Brockmole, James R; Henderson, John M

2006-07-01

When confronted with a previously encountered scene, what information is used to guide search to a known target? We contrasted the role of a scene's basic-level category membership with its specific arrangement of visual properties. Observers were repeatedly shown photographs of scenes that contained consistently but arbitrarily located targets, allowing target positions to be associated with scene content. Learned scenes were then unexpectedly mirror reversed, spatially translating visual features as well as the target across the display while preserving the scene's identity and concept. Mirror reversals produced a cost as the eyes initially moved toward the position in the display in which the target had previously appeared. The cost was not complete, however; when initial search failed, the eyes were quickly directed to the target's new position. These results suggest that in real-world scenes, shifts of attention are initially based on scene identity, and subsequent shifts are guided by more detailed information regarding scene and object layout.

Ocfentanil overdose fatality in the recreational drug scene.

Science.gov (United States)

Coopman, Vera; Cordonnier, Jan; De Leeuw, Marc; Cirimele, Vincent

2016-09-01

This paper describes the first reported death involving ocfentanil, a potent synthetic opioid and structure analogue of fentanyl abused as a new psychoactive substance in the recreational drug scene. A 17-year-old man with a history of illegal substance abuse was found dead in his home after snorting a brown powder purchased over the internet with bitcoins. Acetaminophen, caffeine and ocfentanil were identified in the powder by gas chromatography mass spectrometry and reversed-phase liquid chromatography with diode array detector. Quantitation of ocfentanil in biological samples was performed using a target analysis based on liquid-liquid extraction and ultra performance liquid chromatography tandem mass spectrometry. In the femoral blood taken at the external body examination, the following concentrations were measured: ocfentanil 15.3μg/L, acetaminophen 45mg/L and caffeine 0.23mg/L. Tissues sampled at autopsy were analyzed to study the distribution of ocfentanil. The comprehensive systematic toxicological analysis on the post-mortem blood and tissue samples was negative for other compounds. Based on circumstantial evidence, autopsy findings and the results of the toxicological analysis, the medical examiner concluded that the cause of death was an acute intoxication with ocfentanil. The manner of death was assumed to be accidental after snorting the powder. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Review of infrared scene projector technology-1993

Science.gov (United States)

Driggers, Ronald G.; Barnard, Kenneth J.; Burroughs, E. E.; Deep, Raymond G.; Williams, Owen M.

1994-07-01

The importance of testing IR imagers and missile seekers with realistic IR scenes warrants a review of the current technologies used in dynamic infrared scene projection. These technologies include resistive arrays, deformable mirror arrays, mirror membrane devices, liquid crystal light valves, laser writers, laser diode arrays, and CRTs. Other methods include frustrated total internal reflection, thermoelectric devices, galvanic cells, Bly cells, and vanadium dioxide. A description of each technology is presented along with a discussion of their relative benefits and disadvantages. The current state of each methodology is also summarized. Finally, the methods are compared and contrasted in terms of their performance parameters.

Use of AFIS for linking scenes of crime.

Science.gov (United States)

Hefetz, Ido; Liptz, Yakir; Vaturi, Shaul; Attias, David

2016-05-01

Forensic intelligence can provide critical information in criminal investigations - the linkage of crime scenes. The Automatic Fingerprint Identification System (AFIS) is an example of a technological improvement that has advanced the entire forensic identification field to strive for new goals and achievements. In one example using AFIS, a series of burglaries into private apartments enabled a fingerprint examiner to search latent prints from different burglary scenes against an unsolved latent print database. Latent finger and palm prints coming from the same source were associated with over than 20 cases. Then, by forensic intelligence and profile analysis the offender's behavior could be anticipated. He was caught, identified, and arrested. It is recommended to perform an AFIS search of LT/UL prints against current crimes automatically as part of laboratory protocol and not by an examiner's discretion. This approach may link different crime scenes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Automatic video surveillance of outdoor scenes using track before detect

DEFF Research Database (Denmark)

Hansen, Morten; Sørensen, Helge Bjarup Dissing; Birkemark, Christian M.

2005-01-01

This paper concerns automatic video surveillance of outdoor scenes using a single camera. The first step in automatic interpretation of the video stream is activity detection based on background subtraction. Usually, this process will generate a large number of false alarms in outdoor scenes due...

A shape-optimized framework for kidney segmentation in ultrasound images using NLTV denoising and DRLSE

Directory of Open Access Journals (Sweden)

Yang Fan

2012-10-01

Full Text Available Abstract Background Computer-assisted surgical navigation aims to provide surgeons with anatomical target localization and critical structure observation, where medical image processing methods such as segmentation, registration and visualization play a critical role. Percutaneous renal intervention plays an important role in several minimally-invasive surgeries of kidney, such as Percutaneous Nephrolithotomy (PCNL and Radio-Frequency Ablation (RFA of kidney tumors, which refers to a surgical procedure where access to a target inside the kidney by a needle puncture of the skin. Thus, kidney segmentation is a key step in developing any ultrasound-based computer-aided diagnosis systems for percutaneous renal intervention. Methods In this paper, we proposed a novel framework for kidney segmentation of ultrasound (US images combined with nonlocal total variation (NLTV image denoising, distance regularized level set evolution (DRLSE and shape prior. Firstly, a denoised US image was obtained by NLTV image denoising. Secondly, DRLSE was applied in the kidney segmentation to get binary image. In this case, black and white region represented the kidney and the background respectively. The last stage is that the shape prior was applied to get a shape with the smooth boundary from the kidney shape space, which was used to optimize the segmentation result of the second step. The alignment model was used occasionally to enlarge the shape space in order to increase segmentation accuracy. Experimental results on both synthetic images and US data are given to demonstrate the effectiveness and accuracy of the proposed algorithm. Results We applied our segmentation framework on synthetic and real US images to demonstrate the better segmentation results of our method. From the qualitative results, the experiment results show that the segmentation results are much closer to the manual segmentations. The sensitivity (SN, specificity (SP and positive predictive value

Synthetic biology, inspired by synthetic chemistry.

Science.gov (United States)

Malinova, V; Nallani, M; Meier, W P; Sinner, E K

2012-07-16

The topic synthetic biology appears still as an 'empty basket to be filled'. However, there is already plenty of claims and visions, as well as convincing research strategies about the theme of synthetic biology. First of all, synthetic biology seems to be about the engineering of biology - about bottom-up and top-down approaches, compromising complexity versus stability of artificial architectures, relevant in biology. Synthetic biology accounts for heterogeneous approaches towards minimal and even artificial life, the engineering of biochemical pathways on the organismic level, the modelling of molecular processes and finally, the combination of synthetic with nature-derived materials and architectural concepts, such as a cellular membrane. Still, synthetic biology is a discipline, which embraces interdisciplinary attempts in order to have a profound, scientific base to enable the re-design of nature and to compose architectures and processes with man-made matter. We like to give an overview about the developments in the field of synthetic biology, regarding polymer-based analogs of cellular membranes and what questions can be answered by applying synthetic polymer science towards the smallest unit in life, namely a cell. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Gordon Craig's Scene Project: a history open to revision

Directory of Open Access Journals (Sweden)

Luiz Fernando

2014-09-01

Full Text Available The article proposes a review of Gordon Craig’s Scene project, an invention patented in 1910 and developed until 1922. Craig himself kept an ambiguous position whether it was an unfulfilled project or not. His son and biographer Edward Craig sustained that Craig’s original aims were never achieved because of technical limitation, and most of the scholars who examined the matter followed this position. Departing from the actual screen models saved in the Bibliothèque Nationale de France, Craig’s original notebooks, and a short film from 1963, I defend that the patented project and the essay published in 1923 mean, indeed, the materialisation of the dreamed device of the thousand scenes in one scene

A view not to be missed: Salient scene content interferes with cognitive restoration

NARCIS (Netherlands)

van der Jagt, A.P.N.; Craig, Tony; Brewer, Mark J.; Pearson, David G.

2017-01-01

Attention Restoration Theory (ART) states that built scenes place greater load on attentional resources than natural scenes. This is explained in terms of "hard" and "soft" fascination of built and natural scenes. Given a lack of direct empirical evidence for this assumption we propose that

Places in the Brain: Bridging Layout and Object Geometry in Scene-Selective Cortex.

Science.gov (United States)

Dillon, Moira R; Persichetti, Andrew S; Spelke, Elizabeth S; Dilks, Daniel D

2017-06-13

Diverse animal species primarily rely on sense (left-right) and egocentric distance (proximal-distal) when navigating the environment. Recent neuroimaging studies with human adults show that this information is represented in 2 scene-selective cortical regions-the occipital place area (OPA) and retrosplenial complex (RSC)-but not in a third scene-selective region-the parahippocampal place area (PPA). What geometric properties, then, does the PPA represent, and what is its role in scene processing? Here we hypothesize that the PPA represents relative length and angle, the geometric properties classically associated with object recognition, but only in the context of large extended surfaces that compose the layout of a scene. Using functional magnetic resonance imaging adaptation, we found that the PPA is indeed sensitive to relative length and angle changes in pictures of scenes, but not pictures of objects that reliably elicited responses to the same geometric changes in object-selective cortical regions. Moreover, we found that the OPA is also sensitive to such changes, while the RSC is tolerant to such changes. Thus, the geometric information typically associated with object recognition is also used during some aspects of scene processing. These findings provide evidence that scene-selective cortex differentially represents the geometric properties guiding navigation versus scene categorization. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Estimating cotton canopy ground cover from remotely sensed scene reflectance

International Nuclear Information System (INIS)

Maas, S.J.

1998-01-01

Many agricultural applications require spatially distributed information on growth-related crop characteristics that could be supplied through aircraft or satellite remote sensing. A study was conducted to develop and test a methodology for estimating plant canopy ground cover for cotton (Gossypium hirsutum L.) from scene reflectance. Previous studies indicated that a relatively simple relationship between ground cover and scene reflectance could be developed based on linear mixture modeling. Theoretical analysis indicated that the effects of shadows in the scene could be compensated for by averaging the results obtained using scene reflectance in the red and near-infrared wavelengths. The methodology was tested using field data collected over several years from cotton test plots in Texas and California. Results of the study appear to verify the utility of this approach. Since the methodology relies on information that can be obtained solely through remote sensing, it would be particularly useful in applications where other field information, such as plant size, row spacing, and row orientation, is unavailable

An Algorithm for Pedestrian Detection in Multispectral Image Sequences

Science.gov (United States)

Kniaz, V. V.; Fedorenko, V. V.

2017-05-01

The growing interest for self-driving cars provides a demand for scene understanding and obstacle detection algorithms. One of the most challenging problems in this field is the problem of pedestrian detection. Main difficulties arise from a diverse appearances of pedestrians. Poor visibility conditions such as fog and low light conditions also significantly decrease the quality of pedestrian detection. This paper presents a new optical flow based algorithm BipedDetet that provides robust pedestrian detection on a single-borad computer. The algorithm is based on the idea of simplified Kalman filtering suitable for realization on modern single-board computers. To detect a pedestrian a synthetic optical flow of the scene without pedestrians is generated using slanted-plane model. The estimate of a real optical flow is generated using a multispectral image sequence. The difference of the synthetic optical flow and the real optical flow provides the optical flow induced by pedestrians. The final detection of pedestrians is done by the segmentation of the difference of optical flows. To evaluate the BipedDetect algorithm a multispectral dataset was collected using a mobile robot.

Significance of perceptually relevant image decolorization for scene classification

Science.gov (United States)

Viswanathan, Sowmya; Divakaran, Govind; Soman, Kutti Padanyl

2017-11-01

Color images contain luminance and chrominance components representing the intensity and color information, respectively. The objective of this paper is to show the significance of incorporating chrominance information to the task of scene classification. An improved color-to-grayscale image conversion algorithm that effectively incorporates chrominance information is proposed using the color-to-gray structure similarity index and singular value decomposition to improve the perceptual quality of the converted grayscale images. The experimental results based on an image quality assessment for image decolorization and its success rate (using the Cadik and COLOR250 datasets) show that the proposed image decolorization technique performs better than eight existing benchmark algorithms for image decolorization. In the second part of the paper, the effectiveness of incorporating the chrominance component for scene classification tasks is demonstrated using a deep belief network-based image classification system developed using dense scale-invariant feature transforms. The amount of chrominance information incorporated into the proposed image decolorization technique is confirmed with the improvement to the overall scene classification accuracy. Moreover, the overall scene classification performance improved by combining the models obtained using the proposed method and conventional decolorization methods.

Medial Temporal Lobe Contributions to Episodic Future Thinking: Scene Construction or Future Projection?

Science.gov (United States)

Palombo, D J; Hayes, S M; Peterson, K M; Keane, M M; Verfaellie, M

2018-02-01

Previous research has shown that the medial temporal lobes (MTL) are more strongly engaged when individuals think about the future than about the present, leading to the suggestion that future projection drives MTL engagement. However, future thinking tasks often involve scene processing, leaving open the alternative possibility that scene-construction demands, rather than future projection, are responsible for the MTL differences observed in prior work. This study explores this alternative account. Using functional magnetic resonance imaging, we directly contrasted MTL activity in 1) high scene-construction and low scene-construction imagination conditions matched in future thinking demands and 2) future-oriented and present-oriented imagination conditions matched in scene-construction demands. Consistent with the alternative account, the MTL was more active for the high versus low scene-construction condition. By contrast, MTL differences were not observed when comparing the future versus present conditions. Moreover, the magnitude of MTL activation was associated with the extent to which participants imagined a scene but was not associated with the extent to which participants thought about the future. These findings help disambiguate which component processes of imagination specifically involve the MTL. Published by Oxford University Press 2016.

3D noise-resistant segmentation and tracking of unknown and occluded objects using integral imaging

Science.gov (United States)

Aloni, Doron; Jung, Jae-Hyun; Yitzhaky, Yitzhak

2017-10-01

Three dimensional (3D) object segmentation and tracking can be useful in various computer vision applications, such as: object surveillance for security uses, robot navigation, etc. We present a method for 3D multiple-object tracking using computational integral imaging, based on accurate 3D object segmentation. The method does not employ object detection by motion analysis in a video as conventionally performed (such as background subtraction or block matching). This means that the movement properties do not significantly affect the detection quality. The object detection is performed by analyzing static 3D image data obtained through computational integral imaging With regard to previous works that used integral imaging data in such a scenario, the proposed method performs the 3D tracking of objects without prior information about the objects in the scene, and it is found efficient under severe noise conditions.

Eye movements and attention in reading, scene perception, and visual search.

Science.gov (United States)

Rayner, Keith

2009-08-01

Eye movements are now widely used to investigate cognitive processes during reading, scene perception, and visual search. In this article, research on the following topics is reviewed with respect to reading: (a) the perceptual span (or span of effective vision), (b) preview benefit, (c) eye movement control, and (d) models of eye movements. Related issues with respect to eye movements during scene perception and visual search are also reviewed. It is argued that research on eye movements during reading has been somewhat advanced over research on eye movements in scene perception and visual search and that some of the paradigms developed to study reading should be more widely adopted in the study of scene perception and visual search. Research dealing with "real-world" tasks and research utilizing the visual-world paradigm are also briefly discussed.

Multiple Active Contours Driven by Particle Swarm Optimization for Cardiac Medical Image Segmentation

Science.gov (United States)

Cruz-Aceves, I.; Aviña-Cervantes, J. G.; López-Hernández, J. M.; González-Reyna, S. E.

2013-01-01

This paper presents a novel image segmentation method based on multiple active contours driven by particle swarm optimization (MACPSO). The proposed method uses particle swarm optimization over a polar coordinate system to increase the energy-minimizing capability with respect to the traditional active contour model. In the first stage, to evaluate the robustness of the proposed method, a set of synthetic images containing objects with several concavities and Gaussian noise is presented. Subsequently, MACPSO is used to segment the human heart and the human left ventricle from datasets of sequential computed tomography and magnetic resonance images, respectively. Finally, to assess the performance of the medical image segmentations with respect to regions outlined by experts and by the graph cut method objectively and quantifiably, a set of distance and similarity metrics has been adopted. The experimental results demonstrate that MACPSO outperforms the traditional active contour model in terms of segmentation accuracy and stability. PMID:23762177

Offshore Wind Potential in South India from Synthetic Aperture Radar

DEFF Research Database (Denmark)

Hasager, Charlotte Bay; Bingöl, Ferhat; Badger, Merete

are from Wide Swath Mode and each cover approximately 400 km by 400 km. The ocean wind speed maps are retrieved and processed at Risø DTU. The results show wind energy density from 200 W/m2 to 500 W/m2 at 10 m height above sea level. QuikSCAT ocean winds are included as background information on the 10......The offshore wind energy potential for pre-feasibility in South India in the area from 77° to 80° Eastern longitude and 7° to 10° Northern latitude is observed from a total of 164 ENVISAT Advanced Synthetic Aperture Radar (ASAR) satellite images during the years 2002 to 2011. All satellite scenes......-year mean and a general description of the winds and climate with monsoons in India is presented....

Offshore wind potential in South India from synthetic aperture radar

Energy Technology Data Exchange (ETDEWEB)

Hasager, C.B.; Bingoel, F.; Badger, M.; Karagali, I.; Sreevalsan, E.

2011-10-15

The offshore wind energy potential for pre-feasibility in South India in the area from 77 deg. to 80 deg. Eastern longitude and 7 deg. to 10 deg. Northern latitude is observed from a total of 164 ENVISAT Advanced Synthetic Aperture Radar (ASAR) satellite images during the years 2002 to 2011. All satellite scenes are from Wide Swath Mode and each cover approximately 400 km by 400 km. The ocean wind speed maps are retrieved and processed at Risoe DTU. The results show wind energy density from 200 W/m2 to 500 W/m2 at 10 m height above sea level. QuikSCAT ocean winds are included as background information on the 10-year mean and a general description of the winds and climate with monsoons in India is presented. (Author)

Visibility Enhancement of Scene Images Degraded by Foggy Weather Conditions with Deep Neural Networks

Directory of Open Access Journals (Sweden)

Farhan Hussain

2016-01-01

Full Text Available Nowadays many camera-based advanced driver assistance systems (ADAS have been introduced to assist the drivers and ensure their safety under various driving conditions. One of the problems faced by drivers is the faded scene visibility and lower contrast while driving in foggy conditions. In this paper, we present a novel approach to provide a solution to this problem by employing deep neural networks. We assume that the fog in an image can be mathematically modeled by an unknown complex function and we utilize the deep neural network to approximate the corresponding mathematical model for the fog. The advantages of our technique are as follows: (i its real-time operation and (ii being based on minimal input, that is, a single image, and exhibiting robustness/generalization for various unseen image data. Experiments carried out on various synthetic images indicate that our proposed technique has the abilities to approximate the corresponding fog function reasonably and remove it for better visibility and safety.

Robotic Discovery of the Auditory Scene

National Research Council Canada - National Science Library

Martinson, E; Schultz, A

2007-01-01

.... Motivated by the large negative effect of ambient noise sources on robot audition, the long-term goal is to provide awareness of the auditory scene to a robot, so that it may more effectively act...

Developmental Changes in Attention to Faces and Bodies in Static and Dynamic Scenes

Directory of Open Access Journals (Sweden)

Brenda M Stoesz

2014-03-01

Full Text Available Typically developing individuals show a strong visual preference for faces and face-like stimuli; however, this may come at the expense of attending to bodies or to other aspects of a scene. The primary goal of the present study was to provide additional insight into the development of attentional mechanisms that underlie perception of real people in naturalistic scenes. We examined the looking behaviours of typical children, adolescents, and young adults as they viewed static and dynamic scenes depicting one or more people. Overall, participants showed a bias to attend to faces more than on other parts of the scenes. Adding motion cues led to a reduction in the number, but an increase in the average duration of face fixations in single-character scenes. When multiple characters appeared in a scene, motion-related effects were attenuated and participants shifted their gaze from faces to bodies, or made off-screen glances. Children showed the largest effects related to the introduction of motion cues or additional characters, suggesting that they find dynamic faces difficult to process, and are especially prone to look away from faces when viewing complex social scenes – a strategy that could reduce the cognitive and the affective load imposed by having to divide one’s attention between multiple faces. Our findings provide new insights into the typical development of social attention during natural scene viewing, and lay the foundation for future work examining gaze behaviours in typical and atypical development.

Scene Recognition for Indoor Localization Using a Multi-Sensor Fusion Approach

Directory of Open Access Journals (Sweden)

Mengyun Liu

2017-12-01

Full Text Available After decades of research, there is still no solution for indoor localization like the GNSS (Global Navigation Satellite System solution for outdoor environments. The major reasons for this phenomenon are the complex spatial topology and RF transmission environment. To deal with these problems, an indoor scene constrained method for localization is proposed in this paper, which is inspired by the visual cognition ability of the human brain and the progress in the computer vision field regarding high-level image understanding. Furthermore, a multi-sensor fusion method is implemented on a commercial smartphone including cameras, WiFi and inertial sensors. Compared to former research, the camera on a smartphone is used to “see” which scene the user is in. With this information, a particle filter algorithm constrained by scene information is adopted to determine the final location. For indoor scene recognition, we take advantage of deep learning that has been proven to be highly effective in the computer vision community. For particle filter, both WiFi and magnetic field signals are used to update the weights of particles. Similar to other fingerprinting localization methods, there are two stages in the proposed system, offline training and online localization. In the offline stage, an indoor scene model is trained by Caffe (one of the most popular open source frameworks for deep learning and a fingerprint database is constructed by user trajectories in different scenes. To reduce the volume requirement of training data for deep learning, a fine-tuned method is adopted for model training. In the online stage, a camera in a smartphone is used to recognize the initial scene. Then a particle filter algorithm is used to fuse the sensor data and determine the final location. To prove the effectiveness of the proposed method, an Android client and a web server are implemented. The Android client is used to collect data and locate a user. The web

An L-band interferometric synthetic aperture radar study on the Ganos section of the north Anatolian fault zone between 2007 and 2011: Evidence for along strike segmentation and creep in a shallow fault patch.

Science.gov (United States)

de Michele, Marcello; Ergintav, Semih; Aochi, Hideo; Raucoules, Daniel

2017-01-01

We utilize L-band interferometric synthetic aperture radar (InSAR) data in this study to retrieve a ground velocity map for the near field of the Ganos section of the north Anatolian fault (NAF) zone. The segmentation and creep distribution of this section, which last ruptured in 1912 to generate a moment magnitude (Mw)7.3 earthquake, remains incompletely understood. Because InSAR processing removes the mean orbital plane, we do not investigate large scale displacements due to regional tectonics in this study as these can be determined using global positioning system (GPS) data, instead concentrating on the close-to-the-fault displacement field. Our aim is to determine whether, or not, it is possible to retrieve robust near field velocity maps from stacking L-band interferograms, combining both single and dual polarization SAR data. In addition, we discuss whether a crustal velocity map can be used to complement GPS observations in an attempt to discriminate the present-day surface displacement of the Ganos fault (GF) across multiple segments. Finally, we characterize the spatial distribution of creep on shallow patches along multiple along-strike segments at shallow depths. Our results suggest the presence of fault segmentation along strike as well as creep on the shallow part of the fault (i.e. the existence of a shallow creeping patch) or the presence of a smoother section on the fault plane. Data imply a heterogeneous fault plane with more complex mechanics than previously thought. Because this study improves our knowledge of the mechanisms underlying the GF, our results have implications for local seismic hazard assessment.

Adaptive attunement of selective covert attention to evolutionary-relevant emotional visual scenes.

Science.gov (United States)

Fernández-Martín, Andrés; Gutiérrez-García, Aída; Capafons, Juan; Calvo, Manuel G

2017-05-01

We investigated selective attention to emotional scenes in peripheral vision, as a function of adaptive relevance of scene affective content for male and female observers. Pairs of emotional-neutral images appeared peripherally-with perceptual stimulus differences controlled-while viewers were fixating on a different stimulus in central vision. Early selective orienting was assessed by the probability of directing the first fixation towards either scene, and the time until first fixation. Emotional scenes selectively captured covert attention even when they were task-irrelevant, thus revealing involuntary, automatic processing. Sex of observers and specific emotional scene content (e.g., male-to-female-aggression, families and babies, etc.) interactively modulated covert attention, depending on adaptive priorities and goals for each sex, both for pleasant and unpleasant content. The attentional system exhibits domain-specific and sex-specific biases and attunements, probably rooted in evolutionary pressures to enhance reproductive and protective success. Emotional cues selectively capture covert attention based on their bio-social significance. Copyright © 2017 Elsevier Inc. All rights reserved.

Angular difference feature extraction for urban scene classification using ZY-3 multi-angle high-resolution satellite imagery

Science.gov (United States)

Huang, Xin; Chen, Huijun; Gong, Jianya

2018-01-01

Spaceborne multi-angle images with a high-resolution are capable of simultaneously providing spatial details and three-dimensional (3D) information to support detailed and accurate classification of complex urban scenes. In recent years, satellite-derived digital surface models (DSMs) have been increasingly utilized to provide height information to complement spectral properties for urban classification. However, in such a way, the multi-angle information is not effectively exploited, which is mainly due to the errors and difficulties of the multi-view image matching and the inaccuracy of the generated DSM over complex and dense urban scenes. Therefore, it is still a challenging task to effectively exploit the available angular information from high-resolution multi-angle images. In this paper, we investigate the potential for classifying urban scenes based on local angular properties characterized from high-resolution ZY-3 multi-view images. Specifically, three categories of angular difference features (ADFs) are proposed to describe the angular information at three levels (i.e., pixel, feature, and label levels): (1) ADF-pixel: the angular information is directly extrapolated by pixel comparison between the multi-angle images; (2) ADF-feature: the angular differences are described in the feature domains by comparing the differences between the multi-angle spatial features (e.g., morphological attribute profiles (APs)). (3) ADF-label: label-level angular features are proposed based on a group of urban primitives (e.g., buildings and shadows), in order to describe the specific angular information related to the types of primitive classes. In addition, we utilize spatial-contextual information to refine the multi-level ADF features using superpixel segmentation, for the purpose of alleviating the effects of salt-and-pepper noise and representing the main angular characteristics within a local area. The experiments on ZY-3 multi-angle images confirm that the proposed

Object-based implicit learning in visual search: perceptual segmentation constrains contextual cueing.

Science.gov (United States)

Conci, Markus; Müller, Hermann J; von Mühlenen, Adrian

2013-07-09

In visual search, detection of a target is faster when it is presented within a spatial layout of repeatedly encountered nontarget items, indicating that contextual invariances can guide selective attention (contextual cueing; Chun & Jiang, 1998). However, perceptual regularities may interfere with contextual learning; for instance, no contextual facilitation occurs when four nontargets form a square-shaped grouping, even though the square location predicts the target location (Conci & von Mühlenen, 2009). Here, we further investigated potential causes for this interference-effect: We show that contextual cueing can reliably occur for targets located within the region of a segmented object, but not for targets presented outside of the object's boundaries. Four experiments demonstrate an object-based facilitation in contextual cueing, with a modulation of context-based learning by relatively subtle grouping cues including closure, symmetry, and spatial regularity. Moreover, the lack of contextual cueing for targets located outside the segmented region was due to an absence of (latent) learning of contextual layouts, rather than due to an attentional bias towards the grouped region. Taken together, these results indicate that perceptual segmentation provides a basic structure within which contextual scene regularities are acquired. This in turn argues that contextual learning is constrained by object-based selection.

Adaptive attunement of selective covert attention to evolutionary-relevant emotional visual scenes

OpenAIRE

Fernández-Martín, Andrés (UNIR); Gutiérrez-García, Aida; Capafons, Juan; Calvo, Manuel G

2017-01-01

We investigated selective attention to emotional scenes in peripheral vision, as a function of adaptive relevance of scene affective content for male and female observers. Pairs of emotional neutral images appeared peripherally with perceptual stimulus differences controlled while viewers were fixating on a different stimulus in central vision. Early selective orienting was assessed by the probability of directing the first fixation towards either scene, and the time until first fixation. Emo...

Knowledge Guided Disambiguation for Large-Scale Scene Classification With Multi-Resolution CNNs

Science.gov (United States)

Wang, Limin; Guo, Sheng; Huang, Weilin; Xiong, Yuanjun; Qiao, Yu

2017-04-01

Convolutional Neural Networks (CNNs) have made remarkable progress on scene recognition, partially due to these recent large-scale scene datasets, such as the Places and Places2. Scene categories are often defined by multi-level information, including local objects, global layout, and background environment, thus leading to large intra-class variations. In addition, with the increasing number of scene categories, label ambiguity has become another crucial issue in large-scale classification. This paper focuses on large-scale scene recognition and makes two major contributions to tackle these issues. First, we propose a multi-resolution CNN architecture that captures visual content and structure at multiple levels. The multi-resolution CNNs are composed of coarse resolution CNNs and fine resolution CNNs, which are complementary to each other. Second, we design two knowledge guided disambiguation techniques to deal with the problem of label ambiguity. (i) We exploit the knowledge from the confusion matrix computed on validation data to merge ambiguous classes into a super category. (ii) We utilize the knowledge of extra networks to produce a soft label for each image. Then the super categories or soft labels are employed to guide CNN training on the Places2. We conduct extensive experiments on three large-scale image datasets (ImageNet, Places, and Places2), demonstrating the effectiveness of our approach. Furthermore, our method takes part in two major scene recognition challenges, and achieves the second place at the Places2 challenge in ILSVRC 2015, and the first place at the LSUN challenge in CVPR 2016. Finally, we directly test the learned representations on other scene benchmarks, and obtain the new state-of-the-art results on the MIT Indoor67 (86.7\\%) and SUN397 (72.0\\%). We release the code and models at~\\url{https://github.com/wanglimin/MRCNN-Scene-Recognition}.

Affective video retrieval: violence detection in Hollywood movies by large-scale segmental feature extraction.

Science.gov (United States)

Eyben, Florian; Weninger, Felix; Lehment, Nicolas; Schuller, Björn; Rigoll, Gerhard

2013-01-01

Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology "out of the lab" to real-world, diverse data. In this contribution, we address the problem of finding "disturbing" scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP) on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to .398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis.

Affective video retrieval: violence detection in Hollywood movies by large-scale segmental feature extraction.

Directory of Open Access Journals (Sweden)

Florian Eyben

Full Text Available Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology "out of the lab" to real-world, diverse data. In this contribution, we address the problem of finding "disturbing" scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to .398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis.

Representations and Techniques for 3D Object Recognition and Scene Interpretation

CERN Document Server

Hoiem, Derek

2011-01-01

One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physi

Automating the construction of scene classifiers for content-based video retrieval

NARCIS (Netherlands)

Khan, L.; Israël, Menno; Petrushin, V.A.; van den Broek, Egon; van der Putten, Peter

2004-01-01

This paper introduces a real time automatic scene classifier within content-based video retrieval. In our envisioned approach end users like documentalists, not image processing experts, build classifiers interactively, by simply indicating positive examples of a scene. Classification consists of a

Number of perceptually distinct surface colors in natural scenes.

Science.gov (United States)

Marín-Franch, Iván; Foster, David H

2010-09-30

The ability to perceptually identify distinct surfaces in natural scenes by virtue of their color depends not only on the relative frequency of surface colors but also on the probabilistic nature of observer judgments. Previous methods of estimating the number of discriminable surface colors, whether based on theoretical color gamuts or recorded from real scenes, have taken a deterministic approach. Thus, a three-dimensional representation of the gamut of colors is divided into elementary cells or points which are spaced at one discrimination-threshold unit intervals and which are then counted. In this study, information-theoretic methods were used to take into account both differing surface-color frequencies and observer response uncertainty. Spectral radiances were calculated from 50 hyperspectral images of natural scenes and were represented in a perceptually almost uniform color space. The average number of perceptually distinct surface colors was estimated as 7.3 × 10(3), much smaller than that based on counting methods. This number is also much smaller than the number of distinct points in a scene that are, in principle, available for reliable identification under illuminant changes, suggesting that color constancy, or the lack of it, does not generally determine the limit on the use of color for surface identification.

A hierarchical stress release model for synthetic seismicity

Science.gov (United States)

Bebbington, Mark

1997-06-01

We construct a stochastic dynamic model for synthetic seismicity involving stochastic stress input, release, and transfer in an environment of heterogeneous strength and interacting segments. The model is not fault-specific, having a number of adjustable parameters with physical interpretation, namely, stress relaxation, stress transfer, stress dissipation, segment structure, strength, and strength heterogeneity, which affect the seismicity in various ways. Local parameters are chosen to be consistent with large historical events, other parameters to reproduce bulk seismicity statistics for the fault as a whole. The one-dimensional fault is divided into a number of segments, each comprising a varying number of nodes. Stress input occurs at each node in a simple random process, representing the slow buildup due to tectonic plate movements. Events are initiated, subject to a stochastic hazard function, when the stress on a node exceeds the local strength. An event begins with the transfer of excess stress to neighboring nodes, which may in turn transfer their excess stress to the next neighbor. If the event grows to include the entire segment, then most of the stress on the segment is transferred to neighboring segments (or dissipated) in a characteristic event. These large events may themselves spread to other segments. We use the Middle America Trench to demonstrate that this model, using simple stochastic stress input and triggering mechanisms, can produce behavior consistent with the historical record over five units of magnitude. We also investigate the effects of perturbing various parameters in order to show how the model might be tailored to a specific fault structure. The strength of the model lies in this ability to reproduce the behavior of a general linear fault system through the choice of a relatively small number of parameters. It remains to develop a procedure for estimating the internal state of the model from the historical observations in order to

Narrative Collage of Image Collections by Scene Graph Recombination.

Science.gov (United States)

Fang, Fei; Yi, Miao; Feng, Hui; Hu, Shenghong; Xiao, Chunxia

2017-10-04

Narrative collage is an interesting image editing art to summarize the main theme or storyline behind an image collection. We present a novel method to generate narrative images with plausible semantic scene structures. To achieve this goal, we introduce a layer graph and a scene graph to represent relative depth order and semantic relationship between image objects, respectively. We firstly cluster the input image collection to select representative images, and then extract a group of semantic salient objects from each representative image. Both Layer graphs and scene graphs are constructed and combined according to our specific rules for reorganizing the extracted objects in every image. We design an energy model to appropriately locate every object on the final canvas. Experiment results show that our method can produce competitive narrative collage result and works well on a wide range of image collections.

Virtual environments for scene of crime reconstruction and analysis

Science.gov (United States)

Howard, Toby L. J.; Murta, Alan D.; Gibson, Simon

2000-02-01

This paper describes research conducted in collaboration with Greater Manchester Police (UK), to evalute the utility of Virtual Environments for scene of crime analysis, forensic investigation, and law enforcement briefing and training. We present an illustrated case study of the construction of a high-fidelity virtual environment, intended to match a particular real-life crime scene as closely as possible. We describe and evaluate the combination of several approaches including: the use of the Manchester Scene Description Language for constructing complex geometrical models; the application of a radiosity rendering algorithm with several novel features based on human perceptual consideration; texture extraction from forensic photography; and experiments with interactive walkthroughs and large-screen stereoscopic display of the virtual environment implemented using the MAVERIK system. We also discuss the potential applications of Virtual Environment techniques in the Law Enforcement and Forensic communities.

STREAM PROCESSING ALGORITHMS FOR DYNAMIC 3D SCENE ANALYSIS

Science.gov (United States)

2018-02-15

PROCESSING ALGORITHMS FOR DYNAMIC 3D SCENE ANALYSIS 5a. CONTRACT NUMBER FA8750-14-2-0072 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER 62788F 6...of Figures 1 The 3D processing pipeline flowchart showing key modules. . . . . . . . . . . . . . . . . 12 2 Overall view (data flow) of the proposed...pipeline flowchart showing key modules. from motion and bundle adjustment algorithm. By fusion of depth masks of the scene obtained from 3D

Children's Development of Analogical Reasoning: Insights from Scene Analogy Problems

Science.gov (United States)

Richland, Lindsey E.; Morrison, Robert G.; Holyoak, Keith J.

2006-01-01

We explored how relational complexity and featural distraction, as varied in scene analogy problems, affect children's analogical reasoning performance. Results with 3- and 4-year-olds, 6- and 7-year-olds, 9- to 11-year-olds, and 13- and 14-year-olds indicate that when children can identify the critical structural relations in a scene analogy…

The Influence of Color on the Perception of Scene Gist

Science.gov (United States)

Castelhano, Monica S.; Henderson, John M.

2008-01-01

In 3 experiments the authors used a new contextual bias paradigm to explore how quickly information is extracted from a scene to activate gist, whether color contributes to this activation, and how color contributes, if it does. Participants were shown a brief presentation of a scene followed by the name of a target object. The target object could…

Emotional event-related potentials are larger to figures than scenes but are similarly reduced by inattention

Directory of Open Access Journals (Sweden)

Nordström Henrik

2012-05-01

Full Text Available Abstract Background In research on event-related potentials (ERP to emotional pictures, greater attention to emotional than neutral stimuli (i.e., motivated attention is commonly indexed by two difference waves between emotional and neutral stimuli: the early posterior negativity (EPN and the late positive potential (LPP. Evidence suggests that if attention is directed away from the pictures, then the emotional effects on EPN and LPP are eliminated. However, a few studies have found residual, emotional effects on EPN and LPP. In these studies, pictures were shown at fixation, and picture composition was that of simple figures rather than that of complex scenes. Because figures elicit larger LPP than do scenes, figures might capture and hold attention more strongly than do scenes. Here, we showed negative and neutral pictures of figures and scenes and tested first, whether emotional effects are larger to figures than scenes for both EPN and LPP, and second, whether emotional effects on EPN and LPP are reduced less for unattended figures than scenes. Results Emotional effects on EPN and LPP were larger for figures than scenes. When pictures were unattended, emotional effects on EPN increased for scenes but tended to decrease for figures, whereas emotional effects on LPP decreased similarly for figures and scenes. Conclusions Emotional effects on EPN and LPP were larger for figures than scenes, but these effects did not resist manipulations of attention more strongly for figures than scenes. These findings imply that the emotional content captures attention more strongly for figures than scenes, but that the emotional content does not hold attention more strongly for figures than scenes.

Emotional event-related potentials are larger to figures than scenes but are similarly reduced by inattention

Science.gov (United States)

2012-01-01

Background In research on event-related potentials (ERP) to emotional pictures, greater attention to emotional than neutral stimuli (i.e., motivated attention) is commonly indexed by two difference waves between emotional and neutral stimuli: the early posterior negativity (EPN) and the late positive potential (LPP). Evidence suggests that if attention is directed away from the pictures, then the emotional effects on EPN and LPP are eliminated. However, a few studies have found residual, emotional effects on EPN and LPP. In these studies, pictures were shown at fixation, and picture composition was that of simple figures rather than that of complex scenes. Because figures elicit larger LPP than do scenes, figures might capture and hold attention more strongly than do scenes. Here, we showed negative and neutral pictures of figures and scenes and tested first, whether emotional effects are larger to figures than scenes for both EPN and LPP, and second, whether emotional effects on EPN and LPP are reduced less for unattended figures than scenes. Results Emotional effects on EPN and LPP were larger for figures than scenes. When pictures were unattended, emotional effects on EPN increased for scenes but tended to decrease for figures, whereas emotional effects on LPP decreased similarly for figures and scenes. Conclusions Emotional effects on EPN and LPP were larger for figures than scenes, but these effects did not resist manipulations of attention more strongly for figures than scenes. These findings imply that the emotional content captures attention more strongly for figures than scenes, but that the emotional content does not hold attention more strongly for figures than scenes. PMID:22607397

Short report: the effect of expertise in hiking on recognition memory for mountain scenes.

Science.gov (United States)

Kawamura, Satoru; Suzuki, Sae; Morikawa, Kazunori

2007-10-01

The nature of an expert memory advantage that does not depend on stimulus structure or chunking was examined, using more ecologically valid stimuli in the context of a more natural activity than previously studied domains. Do expert hikers and novice hikers see and remember mountain scenes differently? In the present experiment, 18 novice hikers and 17 expert hikers were presented with 60 photographs of scenes from hiking trails. These scenes differed in the degree of functional aspects that implied some action possibilities or dangers. The recognition test revealed that the memory performance of experts was significantly superior to that of novices for scenes with highly functional aspects. The memory performance for the scenes with few functional aspects did not differ between novices and experts. These results suggest that experts pay more attention to, and thus remember better, scenes with functional meanings than do novices.

OpenSceneGraph 3 Cookbook

CERN Document Server

Wang, Rui

2012-01-01

This is a cookbook full of recipes with practical examples enriched with code and the required screenshots for easy and quick comprehension. You should be familiar with the basic concepts of the OpenSceneGraph API and should be able to write simple programs. Some OpenGL and math knowledge will help a lot, too.

Determination of the impact of RGB points cloud attribute quality on color-based segmentation process

Directory of Open Access Journals (Sweden)

Bartłomiej Kraszewski

2015-06-01

Full Text Available The article presents the results of research on the effect that radiometric quality of point cloud RGB attributes have on color-based segmentation. In the research, a point cloud with a resolution of 5 mm, received from FAROARO Photon 120 scanner, described the fragment of an office’s room and color images were taken by various digital cameras. The images were acquired by SLR Nikon D3X, and SLR Canon D200 integrated with the laser scanner, compact camera Panasonic TZ-30 and a mobile phone digital camera. Color information from images was spatially related to point cloud in FAROARO Scene software. The color-based segmentation of testing data was performed with the use of a developed application named “RGB Segmentation”. The application was based on public Point Cloud Libraries (PCL and allowed to extract subsets of points fulfilling the criteria of segmentation from the source point cloud using region growing method.Using the developed application, the segmentation of four tested point clouds containing different RGB attributes from various images was performed. Evaluation of segmentation process was performed based on comparison of segments acquired using the developed application and extracted manually by an operator. The following items were compared: the number of obtained segments, the number of correctly identified objects and the correctness of segmentation process. The best correctness of segmentation and most identified objects were obtained using the data with RGB attribute from Nikon D3X images. Based on the results it was found that quality of RGB attributes of point cloud had impact only on the number of identified objects. In case of correctness of the segmentation, as well as its error no apparent relationship between the quality of color information and the result of the process was found.[b]Keywords[/b]: terrestrial laser scanning, color-based segmentation, RGB attribute, region growing method, digital images, points cloud

The Anthropo-scene: A guide for the perplexed.

Science.gov (United States)

Lorimer, Jamie

2017-02-01

The scientific proposal that the Earth has entered a new epoch as a result of human activities - the Anthropocene - has catalysed a flurry of intellectual activity. I introduce and review the rich, inchoate and multi-disciplinary diversity of this Anthropo-scene. I identify five ways in which the concept of the Anthropocene has been mobilized: scientific question, intellectual zeitgeist, ideological provocation, new ontologies and science fiction. This typology offers an analytical framework for parsing this diversity, for understanding the interactions between different ways of thinking in the Anthropo-scene, and thus for comprehending elements of its particular and peculiar sociabilities. Here I deploy this framework to situate Earth Systems Science within the Anthropo-scene, exploring both the status afforded science in discussions of this new epoch, and the various ways in which the other means of engaging with the concept come to shape the conduct, content and politics of this scientific enquiry. In conclusion the paper reflects on the potential of the Anthropocene for new modes of academic praxis.

Where and when Do Objects Become Scenes?

Directory of Open Access Journals (Sweden)

Jiye G. Kim

2011-05-01

Full Text Available Scenes can be understood with extraordinary speed and facility, not merely as an inventory of individual objects but in the coding of the relations among them. These relations, which can be readily described by prepositions or gerunds (e.g., a hand holding a pen, allows the explicit representation of complex structures. Where in the brain are inter-object relations specified? In a series of fMRI experiments, we show that pairs of objects shown as interacting elicit greater activity in LOC than when the objects are depicted side-by-side (e.g., a hand beside a pen. Other visual areas, PPA, IPS, and DLPFC, did not show this sensitivity to scene relations, rendering it unlikely that the relations were computed in these regions. Using EEG and TMS, we further show that LOC's sensitivity to object interactions arises around 170ms post stimulus onset and that disruption of normal LOC activity—but not IPS activity—is detrimental to the behavioral sensitivity of inter-object relations. Insofar as LOC is the earliest cortical region where shape is distinguished from texture, our results provide strong evidence that scene-like relations are achieved simultaneously with the perception of object shape and not inferred at some stage following object identification.

Single-View 3D Scene Reconstruction and Parsing by Attribute Grammar.

Science.gov (United States)

Liu, Xiaobai; Zhao, Yibiao; Zhu, Song-Chun

2018-03-01

In this paper, we present an attribute grammar for solving two coupled tasks: i) parsing a 2D image into semantic regions; and ii) recovering the 3D scene structures of all regions. The proposed grammar consists of a set of production rules, each describing a kind of spatial relation between planar surfaces in 3D scenes. These production rules are used to decompose an input image into a hierarchical parse graph representation where each graph node indicates a planar surface or a composite surface. Different from other stochastic image grammars, the proposed grammar augments each graph node with a set of attribute variables to depict scene-level global geometry, e.g., camera focal length, or local geometry, e.g., surface normal, contact lines between surfaces. These geometric attributes impose constraints between a node and its off-springs in the parse graph. Under a probabilistic framework, we develop a Markov Chain Monte Carlo method to construct a parse graph that optimizes the 2D image recognition and 3D scene reconstruction purposes simultaneously. We evaluated our method on both public benchmarks and newly collected datasets. Experiments demonstrate that the proposed method is capable of achieving state-of-the-art scene reconstruction of a single image.

Reconstruction and simplification of urban scene models based on oblique images

Science.gov (United States)

Liu, J.; Guo, B.

2014-08-01

We describe a multi-view stereo reconstruction and simplification algorithms for urban scene models based on oblique images. The complexity, diversity, and density within the urban scene, it increases the difficulty to build the city models using the oblique images. But there are a lot of flat surfaces existing in the urban scene. One of our key contributions is that a dense matching algorithm based on Self-Adaptive Patch in view of the urban scene is proposed. The basic idea of matching propagating based on Self-Adaptive Patch is to build patches centred by seed points which are already matched. The extent and shape of the patches can adapt to the objects of urban scene automatically: when the surface is flat, the extent of the patch would become bigger; while the surface is very rough, the extent of the patch would become smaller. The other contribution is that the mesh generated by Graph Cuts is 2-manifold surface satisfied the half edge data structure. It is solved by clustering and re-marking tetrahedrons in s-t graph. The purpose of getting 2- manifold surface is to simply the mesh by edge collapse algorithm which can preserve and stand out the features of buildings.

Effects of scene content and layout on the perceived light direction in 3D spaces.

Science.gov (United States)

Xia, Ling; Pont, Sylvia C; Heynderickx, Ingrid

2016-08-01

The lighting and furnishing of an interior space (i.e., the reflectance of its materials, the geometries of the furnishings, and their arrangement) determine the appearance of this space. Conversely, human observers infer lighting properties from the space's appearance. We conducted two psychophysical experiments to investigate how the perception of the light direction is influenced by a scene's objects and their layout using real scenes. In the first experiment, we confirmed that the shape of the objects in the scene and the scene layout influence the perceived light direction. In the second experiment, we systematically investigated how specific shape properties influenced the estimation of the light direction. The results showed that increasing the number of visible faces of an object, ultimately using globally spherical shapes in the scene, supported the veridicality of the estimated light direction. Furthermore, symmetric arrangements in the scene improved the estimation of the tilt direction. Thus, human perception of light should integrally consider materials, scene content, and layout.

Overt attention in natural scenes: objects dominate features.

Science.gov (United States)

Stoll, Josef; Thrun, Michael; Nuthmann, Antje; Einhäuser, Wolfgang

2015-02-01

Whether overt attention in natural scenes is guided by object content or by low-level stimulus features has become a matter of intense debate. Experimental evidence seemed to indicate that once object locations in a scene are known, salience models provide little extra explanatory power. This approach has recently been criticized for using inadequate models of early salience; and indeed, state-of-the-art salience models outperform trivial object-based models that assume a uniform distribution of fixations on objects. Here we propose to use object-based models that take a preferred viewing location (PVL) close to the centre of objects into account. In experiment 1, we demonstrate that, when including this comparably subtle modification, object-based models again are at par with state-of-the-art salience models in predicting fixations in natural scenes. One possible interpretation of these results is that objects rather than early salience dominate attentional guidance. In this view, early-salience models predict fixations through the correlation of their features with object locations. To test this hypothesis directly, in two additional experiments we reduced low-level salience in image areas of high object content. For these modified stimuli, the object-based model predicted fixations significantly better than early salience. This finding held in an object-naming task (experiment 2) and a free-viewing task (experiment 3). These results provide further evidence for object-based fixation selection--and by inference object-based attentional guidance--in natural scenes. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Neural Correlates of Divided Attention in Natural Scenes.

Science.gov (United States)

Fagioli, Sabrina; Macaluso, Emiliano

2016-09-01

Individuals are able to split attention between separate locations, but divided spatial attention incurs the additional requirement of monitoring multiple streams of information. Here, we investigated divided attention using photos of natural scenes, where the rapid categorization of familiar objects and prior knowledge about the likely positions of objects in the real world might affect the interplay between these spatial and nonspatial factors. Sixteen participants underwent fMRI during an object detection task. They were presented with scenes containing either a person or a car, located on the left or right side of the photo. Participants monitored either one or both object categories, in one or both visual hemifields. First, we investigated the interplay between spatial and nonspatial attention by comparing conditions of divided attention between categories and/or locations. We then assessed the contribution of top-down processes versus stimulus-driven signals by separately testing the effects of divided attention in target and nontarget trials. The results revealed activation of a bilateral frontoparietal network when dividing attention between the two object categories versus attending to a single category but no main effect of dividing attention between spatial locations. Within this network, the left dorsal premotor cortex and the left intraparietal sulcus were found to combine task- and stimulus-related signals. These regions showed maximal activation when participants monitored two categories at spatially separate locations and the scene included a nontarget object. We conclude that the dorsal frontoparietal cortex integrates top-down and bottom-up signals in the presence of distractors during divided attention in real-world scenes.

Gist in time: Scene semantics and structure enhance recall of searched objects.

Science.gov (United States)

Josephs, Emilie L; Draschkow, Dejan; Wolfe, Jeremy M; Võ, Melissa L-H

2016-09-01

Previous work has shown that recall of objects that are incidentally encountered as targets in visual search is better than recall of objects that have been intentionally memorized (Draschkow, Wolfe, & Võ, 2014). However, this counter-intuitive result is not seen when these tasks are performed with non-scene stimuli. The goal of the current paper is to determine what features of search in a scene contribute to higher recall rates when compared to a memorization task. In each of four experiments, we compare the free recall rate for target objects following a search to the rate following a memorization task. Across the experiments, the stimuli include progressively more scene-related information. Experiment 1 provides the spatial relations between objects. Experiment 2 adds relative size and depth of objects. Experiments 3 and 4 include scene layout and semantic information. We find that search leads to better recall than explicit memorization in cases where scene layout and semantic information are present, as long as the participant has ample time (2500ms) to integrate this information with knowledge about the target object (Exp. 4). These results suggest that the integration of scene and target information not only leads to more efficient search, but can also contribute to stronger memory representations than intentional memorization. Copyright © 2016 Elsevier B.V. All rights reserved.

The development of brain systems associated with successful memory retrieval of scenes.

Science.gov (United States)

Ofen, Noa; Chai, Xiaoqian J; Schuil, Karen D I; Whitfield-Gabrieli, Susan; Gabrieli, John D E

2012-07-18

Neuroanatomical and psychological evidence suggests prolonged maturation of declarative memory systems in the human brain from childhood into young adulthood. Here, we examine functional brain development during successful memory retrieval of scenes in children, adolescents, and young adults ages 8-21 via functional magnetic resonance imaging. Recognition memory improved with age, specifically for accurate identification of studied scenes (hits). Successful retrieval (correct old-new decisions for studied vs unstudied scenes) was associated with activations in frontal, parietal, and medial temporal lobe (MTL) regions. Activations associated with successful retrieval increased with age in left parietal cortex (BA7), bilateral prefrontal, and bilateral caudate regions. In contrast, activations associated with successful retrieval did not change with age in the MTL. Psychophysiological interaction analysis revealed that there were, however, age-relate changes in differential connectivity for successful retrieval between MTL and prefrontal regions. These results suggest that neocortical regions related to attentional or strategic control show the greatest developmental changes for memory retrieval of scenes. Furthermore, these results suggest that functional interactions between MTL and prefrontal regions during memory retrieval also develop into young adulthood. The developmental increase of memory-related activations in frontal and parietal regions for retrieval of scenes and the absence of such an increase in MTL regions parallels what has been observed for memory encoding of scenes.

Image Chunking: Defining Spatial Building Blocks for Scene Analysis.

Science.gov (United States)

1987-04-01

mumgs0.USmusa 7.AUWOJO 4. CIUTAC Rm6ANT Wuugme*j James V/. Mlahoney DACA? 6-85-C-00 10 NOQ 1 4-85-K-O 124 Artificial Inteligence Laboratory US USS 545...0197 672 IMAGE CHUWING: DEINING SPATIAL UILDING PLOCKS FOR 142 SCENE ANRLYSIS(U) MASSACHUSETTS INST OF TECH CAIIAIDGE ARTIFICIAL INTELLIGENCE LAO J...Technical Report 980 F-Image Chunking: Defining Spatial Building Blocks for Scene DTm -Analysis S ELECTED James V. Mahoney’ MIT Artificial Intelligence

Rough-fuzzy clustering and unsupervised feature selection for wavelet based MR image segmentation.

Directory of Open Access Journals (Sweden)

Pradipta Maji

Full Text Available Image segmentation is an indispensable process in the visualization of human tissues, particularly during clinical analysis of brain magnetic resonance (MR images. For many human experts, manual segmentation is a difficult and time consuming task, which makes an automated brain MR image segmentation method desirable. In this regard, this paper presents a new segmentation method for brain MR images, integrating judiciously the merits of rough-fuzzy computing and multiresolution image analysis technique. The proposed method assumes that the major brain tissues, namely, gray matter, white matter, and cerebrospinal fluid from the MR images are considered to have different textural properties. The dyadic wavelet analysis is used to extract the scale-space feature vector for each pixel, while the rough-fuzzy clustering is used to address the uncertainty problem of brain MR image segmentation. An unsupervised feature selection method is introduced, based on maximum relevance-maximum significance criterion, to select relevant and significant textural features for segmentation problem, while the mathematical morphology based skull stripping preprocessing step is proposed to remove the non-cerebral tissues like skull. The performance of the proposed method, along with a comparison with related approaches, is demonstrated on a set of synthetic and real brain MR images using standard validity indices.

Large-scale building scenes reconstruction from close-range images based on line and plane feature

Science.gov (United States)

Ding, Yi; Zhang, Jianqing

2007-11-01

Automatic generate 3D models of buildings and other man-made structures from images has become a topic of increasing importance, those models may be in applications such as virtual reality, entertainment industry and urban planning. In this paper we address the main problems and available solution for the generation of 3D models from terrestrial images. We first generate a coarse planar model of the principal scene planes and then reconstruct windows to refine the building models. There are several points of novelty: first we reconstruct the coarse wire frame model use the line segments matching with epipolar geometry constraint; Secondly, we detect the position of all windows in the image and reconstruct the windows by established corner points correspondences between images, then add the windows to the coarse model to refine the building models. The strategy is illustrated on image triple of college building.

Global Transsaccadic Change Blindness During Scene Perception

National Research Council Canada - National Science Library

Henderson, John

2003-01-01

.... The results from two experiments demonstrated a global transsaccadic change-blindness effect, suggesting that point-by-point visual representations are not functional across saccades during complex scene perception. Ahstract.

Peptide/protein-polymer conjugates: synthetic strategies and design concepts.

Science.gov (United States)

Gauthier, Marc A; Klok, Harm-Anton

2008-06-21

This feature article provides a compilation of tools available for preparing well-defined peptide/protein-polymer conjugates, which are defined as hybrid constructs combining (i) a defined number of peptide/protein segments with uniform chain lengths and defined monomer sequences (primary structure) with (ii) a defined number of synthetic polymer chains. The first section describes methods for post-translational, or direct, introduction of chemoselective handles onto natural or synthetic peptides/proteins. Addressed topics include the residue- and/or site-specific modification of peptides/proteins at Arg, Asp, Cys, Gln, Glu, Gly, His, Lys, Met, Phe, Ser, Thr, Trp, Tyr and Val residues and methods for producing peptides/proteins containing non-canonical amino acids by peptide synthesis and protein engineering. In the second section, methods for introducing chemoselective groups onto the side-chain or chain-end of synthetic polymers produced by radical, anionic, cationic, metathesis and ring-opening polymerization are described. The final section discusses convergent and divergent strategies for covalently assembling polymers and peptides/proteins. An overview of the use of chemoselective reactions such as Heck, Sonogashira and Suzuki coupling, Diels-Alder cycloaddition, Click chemistry, Staudinger ligation, Michael's addition, reductive alkylation and oxime/hydrazone chemistry for the convergent synthesis of peptide/protein-polymer conjugates is given. Divergent approaches for preparing peptide/protein-polymer conjugates which are discussed include peptide synthesis from synthetic polymer supports, polymerization from peptide/protein macroinitiators or chain transfer agents and the polymerization of peptide side-chain monomers.

Remote Sensing Image Registration with Line Segments and Their Intersections

Directory of Open Access Journals (Sweden)

Chengjin Lyu

2017-05-01

Full Text Available Image registration is a basic but essential step for remote sensing image processing, and finding stable features in multitemporal images is one of the most considerable challenges in the field. The main shape contours of artificial objects (e.g., roads, buildings, farmlands, and airports can be generally described as a group of line segments, which are stable features, even in images with evident background changes (e.g., images taken before and after a disaster. In this study, a registration method that uses line segments and their intersections is proposed for multitemporal remote sensing images. First, line segments are extracted in image pyramids to unify the scales of the reference image and the test image. Then, a line descriptor based on the gradient distribution of local areas is constructed, and the segments are matched in image pyramids. Lastly, triplets of intersections of matching lines are selected to estimate affine transformation between two images. Additional corresponding intersections are provided based on the estimated transformation, and an iterative process is adopted to remove outliers. The performance of the proposed method is tested on a variety of optical remote sensing image pairs, including synthetic and real data. Compared with existing methods, our method can provide more accurate registration results, even in images with significant background changes.

Amplitude-aware permutation entropy: Illustration in spike detection and signal segmentation.

Science.gov (United States)

Azami, Hamed; Escudero, Javier

2016-05-01

Signal segmentation and spike detection are two important biomedical signal processing applications. Often, non-stationary signals must be segmented into piece-wise stationary epochs or spikes need to be found among a background of noise before being further analyzed. Permutation entropy (PE) has been proposed to evaluate the irregularity of a time series. PE is conceptually simple, structurally robust to artifacts, and computationally fast. It has been extensively used in many applications, but it has two key shortcomings. First, when a signal is symbolized using the Bandt-Pompe procedure, only the order of the amplitude values is considered and information regarding the amplitudes is discarded. Second, in the PE, the effect of equal amplitude values in each embedded vector is not addressed. To address these issues, we propose a new entropy measure based on PE: the amplitude-aware permutation entropy (AAPE). AAPE is sensitive to the changes in the amplitude, in addition to the frequency, of the signals thanks to it being more flexible than the classical PE in the quantification of the signal motifs. To demonstrate how the AAPE method can enhance the quality of the signal segmentation and spike detection, a set of synthetic and realistic synthetic neuronal signals, electroencephalograms and neuronal data are processed. We compare the performance of AAPE in these problems against state-of-the-art approaches and evaluate the significance of the differences with a repeated ANOVA with post hoc Tukey's test. In signal segmentation, the accuracy of AAPE-based method is higher than conventional segmentation methods. AAPE also leads to more robust results in the presence of noise. The spike detection results show that AAPE can detect spikes well, even when presented with single-sample spikes, unlike PE. For multi-sample spikes, the changes in AAPE are larger than in PE. We introduce a new entropy metric, AAPE, that enables us to consider amplitude information in the

Ontology of a scene based on Java 3D architecture.

Directory of Open Access Journals (Sweden)

Rubén González Crespo

2009-12-01

Full Text Available The present article seeks to make an approach to the class hierarchy of a scene built with the architecture Java 3D, to develop an ontology of a scene as from the semantic essential components for the semantic structuring of the Web3D. Java was selected because the language recommended by the W3C Consortium for the Development of the Web3D oriented applications as from X3D standard is Xj3D which compositionof their Schemas is based the architecture of Java3D In first instance identifies the domain and scope of the ontology, defining classes and subclasses that comprise from Java3D architecture and the essential elements of a scene, as its point of origin, the field of rotation, translation The limitation of the scene and the definition of shaders, then define the slots that are declared in RDF as a framework for describing the properties of the classes established from identifying thedomain and range of each class, then develops composition of the OWL ontology on SWOOP Finally, be perform instantiations of the ontology building for a Iconosphere object as from class expressions defined.

Modelling Technology for Building Fire Scene with Virtual Geographic Environment

Science.gov (United States)

Song, Y.; Zhao, L.; Wei, M.; Zhang, H.; Liu, W.

2017-09-01

Building fire is a risky activity that can lead to disaster and massive destruction. The management and disposal of building fire has always attracted much interest from researchers. Integrated Virtual Geographic Environment (VGE) is a good choice for building fire safety management and emergency decisions, in which a more real and rich fire process can be computed and obtained dynamically, and the results of fire simulations and analyses can be much more accurate as well. To modelling building fire scene with VGE, the application requirements and modelling objective of building fire scene were analysed in this paper. Then, the four core elements of modelling building fire scene (the building space environment, the fire event, the indoor Fire Extinguishing System (FES) and the indoor crowd) were implemented, and the relationship between the elements was discussed also. Finally, with the theory and framework of VGE, the technology of building fire scene system with VGE was designed within the data environment, the model environment, the expression environment, and the collaborative environment as well. The functions and key techniques in each environment are also analysed, which may provide a reference for further development and other research on VGE.

Local Competition-Based Superpixel Segmentation Algorithm in Remote Sensing.

Science.gov (United States)

Liu, Jiayin; Tang, Zhenmin; Cui, Ying; Wu, Guoxing

2017-06-12

Remote sensing technologies have been widely applied in urban environments' monitoring, synthesis and modeling. Incorporating spatial information in perceptually coherent regions, superpixel-based approaches can effectively eliminate the "salt and pepper" phenomenon which is common in pixel-wise approaches. Compared with fixed-size windows, superpixels have adaptive sizes and shapes for different spatial structures. Moreover, superpixel-based algorithms can significantly improve computational efficiency owing to the greatly reduced number of image primitives. Hence, the superpixel algorithm, as a preprocessing technique, is more and more popularly used in remote sensing and many other fields. In this paper, we propose a superpixel segmentation algorithm called Superpixel Segmentation with Local Competition (SSLC), which utilizes a local competition mechanism to construct energy terms and label pixels. The local competition mechanism leads to energy terms locality and relativity, and thus, the proposed algorithm is less sensitive to the diversity of image content and scene layout. Consequently, SSLC could achieve consistent performance in different image regions. In addition, the Probability Density Function (PDF), which is estimated by Kernel Density Estimation (KDE) with the Gaussian kernel, is introduced to describe the color distribution of superpixels as a more sophisticated and accurate measure. To reduce computational complexity, a boundary optimization framework is introduced to only handle boundary pixels instead of the whole image. We conduct experiments to benchmark the proposed algorithm with the other state-of-the-art ones on the Berkeley Segmentation Dataset (BSD) and remote sensing images. Results demonstrate that the SSLC algorithm yields the best overall performance, while the computation time-efficiency is still competitive.

Guidance of Attention to Objects and Locations by Long-Term Memory of Natural Scenes

Science.gov (United States)

Becker, Mark W.; Rasmussen, Ian P.

2008-01-01

Four flicker change-detection experiments demonstrate that scene-specific long-term memory guides attention to both behaviorally relevant locations and objects within a familiar scene. Participants performed an initial block of change-detection trials, detecting the addition of an object to a natural scene. After a 30-min delay, participants…

Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites

Science.gov (United States)

Maalek, Reza; Lichti, Derek D; Ruwanpura, Janaka Y

2018-01-01

Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may not provide generalizable solutions for all environments. In addition, outliers exist in construction site point clouds due to data artefacts caused by moving objects, occlusions and dust. To address these concerns, a novel method for robust classification and segmentation of planar and linear features is proposed. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a new robust clustering method, the robust complete linkage method. A robust method is also proposed to extract the points of flat-slab floors and/or ceilings independent of the aforementioned stages to improve computational efficiency. The applicability of the proposed method is evaluated in eight datasets acquired from a complex laboratory environment and two construction sites at the University of Calgary. The precision, recall, and accuracy of the segmentation at both construction sites were 96.8%, 97.7% and 95%, respectively. These results demonstrate the suitability of the proposed method for robust segmentation of planar and linear features of contaminated datasets, such as those collected from construction sites. PMID:29518062

Performance evaluation of 2D and 3D deep learning approaches for automatic segmentation of multiple organs on CT images

Science.gov (United States)

Zhou, Xiangrong; Yamada, Kazuma; Kojima, Takuya; Takayama, Ryosuke; Wang, Song; Zhou, Xinxin; Hara, Takeshi; Fujita, Hiroshi

2018-02-01

The purpose of this study is to evaluate and compare the performance of modern deep learning techniques for automatically recognizing and segmenting multiple organ regions on 3D CT images. CT image segmentation is one of the important task in medical image analysis and is still very challenging. Deep learning approaches have demonstrated the capability of scene recognition and semantic segmentation on nature images and have been used to address segmentation problems of medical images. Although several works showed promising results of CT image segmentation by using deep learning approaches, there is no comprehensive evaluation of segmentation performance of the deep learning on segmenting multiple organs on different portions of CT scans. In this paper, we evaluated and compared the segmentation performance of two different deep learning approaches that used 2D- and 3D deep convolutional neural networks (CNN) without- and with a pre-processing step. A conventional approach that presents the state-of-the-art performance of CT image segmentation without deep learning was also used for comparison. A dataset that includes 240 CT images scanned on different portions of human bodies was used for performance evaluation. The maximum number of 17 types of organ regions in each CT scan were segmented automatically and compared to the human annotations by using ratio of intersection over union (IU) as the criterion. The experimental results demonstrated the IUs of the segmentation results had a mean value of 79% and 67% by averaging 17 types of organs that segmented by a 3D- and 2D deep CNN, respectively. All the results of the deep learning approaches showed a better accuracy and robustness than the conventional segmentation method that used probabilistic atlas and graph-cut methods. The effectiveness and the usefulness of deep learning approaches were demonstrated for solving multiple organs segmentation problem on 3D CT images.

An earth remote sensing satellite- 1 Synthetic Aperture Radar Mosaic of the Tanana River Basin in Alaska

Science.gov (United States)

Wivell, Charles E.; Olmsted, Coert; Steinwand, Daniel R.; Taylor, Christopher

1993-01-01

Because the pixel location in a line of Synthetic Aperture Radar (SAR) image data is directly related to the distance the pixel is from the radar, terrain elevations cause large displacement errors in the geo-referenced location of the pixel. This is especially true for radar systems with small angles between the nadir and look vectors. Thus, to geo-register a SAR image accurately, the terrain of the area must be taken into account. (Curlander et al., 1987; Kwok et al., 1987, Schreier et al., 1990; Wivell et al., 1992). As part of the 1992 National Aeronautics and Space Administration's Earth Observing System Version 0 activities, a prototype SAR geocod-. ing and terrain correction system was developed at the US. Geological Survey's (USGS) E~os Data Center (EDC) in Sioux Falls, South Dakota. Using this system with 3-arc-second digital elevation models (DEMs) mosaicked at the ED^ Alaska Field Office, 21 ERS-I s.4~ scenes acquired at the Alaska SAR Facility were automatically geocoded, terrain corrected, and mosaicked. The geo-registered scenes were mosaicked using a simple concatenation.

Semantic memory for contextual regularities within and across scene categories: evidence from eye movements.

Science.gov (United States)

Brockmole, James R; Le-Hoa Võ, Melissa

2010-10-01

When encountering familiar scenes, observers can use item-specific memory to facilitate the guidance of attention to objects appearing in known locations or configurations. Here, we investigated how memory for relational contingencies that emerge across different scenes can be exploited to guide attention. Participants searched for letter targets embedded in pictures of bedrooms. In a between-subjects manipulation, targets were either always on a bed pillow or randomly positioned. When targets were systematically located within scenes, search for targets became more efficient. Importantly, this learning transferred to bedrooms without pillows, ruling out learning that is based on perceptual contingencies. Learning also transferred to living room scenes, but it did not transfer to kitchen scenes, even though both scene types contained pillows. These results suggest that statistical regularities abstracted across a range of stimuli are governed by semantic expectations regarding the presence of target-predicting local landmarks. Moreover, explicit awareness of these contingencies led to a central tendency bias in recall memory for precise target positions that is similar to the spatial category effects observed in landmark memory. These results broaden the scope of conditions under which contextual cuing operates and demonstrate how semantic memory plays a causal and independent role in the learning of associations between objects in real-world scenes.

Prosthetic component segmentation with blur compensation: a fast method for 3D fluoroscopy.

Science.gov (United States)

Tarroni, Giacomo; Tersi, Luca; Corsi, Cristiana; Stagni, Rita

2012-06-01

A new method for prosthetic component segmentation from fluoroscopic images is presented. The hybrid approach we propose combines diffusion filtering, region growing and level-set techniques without exploiting any a priori knowledge of the analyzed geometry. The method was evaluated on a synthetic dataset including 270 images of knee and hip prosthesis merged to real fluoroscopic data simulating different conditions of blurring and illumination gradient. The performance of the method was assessed by comparing estimated contours to references using different metrics. Results showed that the segmentation procedure is fast, accurate, independent on the operator as well as on the specific geometrical characteristics of the prosthetic component, and able to compensate for amount of blurring and illumination gradient. Importantly, the method allows a strong reduction of required user interaction time when compared to traditional segmentation techniques. Its effectiveness and robustness in different image conditions, together with simplicity and fast implementation, make this prosthetic component segmentation procedure promising and suitable for multiple clinical applications including assessment of in vivo joint kinematics in a variety of cases.

The elephant in the room: Inconsistency in scene viewing and representation.

Science.gov (United States)

Spotorno, Sara; Tatler, Benjamin W

2017-10-01

We examined the extent to which semantic informativeness, consistency with expectations and perceptual salience contribute to object prioritization in scene viewing and representation. In scene viewing (Experiments 1-2), semantic guidance overshadowed perceptual guidance in determining fixation order, with the greatest prioritization for objects that were diagnostic of the scene's depicted event. Perceptual properties affected selection of consistent objects (regardless of their informativeness) but not of inconsistent objects. Semantic and perceptual properties also interacted in influencing foveal inspection, as inconsistent objects were fixated longer than low but not high salience diagnostic objects. While not studied in direct competition with each other (each studied in competition with diagnostic objects), we found that inconsistent objects were fixated earlier and for longer than consistent but marginally informative objects. In change detection (Experiment 3), perceptual guidance overshadowed semantic guidance, promoting detection of highly salient changes. A residual advantage for diagnosticity over inconsistency emerged only when selection prioritization could not be based on low-level features. Overall these findings show that semantic inconsistency is not prioritized within a scene when competing with other relevant information that is essential to scene understanding and respects observers' expectations. Moreover, they reveal that the relative dominance of semantic or perceptual properties during selection depends on ongoing task requirements. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features

Directory of Open Access Journals (Sweden)

Linyi Li

2017-01-01

Full Text Available In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images.

Mirth and Murder: Crime Scene Investigation as a Work Context for Examining Humor Applications

Science.gov (United States)

Roth, Gene L.; Vivona, Brian

2010-01-01

Within work settings, humor is used by workers for a wide variety of purposes. This study examines humor applications of a specific type of worker in a unique work context: crime scene investigation. Crime scene investigators examine death and its details. Members of crime scene units observe death much more frequently than other police officers…

Smoking scenes in popular Japanese serial television dramas: descriptive analysis during the same 3-month period in two consecutive years.

Science.gov (United States)

Kanda, Hideyuki; Okamura, Tomonori; Turin, Tanvir Chowdhury; Hayakawa, Takehito; Kadowaki, Takashi; Ueshima, Hirotsugu

2006-06-01

Japanese serial television dramas are becoming very popular overseas, particularly in other Asian countries. Exposure to smoking scenes in movies and television dramas has been known to trigger initiation of habitual smoking in young people. Smoking scenes in Japanese dramas may affect the smoking behavior of many young Asians. We examined smoking scenes and smoking-related items in serial television dramas targeting young audiences in Japan during the same season in two consecutive years. Fourteen television dramas targeting the young audience broadcast between July and September in 2001 and 2002 were analyzed. A total of 136 h 42 min of television programs were divided into unit scenes of 3 min (a total of 2734 unit scenes). All the unit scenes were reviewed for smoking scenes and smoking-related items. Of the 2734 3-min unit scenes, 205 (7.5%) were actual smoking scenes and 387 (14.2%) depicted smoking environments with the presence of smoking-related items, such as ash trays. In 185 unit scenes (90.2% of total smoking scenes), actors were shown smoking. Actresses were less frequently shown smoking (9.8% of total smoking scenes). Smoking characters in dramas were in the 20-49 age group in 193 unit scenes (94.1% of total smoking scenes). In 96 unit scenes (46.8% of total smoking scenes), at least one non-smoker was present in the smoking scenes. The smoking locations were mainly indoors, including offices, restaurants and homes (122 unit scenes, 59.6%). The most common smoking-related items shown were ash trays (in 45.5% of smoking-item-related scenes) and cigarettes (in 30.2% of smoking-item-related scenes). Only 3 unit scenes (0.1 % of all scenes) promoted smoking prohibition. This was a descriptive study to examine the nature of smoking scenes observed in Japanese television dramas from a public health perspective.

Technicolor/INRIA team at the MediaEval 2013 Violent Scenes Detection Task

OpenAIRE

Penet , Cédric; Demarty , Claire-Hélène; Gravier , Guillaume; Gros , Patrick

2013-01-01

International audience; This paper presents the work done at Technicolor and INRIA regarding the MediaEval 2013 Violent Scenes Detection task, which aims at detecting violent scenes in movies. We participated in both the objective and the subjective subtasks.

Modification of computational auditory scene analysis (CASA) for noise-robust acoustic feature

Science.gov (United States)

Kwon, Minseok

While there have been many attempts to mitigate interferences of background noise, the performance of automatic speech recognition (ASR) still can be deteriorated by various factors with ease. However, normal hearing listeners can accurately perceive sounds of their interests, which is believed to be a result of Auditory Scene Analysis (ASA). As a first attempt, the simulation of the human auditory processing, called computational auditory scene analysis (CASA), was fulfilled through physiological and psychological investigations of ASA. CASA comprised of Zilany-Bruce auditory model, followed by tracking fundamental frequency for voice segmentation and detecting pairs of onset/offset at each characteristic frequency (CF) for unvoiced segmentation. The resulting Time-Frequency (T-F) representation of acoustic stimulation was converted into acoustic feature, gammachirp-tone frequency cepstral coefficients (GFCC). 11 keywords with various environmental conditions are used and the robustness of GFCC was evaluated by spectral distance (SD) and dynamic time warping distance (DTW). In "clean" and "noisy" conditions, the application of CASA generally improved noise robustness of the acoustic feature compared to a conventional method with or without noise suppression using MMSE estimator. The intial study, however, not only showed the noise-type dependency at low SNR, but also called the evaluation methods in question. Some modifications were made to capture better spectral continuity from an acoustic feature matrix, to obtain faster processing speed, and to describe the human auditory system more precisely. The proposed framework includes: 1) multi-scale integration to capture more accurate continuity in feature extraction, 2) contrast enhancement (CE) of each CF by competition with neighboring frequency bands, and 3) auditory model modifications. The model modifications contain the introduction of higher Q factor, middle ear filter more analogous to human auditory system

Multiple vehicle routing and dispatching to an emergency scene

OpenAIRE

M S Daskin; A Haghani

1984-01-01

A model of the distribution of arrival time at the scene of an emergency for the first of many vehicles is developed for the case in which travel times on the links of the network are normally distributed and the path travel times of different vehicles are correlated. The model suggests that the probability that the first vehicle arrives at the scene within a given time may be increased by reducing the path time correlations, even if doing so necessitates increasing the mean path travel time ...

Segmentation: Identification of consumer segments

DEFF Research Database (Denmark)

Høg, Esben

2005-01-01

It is very common to categorise people, especially in the advertising business. Also traditional marketing theory has taken in consumer segments as a favorite topic. Segmentation is closely related to the broader concept of classification. From a historical point of view, classification has its...... origin in other sciences as for example biology, anthropology etc. From an economic point of view, it is called segmentation when specific scientific techniques are used to classify consumers to different characteristic groupings. What is the purpose of segmentation? For example, to be able to obtain...... a basic understanding of grouping people. Advertising agencies may use segmentation totarget advertisements, while food companies may usesegmentation to develop products to various groups of consumers. MAPP has for example investigated the positioning of fish in relation to other food products...

Combined Influence of Visual Scene and Body Tilt on Arm Pointing Movements: Gravity Matters!

Science.gov (United States)

Scotto Di Cesare, Cécile; Sarlegna, Fabrice R.; Bourdin, Christophe; Mestre, Daniel R.; Bringoux, Lionel

2014-01-01

Performing accurate actions such as goal-directed arm movements requires taking into account visual and body orientation cues to localize the target in space and produce appropriate reaching motor commands. We experimentally tilted the body and/or the visual scene to investigate how visual and body orientation cues are combined for the control of unseen arm movements. Subjects were asked to point toward a visual target using an upward movement during slow body and/or visual scene tilts. When the scene was tilted, final pointing errors varied as a function of the direction of the scene tilt (forward or backward). Actual forward body tilt resulted in systematic target undershoots, suggesting that the brain may have overcompensated for the biomechanical movement facilitation arising from body tilt. Combined body and visual scene tilts also affected final pointing errors according to the orientation of the visual scene. The data were further analysed using either a body-centered or a gravity-centered reference frame to encode visual scene orientation with simple additive models (i.e., ‘combined’ tilts equal to the sum of ‘single’ tilts). We found that the body-centered model could account only for some of the data regarding kinematic parameters and final errors. In contrast, the gravity-centered modeling in which the body and visual scene orientations were referred to vertical could explain all of these data. Therefore, our findings suggest that the brain uses gravity, thanks to its invariant properties, as a reference for the combination of visual and non-visual cues. PMID:24925371

Natural - synthetic - artificial!

DEFF Research Database (Denmark)

Nielsen, Peter E

2010-01-01

The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life.......The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life....

Negotiating place and gendered violence in Canada's largest open drug scene.

Science.gov (United States)

McNeil, Ryan; Shannon, Kate; Shaver, Laura; Kerr, Thomas; Small, Will

2014-05-01

Vancouver's Downtown Eastside is home to Canada's largest street-based drug scene and only supervised injection facility (Insite). High levels of violence among men and women have been documented in this neighbourhood. This study was undertaken to explore the role of violence in shaping the socio-spatial relations of women and 'marginal men' (i.e., those occupying subordinate positions within the drug scene) in the Downtown Eastside, including access to Insite. Semi-structured qualitative interviews were conducted with 23 people who inject drugs (PWID) recruited through the Vancouver Area Network of Drug Users, a local drug user organization. Interviews included a mapping exercise. Interview transcripts and maps were analyzed thematically, with an emphasis on how gendered violence shaped participants' spatial practices. Hegemonic forms of masculinity operating within the Downtown Eastside framed the everyday violence experienced by women and marginal men. This violence shaped the spatial practices of women and marginal men, in that they avoided drug scene milieus where they had experienced violence or that they perceived to be dangerous. Some men linked their spatial restrictions to the perceived 'dope quality' of neighbourhood drug dealers to maintain claims to dominant masculinities while enacting spatial strategies to promote safety. Environmental supports provided by health and social care agencies were critical in enabling women and marginal men to negotiate place and survival within the context of drug scene violence. Access to Insite did not motivate participants to enter into "dangerous" drug scene milieus but they did venture into these areas if necessary to obtain drugs or generate income. Gendered violence is critical in restricting the geographies of men and marginal men within the street-based drug scene. There is a need to scale up existing environmental interventions, including supervised injection services, to minimize violence and potential drug

Real-time scene and signature generation for ladar and imaging sensors

Science.gov (United States)

Swierkowski, Leszek; Christie, Chad L.; Antanovskii, Leonid; Gouthas, Efthimios

2014-05-01

This paper describes development of two key functionalities within the VIRSuite scene simulation program, broadening its scene generation capabilities and increasing accuracy of thermal signatures. Firstly, a new LADAR scene generation module has been designed. It is capable of simulating range imagery for Geiger mode LADAR, in addition to the already existing functionality for linear mode systems. Furthermore, a new 3D heat diffusion solver has been developed within the VIRSuite signature prediction module. It is capable of calculating the temperature distribution in complex three-dimensional objects for enhanced dynamic prediction of thermal signatures. With these enhancements, VIRSuite is now a robust tool for conducting dynamic simulation for missiles with multi-mode seekers.

Three-dimensional scene encryption and display based on computer-generated holograms.

Science.gov (United States)

Kong, Dezhao; Cao, Liangcai; Jin, Guofan; Javidi, Bahram

2016-10-10

An optical encryption and display method for a three-dimensional (3D) scene is proposed based on computer-generated holograms (CGHs) using a single phase-only spatial light modulator. The 3D scene is encoded as one complex Fourier CGH. The Fourier CGH is then decomposed into two phase-only CGHs with random distributions by the vector stochastic decomposition algorithm. Two CGHs are interleaved as one final phase-only CGH for optical encryption and reconstruction. The proposed method can support high-level nonlinear optical 3D scene security and complex amplitude modulation of the optical field. The exclusive phase key offers strong resistances of decryption attacks. Experimental results demonstrate the validity of the novel method.

Anticipatory scene representation in preschool children's recall and recognition memory.

Science.gov (United States)

Kreindel, Erica; Intraub, Helene

2017-09-01

Behavioral and neuroscience research on boundary extension (false memory beyond the edges of a view of a scene) has provided new insights into the constructive nature of scene representation, and motivates questions about development. Early research with children (as young as 6-7 years) was consistent with boundary extension, but relied on an analysis of spatial errors in drawings which are open to alternative explanations (e.g. drawing ability). Experiment 1 replicated and extended prior drawing results with 4-5-year-olds and adults. In Experiment 2, a new, forced-choice immediate recognition memory test was implemented with the same children. On each trial, a card (photograph of a simple scene) was immediately replaced by a test card (identical view and either a closer or more wide-angle view) and participants indicated which one matched the original view. Error patterns supported boundary extension; identical photographs were more frequently rejected when the closer view was the original view, than vice versa. This asymmetry was not attributable to a selection bias (guessing tasks; Experiments 3-5). In Experiment 4, working memory load was increased by presenting more expansive views of more complex scenes. Again, children exhibited boundary extension, but now adults did not, unless stimulus duration was reduced to 5 s (limiting time to implement strategies; Experiment 5). We propose that like adults, children interpret photographs as views of places in the world; they extrapolate the anticipated continuation of the scene beyond the view and misattribute it to having been seen. Developmental differences in source attribution decision processes provide an explanation for the age-related differences observed. © 2016 John Wiley & Sons Ltd.

From Theatre Improvisation To Video Scenes

DEFF Research Database (Denmark)

Larsen, Henry; Hvidt, Niels Christian; Friis, Preben

2018-01-01

At Sygehus Lillebaelt, a Danish hospital, there has been a focus for several years on patient communi- cation. This paper reflects on a course focusing on engaging with the patient’s existential themes in particular the negotiations around the creation of video scenes. In the initial workshops, w...

Scene independent real-time indirect illumination

DEFF Research Database (Denmark)

Frisvad, Jeppe Revall; Christensen, Niels Jørgen; Falster, Peter

2005-01-01

A novel method for real-time simulation of indirect illumination is presented in this paper. The method, which we call Direct Radiance Mapping (DRM), is based on basal radiance calculations and does not impose any restrictions on scene geometry or dynamics. This makes the method tractable for rea...

Artificial immune kernel clustering network for unsupervised image segmentation

Institute of Scientific and Technical Information of China (English)

Wenlong Huang; Licheng Jiao

2008-01-01

An immune kernel clustering network (IKCN) is proposed based on the combination of the artificial immune network and the support vector domain description (SVDD) for the unsupervised image segmentation. In the network, a new antibody neighborhood and an adaptive learning coefficient, which is inspired by the long-term memory in cerebral cortices are presented. Starting from IKCN algorithm, we divide the image feature sets into subsets by the antibodies, and then map each subset into a high dimensional feature space by a mercer kernel, where each antibody neighborhood is represented as a support vector hypersphere. The clustering results of the local support vector hyperspheres are combined to yield a global clustering solution by the minimal spanning tree (MST), where a predefined number of clustering is not needed. We compare the proposed methods with two common clustering algorithms for the artificial synthetic data set and several image data sets, including the synthetic texture images and the SAR images, and encouraging experimental results are obtained.

Fuzzy Emotional Semantic Analysis and Automated Annotation of Scene Images

Directory of Open Access Journals (Sweden)

Jianfang Cao

2015-01-01

Full Text Available With the advances in electronic and imaging techniques, the production of digital images has rapidly increased, and the extraction and automated annotation of emotional semantics implied by images have become issues that must be urgently addressed. To better simulate human subjectivity and ambiguity for understanding scene images, the current study proposes an emotional semantic annotation method for scene images based on fuzzy set theory. A fuzzy membership degree was calculated to describe the emotional degree of a scene image and was implemented using the Adaboost algorithm and a back-propagation (BP neural network. The automated annotation method was trained and tested using scene images from the SUN Database. The annotation results were then compared with those based on artificial annotation. Our method showed an annotation accuracy rate of 91.2% for basic emotional values and 82.4% after extended emotional values were added, which correspond to increases of 5.5% and 8.9%, respectively, compared with the results from using a single BP neural network algorithm. Furthermore, the retrieval accuracy rate based on our method reached approximately 89%. This study attempts to lay a solid foundation for the automated emotional semantic annotation of more types of images and therefore is of practical significance.

Scene recognition based on integrating active learning with dictionary learning

Science.gov (United States)

Wang, Chengxi; Yin, Xueyan; Yang, Lin; Gong, Chengrong; Zheng, Caixia; Yi, Yugen

2018-04-01

Scene recognition is a significant topic in the field of computer vision. Most of the existing scene recognition models require a large amount of labeled training samples to achieve a good performance. However, labeling image manually is a time consuming task and often unrealistic in practice. In order to gain satisfying recognition results when labeled samples are insufficient, this paper proposed a scene recognition algorithm named Integrating Active Learning and Dictionary Leaning (IALDL). IALDL adopts projective dictionary pair learning (DPL) as classifier and introduces active learning mechanism into DPL for improving its performance. When constructing sampling criterion in active learning, IALDL considers both the uncertainty and representativeness as the sampling criteria to effectively select the useful unlabeled samples from a given sample set for expanding the training dataset. Experiment results on three standard databases demonstrate the feasibility and validity of the proposed IALDL.

Developing Scene Understanding Neural Software for Realistic Autonomous Outdoor Missions

Science.gov (United States)

2017-09-01

computer using a single graphics processing unit (GPU). To the best of our knowledge, an implementation of the open-source Python -based AlexNet CNN on...1. Introduction Neurons in the brain enable us to understand scenes by assessing the spatial, temporal, and feature relations of objects in the...effort to use computer neural networks to augment human neural intelligence to improve our scene understanding (Krizhevsky et al. 2012; Zhou et al

Image processing pipeline for segmentation and material classification based on multispectral high dynamic range polarimetric images.

Science.gov (United States)

Martínez-Domingo, Miguel Ángel; Valero, Eva M; Hernández-Andrés, Javier; Tominaga, Shoji; Horiuchi, Takahiko; Hirai, Keita

2017-11-27

We propose a method for the capture of high dynamic range (HDR), multispectral (MS), polarimetric (Pol) images of indoor scenes using a liquid crystal tunable filter (LCTF). We have included the adaptive exposure estimation (AEE) method to fully automatize the capturing process. We also propose a pre-processing method which can be applied for the registration of HDR images after they are already built as the result of combining different low dynamic range (LDR) images. This method is applied to ensure a correct alignment of the different polarization HDR images for each spectral band. We have focused our efforts in two main applications: object segmentation and classification into metal and dielectric classes. We have simplified the segmentation using mean shift combined with cluster averaging and region merging techniques. We compare the performance of our segmentation with that of Ncut and Watershed methods. For the classification task, we propose to use information not only in the highlight regions but also in their surrounding area, extracted from the degree of linear polarization (DoLP) maps. We present experimental results which proof that the proposed image processing pipeline outperforms previous techniques developed specifically for MSHDRPol image cubes.

Deconstructing visual scenes in cortex: gradients of object and spatial layout information.

Science.gov (United States)

Harel, Assaf; Kravitz, Dwight J; Baker, Chris I

2013-04-01

Real-world visual scenes are complex cluttered, and heterogeneous stimuli engaging scene- and object-selective cortical regions including parahippocampal place area (PPA), retrosplenial complex (RSC), and lateral occipital complex (LOC). To understand the unique contribution of each region to distributed scene representations, we generated predictions based on a neuroanatomical framework adapted from monkey and tested them using minimal scenes in which we independently manipulated both spatial layout (open, closed, and gradient) and object content (furniture, e.g., bed, dresser). Commensurate with its strong connectivity with posterior parietal cortex, RSC evidenced strong spatial layout information but no object information, and its response was not even modulated by object presence. In contrast, LOC, which lies within the ventral visual pathway, contained strong object information but no background information. Finally, PPA, which is connected with both the dorsal and the ventral visual pathway, showed information about both objects and spatial backgrounds and was sensitive to the presence or absence of either. These results suggest that 1) LOC, PPA, and RSC have distinct representations, emphasizing different aspects of scenes, 2) the specific representations in each region are predictable from their patterns of connectivity, and 3) PPA combines both spatial layout and object information as predicted by connectivity.

A semi-interactive panorama based 3D reconstruction framework for indoor scenes

NARCIS (Netherlands)

Dang, T.K.; Worring, M.; Bui, T.D.

2011-01-01

We present a semi-interactive method for 3D reconstruction specialized for indoor scenes which combines computer vision techniques with efficient interaction. We use panoramas, popularly used for visualization of indoor scenes, but clearly not able to show depth, for their great field of view, as

Higher-order scene statistics of breast images

Science.gov (United States)

Abbey, Craig K.; Sohl-Dickstein, Jascha N.; Olshausen, Bruno A.; Eckstein, Miguel P.; Boone, John M.

2009-02-01

Researchers studying human and computer vision have found description and construction of these systems greatly aided by analysis of the statistical properties of naturally occurring scenes. More specifically, it has been found that receptive fields with directional selectivity and bandwidth properties similar to mammalian visual systems are more closely matched to the statistics of natural scenes. It is argued that this allows for sparse representation of the independent components of natural images [Olshausen and Field, Nature, 1996]. These theories have important implications for medical image perception. For example, will a system that is designed to represent the independent components of natural scenes, where objects occlude one another and illumination is typically reflected, be appropriate for X-ray imaging, where features superimpose on one another and illumination is transmissive? In this research we begin to examine these issues by evaluating higher-order statistical properties of breast images from X-ray projection mammography (PM) and dedicated breast computed tomography (bCT). We evaluate kurtosis in responses of octave bandwidth Gabor filters applied to PM and to coronal slices of bCT scans. We find that kurtosis in PM rises and quickly saturates for filter center frequencies with an average value above 0.95. By contrast, kurtosis in bCT peaks near 0.20 cyc/mm with kurtosis of approximately 2. Our findings suggest that the human visual system may be tuned to represent breast tissue more effectively in bCT over a specific range of spatial frequencies.

An Approach to a Comprehensive Test Framework for Analysis and Evaluation of Text Line Segmentation Algorithms

Directory of Open Access Journals (Sweden)

Zoran N. Milivojevic

2011-09-01

Full Text Available The paper introduces a testing framework for the evaluation and validation of text line segmentation algorithms. Text line segmentation represents the key action for correct optical character recognition. Many of the tests for the evaluation of text line segmentation algorithms deal with text databases as reference templates. Because of the mismatch, the reliable testing framework is required. Hence, a new approach to a comprehensive experimental framework for the evaluation of text line segmentation algorithms is proposed. It consists of synthetic multi-like text samples and real handwritten text as well. Although the tests are mutually independent, the results are cross-linked. The proposed method can be used for different types of scripts and languages. Furthermore, two different procedures for the evaluation of algorithm efficiency based on the obtained error type classification are proposed. The first is based on the segmentation line error description, while the second one incorporates well-known signal detection theory. Each of them has different capabilities and convenience, but they can be used as supplements to make the evaluation process efficient. Overall the proposed procedure based on the segmentation line error description has some advantages, characterized by five measures that describe measurement procedures.

The singular nature of auditory and visual scene analysis in autism.

Science.gov (United States)

Lin, I-Fan; Shirama, Aya; Kato, Nobumasa; Kashino, Makio

2017-02-19

Individuals with autism spectrum disorder often have difficulty acquiring relevant auditory and visual information in daily environments, despite not being diagnosed as hearing impaired or having low vision. Resent psychophysical and neurophysiological studies have shown that autistic individuals have highly specific individual differences at various levels of information processing, including feature extraction, automatic grouping and top-down modulation in auditory and visual scene analysis. Comparison of the characteristics of scene analysis between auditory and visual modalities reveals some essential commonalities, which could provide clues about the underlying neural mechanisms. Further progress in this line of research may suggest effective methods for diagnosing and supporting autistic individuals.This article is part of the themed issue 'Auditory and visual scene analysis'. © 2017 The Author(s).

Study on general design of dual-DMD based infrared two-band scene simulation system

Science.gov (United States)

Pan, Yue; Qiao, Yang; Xu, Xi-ping

2017-02-01

Mid-wave infrared(MWIR) and long-wave infrared(LWIR) two-band scene simulation system is a kind of testing equipment that used for infrared two-band imaging seeker. Not only it would be qualified for working waveband, but also realize the essence requests that infrared radiation characteristics should correspond to the real scene. Past single-digital micromirror device (DMD) based infrared scene simulation system does not take the huge difference between targets and background radiation into account, and it cannot realize the separated modulation to two-band light beam. Consequently, single-DMD based infrared scene simulation system cannot accurately express the thermal scene model that upper-computer built, and it is not that practical. To solve the problem, we design a dual-DMD based, dual-channel, co-aperture, compact-structure infrared two-band scene simulation system. The operating principle of the system is introduced in detail, and energy transfer process of the hardware-in-the-loop simulation experiment is analyzed as well. Also, it builds the equation about the signal-to-noise ratio of infrared detector in the seeker, directing the system overall design. The general design scheme of system is given, including the creation of infrared scene model, overall control, optical-mechanical structure design and image registration. By analyzing and comparing the past designs, we discuss the arrangement of optical engine framework in the system. According to the main content of working principle and overall design, we summarize each key techniques in the system.

Comparative study on the performance of textural image features for active contour segmentation.

Science.gov (United States)

Moraru, Luminita; Moldovanu, Simona

2012-07-01

We present a computerized method for the semi-automatic detection of contours in ultrasound images. The novelty of our study is the introduction of a fast and efficient image function relating to parametric active contour models. This new function is a combination of the gray-level information and first-order statistical features, called standard deviation parameters. In a comprehensive study, the developed algorithm and the efficiency of segmentation were first tested for synthetic images. Tests were also performed on breast and liver ultrasound images. The proposed method was compared with the watershed approach to show its efficiency. The performance of the segmentation was estimated using the area error rate. Using the standard deviation textural feature and a 5×5 kernel, our curve evolution was able to produce results close to the minimal area error rate (namely 8.88% for breast images and 10.82% for liver images). The image resolution was evaluated using the contrast-to-gradient method. The experiments showed promising segmentation results.

Local Competition-Based Superpixel Segmentation Algorithm in Remote Sensing

Directory of Open Access Journals (Sweden)

Jiayin Liu

2017-06-01

Full Text Available Remote sensing technologies have been widely applied in urban environments’ monitoring, synthesis and modeling. Incorporating spatial information in perceptually coherent regions, superpixel-based approaches can effectively eliminate the “salt and pepper” phenomenon which is common in pixel-wise approaches. Compared with fixed-size windows, superpixels have adaptive sizes and shapes for different spatial structures. Moreover, superpixel-based algorithms can significantly improve computational efficiency owing to the greatly reduced number of image primitives. Hence, the superpixel algorithm, as a preprocessing technique, is more and more popularly used in remote sensing and many other fields. In this paper, we propose a superpixel segmentation algorithm called Superpixel Segmentation with Local Competition (SSLC, which utilizes a local competition mechanism to construct energy terms and label pixels. The local competition mechanism leads to energy terms locality and relativity, and thus, the proposed algorithm is less sensitive to the diversity of image content and scene layout. Consequently, SSLC could achieve consistent performance in different image regions. In addition, the Probability Density Function (PDF, which is estimated by Kernel Density Estimation (KDE with the Gaussian kernel, is introduced to describe the color distribution of superpixels as a more sophisticated and accurate measure. To reduce computational complexity, a boundary optimization framework is introduced to only handle boundary pixels instead of the whole image. We conduct experiments to benchmark the proposed algorithm with the other state-of-the-art ones on the Berkeley Segmentation Dataset (BSD and remote sensing images. Results demonstrate that the SSLC algorithm yields the best overall performance, while the computation time-efficiency is still competitive.

Cross-cultural differences in item and background memory: examining the influence of emotional intensity and scene congruency.

Science.gov (United States)

Mickley Steinmetz, Katherine R; Sturkie, Charlee M; Rochester, Nina M; Liu, Xiaodong; Gutchess, Angela H

2018-07-01

After viewing a scene, individuals differ in what they prioritise and remember. Culture may be one factor that influences scene memory, as Westerners have been shown to be more item-focused than Easterners (see Masuda, T., & Nisbett, R. E. (2001). Attending holistically versus analytically: Comparing the context sensitivity of Japanese and Americans. Journal of Personality and Social Psychology, 81, 922-934). However, cultures may differ in their sensitivity to scene incongruences and emotion processing, which may account for cross-cultural differences in scene memory. The current study uses hierarchical linear modeling (HLM) to examine scene memory while controlling for scene congruency and the perceived emotional intensity of the images. American and East Asian participants encoded pictures that included a positive, negative, or neutral item placed on a neutral background. After a 20-min delay, participants were shown the item and background separately along with similar and new items and backgrounds to assess memory specificity. Results indicated that even when congruency and emotional intensity were controlled, there was evidence that Americans had better item memory than East Asians. Incongruent scenes were better remembered than congruent scenes. However, this effect did not differ by culture. This suggests that Americans' item focus may result in memory changes that are robust despite variations in scene congruency and perceived emotion.

Wall grid structure for interior scene synthesis

KAUST Repository

Xu, Wenzhuo; Wang, Bin; Yan, Dongming

2015-01-01

We present a system for automatically synthesizing a diverse set of semantically valid, and well-arranged 3D interior scenes for a given empty room shape. Unlike existing work on layout synthesis, that typically knows potentially needed 3D models

Popular music scenes and aging bodies.

Science.gov (United States)

Bennett, Andy

2018-06-01

During the last two decades there has been increasing interest in the phenomenon of the aging popular music audience (Bennett & Hodkinson, 2012). Although the specter of the aging fan is by no means new, the notion of, for example, the aging rocker or the aging punk has attracted significant sociological attention, not least of all because of what this says about the shifting socio-cultural significance of rock and punk and similar genres - which at the time of their emergence were inextricably tied to youth and vociferously marketed as "youth musics". As such, initial interpretations of aging music fans tended to paint a somewhat negative picture, suggesting a sense in which such fans were cultural misfits (Ross, 1994). In more recent times, however, work informed by cultural aging perspectives has begun to consider how so-called "youth cultural" identities may in fact provide the basis of more stable and evolving identities over the life course (Bennett, 2013). Starting from this position, the purpose of this article is to critically examine how aging members of popular music scenes might be recast as a salient example of the more pluralistic fashion in which aging is anticipated, managed and articulated in contemporary social settings. The article then branches out to consider two ways that aging members of music scenes continue their scene involvement. The first focuses on evolving a series of discourses that legitimately position them as aging bodies in cultural spaces that also continue to be inhabited by significant numbers of people in their teens, twenties and thirties. The second sees aging fans taking advantage of new opportunities for consuming live music including winery concerts and dinner and show events. Copyright © 2018 Elsevier Inc. All rights reserved.

Plant synthetic biology.

Science.gov (United States)

Liu, Wusheng; Stewart, C Neal

2015-05-01

Plant synthetic biology is an emerging field that combines engineering principles with plant biology toward the design and production of new devices. This emerging field should play an important role in future agriculture for traditional crop improvement, but also in enabling novel bioproduction in plants. In this review we discuss the design cycles of synthetic biology as well as key engineering principles, genetic parts, and computational tools that can be utilized in plant synthetic biology. Some pioneering examples are offered as a demonstration of how synthetic biology can be used to modify plants for specific purposes. These include synthetic sensors, synthetic metabolic pathways, and synthetic genomes. We also speculate about the future of synthetic biology of plants. Copyright © 2015 Elsevier Ltd. All rights reserved.

Three fatalities associated with the synthetic cannabinoids 5F-ADB, 5F-PB-22, and AB-CHMINACA.

Science.gov (United States)

Angerer, V; Jacobi, S; Franz, F; Auwärter, V; Pietsch, J

2017-12-01

The use of synthetic cannabinoids (SC) has been widespread in certain groups of drug users for many years. In the scientific literature many intoxication cases and a number of fatalities after the use of synthetic cannabinoids were reported. In this paper three death cases are described with involvement of the synthetic cannabinoids 5F-PB-22, AB-CHMINACA, and 5F-ADB. The three cases occurred in the eastern region of Germany, which is known as a region of high methamphetamine abuse. All decedents were male, between 25 and 41 years old, and had a known history of drug use. Femoral blood concentrations of the synthetic cannabinoids were measured using a validated LC-MS/MS method. The concentration of 5F-PB-22 in the first case was 0.37ng/mL, the concentration of AB-CHMINACA in the second case was approximately 4.1ng/mL (extrapolated) and the 5F-ADB concentration in the third case was 0.38ng/mL. Compared to other published cases the concentrations in the here presented cases seem to be in the lower range. However, taking into account the scene of death, the results of the forensic autopsy and the full toxicological analysis, the deaths can be explained as a direct consequence of consumption of synthetic cannabinoids, although in case one and two relevant amounts of ethanol were found, and in case three trimipramine and olanzapine were present in non-toxic concentrations. It has to be noted that concentrations of synthetic cannabinoids in femoral blood cannot directly be judged as toxic or lethal due to the possibility of postmortem redistribution and the development of tolerance after frequent use. Therefore, all available information has to be considered carefully before stating SC use as the cause of death. Copyright © 2017 Elsevier B.V. All rights reserved.

Eye Movements when Looking at Unusual/Weird Scenes: Are There Cultural Differences?

Science.gov (United States)

Rayner, Keith; Castelhano, Monica S.; Yang, Jinmian

2009-01-01

Recent studies have suggested that eye movement patterns while viewing scenes differ for people from different cultural backgrounds and that these differences in how scenes are viewed are due to differences in the prioritization of information (background or foreground). The current study examined whether there are cultural differences in how…

The elephant in the room: inconsistency in scene viewing and representation

OpenAIRE

Spotorno, Sara; Tatler, Benjamin W.

2017-01-01

We examined the extent to which semantic informativeness, consistency with expectations and perceptual salience contribute to object prioritization in scene viewing and representation. In scene viewing (Experiments 1–2), semantic guidance overshadowed perceptual guidance in determining fixation order, with the greatest prioritization for objects that were diagnostic of the scene’s depicted event. Perceptual properties affected selection of consistent objects (regardless of their informativene...

Scene grammar shapes the way we interact with objects, strengthens memories, and speeds search.

Science.gov (United States)

Draschkow, Dejan; Võ, Melissa L-H

2017-11-28

Predictions of environmental rules (here referred to as "scene grammar") can come in different forms: seeing a toilet in a living room would violate semantic predictions, while finding a toilet brush next to the toothpaste would violate syntactic predictions. The existence of such predictions has usually been investigated by showing observers images containing such grammatical violations. Conversely, the generative process of creating an environment according to one's scene grammar and its effects on behavior and memory has received little attention. In a virtual reality paradigm, we either instructed participants to arrange objects according to their scene grammar or against it. Subsequently, participants' memory for the arrangements was probed using a surprise recall (Exp1), or repeated search (Exp2) task. As a result, participants' construction behavior showed strategic use of larger, static objects to anchor the location of smaller objects which are generally the goals of everyday actions. Further analysis of this scene construction data revealed possible commonalities between the rules governing word usage in language and object usage in naturalistic environments. Taken together, we revealed some of the building blocks of scene grammar necessary for efficient behavior, which differentially influence how we interact with objects and what we remember about scenes.

Z-depth integration: a new technique for manipulating z-depth properties in composited scenes

Science.gov (United States)

Steckel, Kayla; Whittinghill, David

2014-02-01

This paper presents a new technique in the production pipeline of asset creation for virtual environments called Z-Depth Integration (ZeDI). ZeDI is intended to reduce the time required to place elements at the appropriate z-depth within a scene. Though ZeDI is intended for use primarily in two-dimensional scene composition, depth-dependent "flat" animated objects are often critical elements of augmented and virtual reality applications (AR/VR). ZeDI is derived from "deep image compositing", a capacity implemented within the OpenEXR file format. In order to trick the human eye into perceiving overlapping scene elements as being in front of or behind one another, the developer must manually manipulate which pixels of an element are visible in relation to other objects embedded within the environment's image sequence. ZeDI improves on this process by providing a means for interacting with procedurally extracted z-depth data from a virtual environment scene. By streamlining the process of defining objects' depth characteristics, it is expected that the time and energy required for developers to create compelling AR/VR scenes will be reduced. In the proof of concept presented in this manuscript, ZeDI is implemented for pre-rendered virtual scene construction via an AfterEffects software plug-in.

Special effects used in creating 3D animated scenes-part 1

Science.gov (United States)

Avramescu, A. M.

2015-11-01

In present, with the help of computer, we can create special effects that look so real that we almost don't perceive them as being different. These special effects are somehow hard to differentiate from the real elements like those on the screen. With the increasingly accesible 3D field that has more and more areas of application, the 3D technology goes easily from architecture to product designing. Real like 3D animations are used as means of learning, for multimedia presentations of big global corporations, for special effects and even for virtual actors in movies. Technology, as part of the movie art, is considered a prerequisite but the cinematography is the first art that had to wait for the correct intersection of technological development, innovation and human vision in order to attain full achievement. Increasingly more often, the majority of industries is using 3D sequences (three dimensional). 3D represented graphics, commercials and special effects from movies are all designed in 3D. The key for attaining real visual effects is to successfully combine various distinct elements: characters, objects, images and video scenes; like all these elements represent a whole that works in perfect harmony. This article aims to exhibit a game design from these days. Considering the advanced technology and futuristic vision of designers, nowadays we have different and multifarious game models. Special effects are decisively contributing in the creation of a realistic three-dimensional scene. These effects are essential for transmitting the emotional state of the scene. Creating the special effects is a work of finesse in order to achieve high quality scenes. Special effects can be used to get the attention of the onlooker on an object from a scene. Out of the conducted study, the best-selling game of the year 2010 was Call of Duty: Modern Warfare 2. This way, the article aims for the presented scene to be similar with many locations from this type of games, more

Contribution to the tracking and the 3D reconstruction of scenes composed of torus from image sequences a acquired by a moving camera; Contribution au suivi et a la reconstruction de scenes constituees d`objet toriques a partir de sequences d`images acquises par une camera mobile

Energy Technology Data Exchange (ETDEWEB)

Naudet, S

1997-01-31

The three-dimensional perception of the environment is often necessary for a robot to correctly perform its tasks. One solution, based on the dynamic vision, consists in analysing time-varying monocular images to estimate the spatial geometry of the scene. This thesis deals with the reconstruction of torus by dynamic vision. Though this object class is restrictive, it enables to tackle the problem of reconstruction of bent pipes usually encountered in industrial environments. The proposed method is based on the evolution of apparent contours of objects in the sequence. Using the expression of torus limb boundaries, it is possible to recursively estimate the object three-dimensional parameters by minimising the error between the predicted projected contours and the image contours. This process, which is performed by a Kalman filter, does not need a precise knowledge of the camera displacement or any matching of the tow limbs belonging to the same object. To complete this work, temporal tracking of objects which deals with occlusion situations is proposed. The approach consists in modeling and interpreting the apparent motion of objects in the successive images. The motion interpretation, based on a simplified representation of the scene, allows to recover pertinent three-dimensional information which is used to manage occlusion situations. Experiments, on synthetic and real images, proves he validity of the tracking and the reconstruction processes. (author) 127 refs.

Status of the segment interconnect, cable segment ancillary logic, and the cable segment hybrid driver projects

International Nuclear Information System (INIS)

Swoboda, C.; Barsotti, E.; Chappa, S.; Downing, R.; Goeransson, G.; Lensy, D.; Moore, G.; Rotolo, C.; Urish, J.

1985-01-01

The FASTBUS Segment Interconnect (SI) provides a communication path between two otherwise independent, asynchronous bus segments. In particular, the Segment Interconnect links a backplane crate segment to a cable segment. All standard FASTBUS address and data transactions can be passed through the SI or any number of SIs and segments in a path. Thus systems of arbitrary connection complexity can be formed, allowing simultaneous independent processing, yet still permitting devices associated with one segment to be accessed from others. The model S1 Segment Interconnect and the Cable Segment Ancillary Logic covered in this report comply with all the mandatory features stated in the FASTBUS specification document DOE/ER-0189. A block diagram of the SI is shown

Differential physiological and behavioral cues observed in individuals smoking botanical marijuana versus synthetic cannabinoid drugs.

Science.gov (United States)

Chase, Peter B; Hawkins, Jeff; Mosier, Jarrod; Jimenez, Ernest; Boesen, Keith; Logan, Barry K; Walter, Frank G

2016-01-01

Synthetic cannabinoid use has increased in many states, and medicinal and/or recreational marijuana use has been legalized in some states. These changes present challenges to law enforcement drug recognition experts (DREs) who determine whether drivers are impaired by synthetic cannabinoids or marijuana, as well as to clinical toxicologists who care for patients with complications from synthetic cannabinoids and marijuana. Our goal was to compare what effects synthetic cannabinoids and marijuana had on performance and behavior, including driving impairment, by reviewing records generated by law enforcement DREs who evaluated motorists arrested for impaired driving. Data were from a retrospective, convenience sample of de-identified arrest reports from impaired drivers suspected of using synthetic cannabinoids (n = 100) or marijuana (n = 33). Inclusion criteria were arrested drivers who admitted to using either synthetic cannabinoids or marijuana, or who possessed either synthetic cannabinoids or marijuana; who also had a DRE evaluation at the scene; and whose blood screens were negative for alcohol and other drugs. Exclusion criteria were impaired drivers arrested with other intoxicants found in their drug or alcohol blood screens. Blood samples were analyzed for 20 popular synthetic cannabinoids by using liquid chromatography-tandem mass spectrometry. Delta-9-tetrahydrocannabinol (THC) and THC-COOH were quantified by gas chromatography-mass spectrometry. Statistical significance was determined by using Fisher's exact test or Student's t-test, where appropriate, to compare the frequency of characteristics of those in the synthetic cannabinoid group versus those in the marijuana group. 16 synthetic cannabinoid and 25 marijuana records met selection criteria; the drivers of these records were arrested for moving violations. Median age for the synthetic cannabinoid group (n = 16, 15 males) was 20 years (IQR 19-23 years). Median age for the marijuana group (n = 25, 21

Non-uniform crosstalk reduction for dynamic scenes

NARCIS (Netherlands)

Smit, F.A.; Liere, van R.; Fröhlich, B.

2007-01-01

Stereo displays suffer from crosstalk, an effect that reduces or even inhibits the viewer's ability to correctly perceive depth. Previous work on software crosstalk reduction focussed on the preprocessing of static scenes which are viewed from a fixed viewpoint. However, in virtual environments

Implicit Active Contours Driven by Local and Global Image Fitting Energy for Image Segmentation and Target Localization

Directory of Open Access Journals (Sweden)

Xiaosheng Yu

2013-01-01

Full Text Available We propose a novel active contour model in a variational level set formulation for image segmentation and target localization. We combine a local image fitting term and a global image fitting term to drive the contour evolution. Our model can efficiently segment the images with intensity inhomogeneity with the contour starting anywhere in the image. In its numerical implementation, an efficient numerical schema is used to ensure sufficient numerical accuracy. We validated its effectiveness in numerous synthetic images and real images, and the promising experimental results show its advantages in terms of accuracy, efficiency, and robustness.

Multimodal computational attention for scene understanding and robotics

CERN Document Server

Schauerte, Boris

2016-01-01

This book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated. .

Robust generative asymmetric GMM for brain MR image segmentation.

Science.gov (United States)

Ji, Zexuan; Xia, Yong; Zheng, Yuhui

2017-11-01

Accurate segmentation of brain tissues from magnetic resonance (MR) images based on the unsupervised statistical models such as Gaussian mixture model (GMM) has been widely studied during last decades. However, most GMM based segmentation methods suffer from limited accuracy due to the influences of noise and intensity inhomogeneity in brain MR images. To further improve the accuracy for brain MR image segmentation, this paper presents a Robust Generative Asymmetric GMM (RGAGMM) for simultaneous brain MR image segmentation and intensity inhomogeneity correction. First, we develop an asymmetric distribution to fit the data shapes, and thus construct a spatial constrained asymmetric model. Then, we incorporate two pseudo-likelihood quantities and bias field estimation into the model's log-likelihood, aiming to exploit the neighboring priors of within-cluster and between-cluster and to alleviate the impact of intensity inhomogeneity, respectively. Finally, an expectation maximization algorithm is derived to iteratively maximize the approximation of the data log-likelihood function to overcome the intensity inhomogeneity in the image and segment the brain MR images simultaneously. To demonstrate the performances of the proposed algorithm, we first applied the proposed algorithm to a synthetic brain MR image to show the intermediate illustrations and the estimated distribution of the proposed algorithm. The next group of experiments is carried out in clinical 3T-weighted brain MR images which contain quite serious intensity inhomogeneity and noise. Then we quantitatively compare our algorithm to state-of-the-art segmentation approaches by using Dice coefficient (DC) on benchmark images obtained from IBSR and BrainWeb with different level of noise and intensity inhomogeneity. The comparison results on various brain MR images demonstrate the superior performances of the proposed algorithm in dealing with the noise and intensity inhomogeneity. In this paper, the RGAGMM

Segmentation-based retrospective shading correction in fluorescence microscopy E. coli images for quantitative analysis

Science.gov (United States)

Mai, Fei; Chang, Chunqi; Liu, Wenqing; Xu, Weichao; Hung, Yeung S.

2009-10-01

Due to the inherent imperfections in the imaging process, fluorescence microscopy images often suffer from spurious intensity variations, which is usually referred to as intensity inhomogeneity, intensity non uniformity, shading or bias field. In this paper, a retrospective shading correction method for fluorescence microscopy Escherichia coli (E. Coli) images is proposed based on segmentation result. Segmentation and shading correction are coupled together, so we iteratively correct the shading effects based on segmentation result and refine the segmentation by segmenting the image after shading correction. A fluorescence microscopy E. Coli image can be segmented (based on its intensity value) into two classes: the background and the cells, where the intensity variation within each class is close to zero if there is no shading. Therefore, we make use of this characteristics to correct the shading in each iteration. Shading is mathematically modeled as a multiplicative component and an additive noise component. The additive component is removed by a denoising process, and the multiplicative component is estimated using a fast algorithm to minimize the intra-class intensity variation. We tested our method on synthetic images and real fluorescence E.coli images. It works well not only for visual inspection, but also for numerical evaluation. Our proposed method should be useful for further quantitative analysis especially for protein expression value comparison.

Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior.

Science.gov (United States)

Groen, Iris Ia; Greene, Michelle R; Baldassano, Christopher; Fei-Fei, Li; Beck, Diane M; Baker, Chris I

2018-03-07

Inherent correlations between visual and semantic features in real-world scenes make it difficult to determine how different scene properties contribute to neural representations. Here, we assessed the contributions of multiple properties to scene representation by partitioning the variance explained in human behavioral and brain measurements by three feature models whose inter-correlations were minimized a priori through stimulus preselection. Behavioral assessments of scene similarity reflected unique contributions from a functional feature model indicating potential actions in scenes as well as high-level visual features from a deep neural network (DNN). In contrast, similarity of cortical responses in scene-selective areas was uniquely explained by mid- and high-level DNN features only, while an object label model did not contribute uniquely to either domain. The striking dissociation between functional and DNN features in their contribution to behavioral and brain representations of scenes indicates that scene-selective cortex represents only a subset of behaviorally relevant scene information.

Anticipatory Scene Representation in Preschool Children's Recall and Recognition Memory

Science.gov (United States)

Kreindel, Erica; Intraub, Helene

2017-01-01

Behavioral and neuroscience research on boundary extension (false memory beyond the edges of a view of a scene) has provided new insights into the constructive nature of scene representation, and motivates questions about development. Early research with children (as young as 6-7 years) was consistent with boundary extension, but relied on an…

Quantitative assessment of similarity between randomly acquired characteristics on high quality exemplars and crime scene impressions via analysis of feature size and shape.

Science.gov (United States)

Richetelli, Nicole; Nobel, Madonna; Bodziak, William J; Speir, Jacqueline A

2017-01-01

were consistently detected for three of the five metrics (modified phase only correlation, Euclidean distance, and Hausdorff distance). Conversely, a single metric (the matched filter) expressed the least dependence between score and both shape and size. Moreover, for all crime-scene-like RACs with coincidental association in position, the matched filter produced the greatest discrimination potential in sorting known matches and known non-matches. Despite this demonstrated success, numerical metrics of similarity are not without limitations, and the remainder of this work provides commentary on the difficulties associated with using objective metrics when faced with segmentation, incomplete information, and low signal-to-noise ratios. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Object Attention Patches for Text Detection and Recognition in Scene Images using SIFT

NARCIS (Netherlands)

Sriman, Bowornrat; Schomaker, Lambertus; De Marsico, Maria; Figueiredo, Mário; Fred, Ana

2015-01-01

Natural urban scene images contain many problems for character recognition such as luminance noise, varying font styles or cluttered backgrounds. Detecting and recognizing text in a natural scene is a difficult problem. Several techniques have been proposed to overcome these problems. These are,

Segmentation of dermatoscopic images by frequency domain filtering and k-means clustering algorithms.

Science.gov (United States)

Rajab, Maher I

2011-11-01

Since the introduction of epiluminescence microscopy (ELM), image analysis tools have been extended to the field of dermatology, in an attempt to algorithmically reproduce clinical evaluation. Accurate image segmentation of skin lesions is one of the key steps for useful, early and non-invasive diagnosis of coetaneous melanomas. This paper proposes two image segmentation algorithms based on frequency domain processing and k-means clustering/fuzzy k-means clustering. The two methods are capable of segmenting and extracting the true border that reveals the global structure irregularity (indentations and protrusions), which may suggest excessive cell growth or regression of a melanoma. As a pre-processing step, Fourier low-pass filtering is applied to reduce the surrounding noise in a skin lesion image. A quantitative comparison of the techniques is enabled by the use of synthetic skin lesion images that model lesions covered with hair to which Gaussian noise is added. The proposed techniques are also compared with an established optimal-based thresholding skin-segmentation method. It is demonstrated that for lesions with a range of different border irregularity properties, the k-means clustering and fuzzy k-means clustering segmentation methods provide the best performance over a range of signal to noise ratios. The proposed segmentation techniques are also demonstrated to have similar performance when tested on real skin lesions representing high-resolution ELM images. This study suggests that the segmentation results obtained using a combination of low-pass frequency filtering and k-means or fuzzy k-means clustering are superior to the result that would be obtained by using k-means or fuzzy k-means clustering segmentation methods alone. © 2011 John Wiley & Sons A/S.

Oxytocin increases amygdala reactivity to threatening scenes in females.

Science.gov (United States)

Lischke, Alexander; Gamer, Matthias; Berger, Christoph; Grossmann, Annette; Hauenstein, Karlheinz; Heinrichs, Markus; Herpertz, Sabine C; Domes, Gregor

2012-09-01

The neuropeptide oxytocin (OT) is well known for its profound effects on social behavior, which appear to be mediated by an OT-dependent modulation of amygdala activity in the context of social stimuli. In humans, OT decreases amygdala reactivity to threatening faces in males, but enhances amygdala reactivity to similar faces in females, suggesting sex-specific differences in OT-dependent threat-processing. To further explore whether OT generally enhances amygdala-dependent threat-processing in females, we used functional magnetic resonance imaging (fMRI) in a randomized within-subject crossover design to measure amygdala activity in response to threatening and non-threatening scenes in 14 females following intranasal administration of OT or placebo. Participants' eye movements were recorded to investigate whether an OT-dependent modulation of amygdala activity is accompanied by enhanced exploration of salient scene features. Although OT had no effect on participants' gazing behavior, it increased amygdala reactivity to scenes depicting social and non-social threat. In females, OT may, thus, enhance the detection of threatening stimuli in the environment, potentially by interacting with gonadal steroids, such as progesterone and estrogen. Copyright © 2012 Elsevier Ltd. All rights reserved.

Synthetic Cannabinoids

Directory of Open Access Journals (Sweden)

Aslihan Okan Ibiloglu

2017-09-01

Full Text Available Synthetic cannabinoids which is a subgroup of cannabinoids are commonly used for recreational drug use throughout the whole world. Although both marijuana and synthetic cannabinoids stimulate the same receptors, cannabinoid receptor 1 (CB1 and cannabinoid receptor 2 (CB2, studies have shown that synthetic cannabinoids are much more potent than marijuana. The longer use of synthetic cannabinoids can cause severe physical and psychological symptoms that might even result in death, similar to many known illicit drugs. Main treatment options mostly involve symptom management and supportive care. The aim of this article is to discuss clinical and pharmacological properties of the increasingly used synthetic cannabinoids. [Psikiyatride Guncel Yaklasimlar - Current Approaches in Psychiatry 2017; 9(3.000: 317-328

A Variational Level Set Model Combined with FCMS for Image Clustering Segmentation

Directory of Open Access Journals (Sweden)

Liming Tang

2014-01-01

Full Text Available The fuzzy C means clustering algorithm with spatial constraint (FCMS is effective for image segmentation. However, it lacks essential smoothing constraints to the cluster boundaries and enough robustness to the noise. Samson et al. proposed a variational level set model for image clustering segmentation, which can get the smooth cluster boundaries and closed cluster regions due to the use of level set scheme. However it is very sensitive to the noise since it is actually a hard C means clustering model. In this paper, based on Samson’s work, we propose a new variational level set model combined with FCMS for image clustering segmentation. Compared with FCMS clustering, the proposed model can get smooth cluster boundaries and closed cluster regions due to the use of level set scheme. In addition, a block-based energy is incorporated into the energy functional, which enables the proposed model to be more robust to the noise than FCMS clustering and Samson’s model. Some experiments on the synthetic and real images are performed to assess the performance of the proposed model. Compared with some classical image segmentation models, the proposed model has a better performance for the images contaminated by different noise levels.

Unsupervised motion-based object segmentation refined by color

Science.gov (United States)

Piek, Matthijs C.; Braspenning, Ralph; Varekamp, Chris

2003-06-01

For various applications, such as data compression, structure from motion, medical imaging and video enhancement, there is a need for an algorithm that divides video sequences into independently moving objects. Because our focus is on video enhancement and structure from motion for consumer electronics, we strive for a low complexity solution. For still images, several approaches exist based on colour, but these lack in both speed and segmentation quality. For instance, colour-based watershed algorithms produce a so-called oversegmentation with many segments covering each single physical object. Other colour segmentation approaches exist which somehow limit the number of segments to reduce this oversegmentation problem. However, this often results in inaccurate edges or even missed objects. Most likely, colour is an inherently insufficient cue for real world object segmentation, because real world objects can display complex combinations of colours. For video sequences, however, an additional cue is available, namely the motion of objects. When different objects in a scene have different motion, the motion cue alone is often enough to reliably distinguish objects from one another and the background. However, because of the lack of sufficient resolution of efficient motion estimators, like the 3DRS block matcher, the resulting segmentation is not at pixel resolution, but at block resolution. Existing pixel resolution motion estimators are more sensitive to noise, suffer more from aperture problems or have less correspondence to the true motion of objects when compared to block-based approaches or are too computationally expensive. From its tendency to oversegmentation it is apparent that colour segmentation is particularly effective near edges of homogeneously coloured areas. On the other hand, block-based true motion estimation is particularly effective in heterogeneous areas, because heterogeneous areas improve the chance a block is unique and thus decrease the

A JOINT FRAMEWORK FOR 4D SEGMENTATION AND ESTIMATION OF SMOOTH TEMPORAL APPEARANCE CHANGES.

Science.gov (United States)

Gao, Yang; Prastawa, Marcel; Styner, Martin; Piven, Joseph; Gerig, Guido

2014-04-01

Medical imaging studies increasingly use longitudinal images of individual subjects in order to follow-up changes due to development, degeneration, disease progression or efficacy of therapeutic intervention. Repeated image data of individuals are highly correlated, and the strong causality of information over time lead to the development of procedures for joint segmentation of the series of scans, called 4D segmentation. A main aim was improved consistency of quantitative analysis, most often solved via patient-specific atlases. Challenging open problems are contrast changes and occurance of subclasses within tissue as observed in multimodal MRI of infant development, neurodegeneration and disease. This paper proposes a new 4D segmentation framework that enforces continuous dynamic changes of tissue contrast patterns over time as observed in such data. Moreover, our model includes the capability to segment different contrast patterns within a specific tissue class, for example as seen in myelinated and unmyelinated white matter regions in early brain development. Proof of concept is shown with validation on synthetic image data and with 4D segmentation of longitudinal, multimodal pediatric MRI taken at 6, 12 and 24 months of age, but the methodology is generic w.r.t. different application domains using serial imaging.

Guiding automated left ventricular chamber segmentation in cardiac imaging using the concept of conserved myocardial volume.

Science.gov (United States)

Garson, Christopher D; Li, Bing; Acton, Scott T; Hossack, John A

2008-06-01

The active surface technique using gradient vector flow allows semi-automated segmentation of ventricular borders. The accuracy of the algorithm depends on the optimal selection of several key parameters. We investigated the use of conservation of myocardial volume for quantitative assessment of each of these parameters using synthetic and in vivo data. We predicted that for a given set of model parameters, strong conservation of volume would correlate with accurate segmentation. The metric was most useful when applied to the gradient vector field weighting and temporal step-size parameters, but less effective in guiding an optimal choice of the active surface tension and rigidity parameters.

Face, Body, and Center of Gravity Mediate Person Detection in Natural Scenes

Science.gov (United States)

Bindemann, Markus; Scheepers, Christoph; Ferguson, Heather J.; Burton, A. Mike

2010-01-01

Person detection is an important prerequisite of social interaction, but is not well understood. Following suggestions that people in the visual field can capture a viewer's attention, this study examines the role of the face and the body for person detection in natural scenes. We observed that viewers tend first to look at the center of a scene,…

Segmented block copolymers with monodisperse aramide end-segments

NARCIS (Netherlands)

Araichimani, A.; Gaymans, R.J.

2008-01-01

Segmented block copolymers were synthesized using monodisperse diaramide (TT) as hard segments and PTMO with a molecular weight of 2 900 g · mol-1 as soft segments. The aramide: PTMO segment ratio was increased from 1:1 to 2:1 thereby changing the structure from a high molecular weight multi-block

Virtual Relighting of a Virtualized Scene by Estimating Surface Reflectance Properties

OpenAIRE

福富, 弘敦; 町田, 貴史; 横矢, 直和

2011-01-01

In mixed reality that merges real and virtual worlds, it is required to interactively manipulate the illumination conditions in a virtualized space. In general, specular reflections in a scene make it difficult to interactively manipulate the illumination conditions. Our goal is to provide an opportunity to simulate the original scene, including diffuse and specular relfections, with novel viewpoints and illumination conditions. Thus, we propose a new method for estimating diffuse and specula...

Segmentation of consumer's markets and evaluation of market's segments

OpenAIRE

ŠVECOVÁ, Iveta

2013-01-01

The goal of this bachelor thesis was to explain a possibly segmentation of consumer´s markets for a chosen company, and to present a suitable goods offer, so it would be suitable to the needs of selected segments. The work is divided into theoretical and practical part. First part describes marketing, segmentation, segmentation of consumer's markets, consumer's market, market's segments a other terms. Second part describes an evaluation of questionnaire survey, discovering of market's segment...

Efficient 3D scene modeling and mosaicing

CERN Document Server

Nicosevici, Tudor

2013-01-01

This book proposes a complete pipeline for monocular (single camera) based 3D mapping of terrestrial and underwater environments. The aim is to provide a solution to large-scale scene modeling that is both accurate and efficient. To this end, we have developed a novel Structure from Motion algorithm that increases mapping accuracy by registering camera views directly with the maps. The camera registration uses a dual approach that adapts to the type of environment being mapped.   In order to further increase the accuracy of the resulting maps, a new method is presented, allowing detection of images corresponding to the same scene region (crossovers). Crossovers then used in conjunction with global alignment methods in order to highly reduce estimation errors, especially when mapping large areas. Our method is based on Visual Bag of Words paradigm (BoW), offering a more efficient and simpler solution by eliminating the training stage, generally required by state of the art BoW algorithms.   Also, towards dev...

PVC-based synthetic leather to provide more comfortable and sustainable vehicles

Science.gov (United States)

Maia, I.; Santos, J.; Abreu, MJ; Miranda, T.; Carneiro, N.; Soares, GMB

2017-10-01

Consumers are increasingly demanding the interior of cars to be comfortable even in the case of more economic commercial segments. Thus, the development of materials with thermoregulation properties has assumed renewed interest for these particular applications. An attempt has been made to prepare a multilayer PVC-based synthetic leather with paraffinic PCMs to be applied on a car seat. The thermal behaviour of the material was analysed using Alambeta apparatus, a thermo-camera and a thermal manikin. The results obtained show that the synthetic leather with incorporated PCMs gives cooler feeling and has higher reaction times regarding environmental temperature variations than the material without PCMs incorporation. Globally, the new designed material allowed greater thermal comfort to the cars´ inhabitants. In addition, the material quality was evaluated according to the standard of the customer, BMW 9,210,275; Edition / Version 4, 2010-10-01 revealing that the material meets all the requirements under test, except for the performance in terms of flexibility.

[From synthetic biology to synthetic humankind].

Science.gov (United States)

Nouvel, Pascal

2015-01-01

In this paper, we propose an historical survey of the expression "synthetic biology" in order to identify its main philosophical components. The result of the analysis is then used to investigate the meaning of the notion of "synthetic man". It is shown that both notions share a common philosophical background that can be summed up by the short but meaningful assertion: "biology is technology". The analysis allows us to distinguish two notions that are often confused in transhumanist literature: the notion of synthetic man and the notion of renewed man. The consequences of this crucial distinction are discussed. Copyright © 2015 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Surface-illuminant ambiguity and color constancy: effects of scene complexity and depth cues.

Science.gov (United States)

Kraft, James M; Maloney, Shannon I; Brainard, David H

2002-01-01

Two experiments were conducted to study how scene complexity and cues to depth affect human color constancy. Specifically, two levels of scene complexity were compared. The low-complexity scene contained two walls with the same surface reflectance and a test patch which provided no information about the illuminant. In addition to the surfaces visible in the low-complexity scene, the high-complexity scene contained two rectangular solid objects and 24 paper samples with diverse surface reflectances. Observers viewed illuminated objects in an experimental chamber and adjusted the test patch until it appeared achromatic. Achromatic settings made tinder two different illuminants were used to compute an index that quantified the degree of constancy. Two experiments were conducted: one in which observers viewed the stimuli directly, and one in which they viewed the scenes through an optical system that reduced cues to depth. In each experiment, constancy was assessed for two conditions. In the valid-cue condition, many cues provided valid information about the illuminant change. In the invalid-cue condition, some image cues provided invalid information. Four broad conclusions are drawn from the data: (a) constancy is generally better in the valid-cue condition than in the invalid-cue condition: (b) for the stimulus configuration used, increasing image complexity has little effect in the valid-cue condition but leads to increased constancy in the invalid-cue condition; (c) for the stimulus configuration used, reducing cues to depth has little effect for either constancy condition: and (d) there is moderate individual variation in the degree of constancy exhibited, particularly in the degree to which the complexity manipulation affects performance.

Fast Binary Coding for the Scene Classification of High-Resolution Remote Sensing Imagery

Directory of Open Access Journals (Sweden)

Fan Hu

2016-06-01

Full Text Available Scene classification of high-resolution remote sensing (HRRS imagery is an important task in the intelligent processing of remote sensing images and has attracted much attention in recent years. Although the existing scene classification methods, e.g., the bag-of-words (BOW model and its variants, can achieve acceptable performance, these approaches strongly rely on the extraction of local features and the complicated coding strategy, which are usually time consuming and demand much expert effort. In this paper, we propose a fast binary coding (FBC method, to effectively generate efficient discriminative scene representations of HRRS images. The main idea is inspired by the unsupervised feature learning technique and the binary feature descriptions. More precisely, equipped with the unsupervised feature learning technique, we first learn a set of optimal “filters” from large quantities of randomly-sampled image patches and then obtain feature maps by convolving the image scene with the learned filters. After binarizing the feature maps, we perform a simple hashing step to convert the binary-valued feature map to the integer-valued feature map. Finally, statistical histograms computed on the integer-valued feature map are used as global feature representations of the scenes of HRRS images, similar to the conventional BOW model. The analysis of the algorithm complexity and experiments on HRRS image datasets demonstrate that, in contrast with existing scene classification approaches, the proposed FBC has much faster computational speed and achieves comparable classification performance. In addition, we also propose two extensions to FBC, i.e., the spatial co-occurrence matrix and different visual saliency maps, for further improving its final classification accuracy.

Effect of Smoking Scenes in Films on Immediate Smoking

Science.gov (United States)

Shmueli, Dikla; Prochaska, Judith J.; Glantz, Stanton A.

2010-01-01

Background The National Cancer Institute has concluded that exposure to smoking in movies causes adolescent smoking and there are similar results for young adults. Purpose This study investigated whether exposure of young adult smokers to images of smoking in films stimulated smoking behavior. Methods 100 cigarette smokers aged 18–25 years were randomly assigned to watch a movie montage composed with or without smoking scenes and paraphernalia followed by a10-minute recess. The outcome was whether or not participants smoked during the recess. Data were collected and analyzed in 2008 and 2009. Results Smokers who watched the smoking scenes were more likely to smoke during the break (OR3.06, 95% CI=1.01, 9.29). In addition to this acute effect of exposure, smokers who had seen more smoking in movies before the day of the experiment were more likely to smoke during the break (OR 6.73; 1.00–45.25 comparing the top to bottom percentiles of exposure) were more likely to smoke during the break. Level of nicotine dependence (OR 1.71; 1.27–2.32 per point on the FTND scale), “contemplation” (OR 9.07; 1.71–47.99) and “precontemplation” (OR 7.30; 1.39–38.36) stages of change, and impulsivity (OR 1.21; 1.03–1.43), were also associated with smoking during the break. Participants who watched the montage with smoking scenes and those with a higher level of nicotine dependence were also more likely to have smoked within 30 minutes after the study. Conclusions There is a direct link between viewing smoking scenes and immediate subsequent smoking behavior. This finding suggests that individuals attempting to limit or quit smoking should be advised to refrain from or reduce their exposure to movies that contain smoking. PMID:20307802

HDR video synthesis for vision systems in dynamic scenes

Science.gov (United States)

Shopovska, Ivana; Jovanov, Ljubomir; Goossens, Bart; Philips, Wilfried

2016-09-01

High dynamic range (HDR) image generation from a number of differently exposed low dynamic range (LDR) images has been extensively explored in the past few decades, and as a result of these efforts a large number of HDR synthesis methods have been proposed. Since HDR images are synthesized by combining well-exposed regions of the input images, one of the main challenges is dealing with camera or object motion. In this paper we propose a method for the synthesis of HDR video from a single camera using multiple, differently exposed video frames, with circularly alternating exposure times. One of the potential applications of the system is in driver assistance systems and autonomous vehicles, involving significant camera and object movement, non- uniform and temporally varying illumination, and the requirement of real-time performance. To achieve these goals simultaneously, we propose a HDR synthesis approach based on weighted averaging of aligned radiance maps. The computational complexity of high-quality optical flow methods for motion compensation is still pro- hibitively high for real-time applications. Instead, we rely on more efficient global projective transformations to solve camera movement, while moving objects are detected by thresholding the differences between the trans- formed and brightness adapted images in the set. To attain temporal consistency of the camera motion in the consecutive HDR frames, the parameters of the perspective transformation are stabilized over time by means of computationally efficient temporal filtering. We evaluated our results on several reference HDR videos, on synthetic scenes, and using 14-bit raw images taken with a standard camera.

Effects of varying presentation time on long-term recognition memory for scenes: Verbatim and gist representations.

Science.gov (United States)

Ahmad, Fahad N; Moscovitch, Morris; Hockley, William E

2017-04-01

Konkle, Brady, Alvarez and Oliva (Psychological Science, 21, 1551-1556, 2010) showed that participants have an exceptional long-term memory (LTM) for photographs of scenes. We examined to what extent participants' exceptional LTM for scenes is determined by presentation time during encoding. In addition, at retrieval, we varied the nature of the lures in a forced-choice recognition task so that they resembled the target in gist (i.e., global or categorical) information, but were distinct in verbatim information (e.g., an "old" beach scene and a similar "new" beach scene; exemplar condition) or vice versa (e.g., a beach scene and a new scene from a novel category; novel condition). In Experiment 1, half of the list of scenes was presented for 1 s, whereas the other half was presented for 4 s. We found lower performance for shorter study presentation time in the exemplar test condition and similar performance for both study presentation times in the novel test condition. In Experiment 2, participants showed similar performance in an exemplar test for which the lure was of a different category but a category that was used at study. In Experiment 3, when presentation time was lowered to 500 ms, recognition accuracy was reduced in both novel and exemplar test conditions. A less detailed memorial representation of the studied scene containing more gist (i.e., meaning) than verbatim (i.e., surface or perceptual details) information is retrieved from LTM after a short compared to a long study presentation time. We conclude that our findings support fuzzy-trace theory.

The Role of Binocular Disparity in Rapid Scene and Pattern Recognition

Directory of Open Access Journals (Sweden)

Matteo Valsecchi

2013-04-01

Full Text Available We investigated the contribution of binocular disparity to the rapid recognition of scenes and simpler spatial patterns using a paradigm combining backward masked stimulus presentation and short-term match-to-sample recognition. First, we showed that binocular disparity did not contribute significantly to the recognition of briefly presented natural and artificial scenes, even when the availability of monocular cues was reduced. Subsequently, using dense random dot stereograms as stimuli, we showed that observers were in principle able to extract spatial patterns defined only by disparity under brief, masked presentations. Comparing our results with the predictions from a cue-summation model, we showed that combining disparity with luminance did not per se disrupt the processing of disparity. Our results suggest that the rapid recognition of scenes is mediated mostly by a monocular comparison of the images, although we can rely on stereo in fast pattern recognition.

Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

Science.gov (United States)

Anwer, Rao Muhammad; Khan, Fahad Shahbaz; van de Weijer, Joost; Molinier, Matthieu; Laaksonen, Jorma

2018-04-01

Designing discriminative powerful texture features robust to realistic imaging conditions is a challenging computer vision problem with many applications, including material recognition and analysis of satellite or aerial imagery. In the past, most texture description approaches were based on dense orderless statistical distribution of local features. However, most recent approaches to texture recognition and remote sensing scene classification are based on Convolutional Neural Networks (CNNs). The de facto practice when learning these CNN models is to use RGB patches as input with training performed on large amounts of labeled data (ImageNet). In this paper, we show that Local Binary Patterns (LBP) encoded CNN models, codenamed TEX-Nets, trained using mapped coded images with explicit LBP based texture information provide complementary information to the standard RGB deep models. Additionally, two deep architectures, namely early and late fusion, are investigated to combine the texture and color information. To the best of our knowledge, we are the first to investigate Binary Patterns encoded CNNs and different deep network fusion architectures for texture recognition and remote sensing scene classification. We perform comprehensive experiments on four texture recognition datasets and four remote sensing scene classification benchmarks: UC-Merced with 21 scene categories, WHU-RS19 with 19 scene classes, RSSCN7 with 7 categories and the recently introduced large scale aerial image dataset (AID) with 30 aerial scene types. We demonstrate that TEX-Nets provide complementary information to standard RGB deep model of the same network architecture. Our late fusion TEX-Net architecture always improves the overall performance compared to the standard RGB network on both recognition problems. Furthermore, our final combination leads to consistent improvement over the state-of-the-art for remote sensing scene classification.

The effects of alcohol intoxication on attention and memory for visual scenes.

Science.gov (United States)

Harvey, Alistair J; Kneller, Wendy; Campbell, Alison C

2013-01-01

This study tests the claim that alcohol intoxication narrows the focus of visual attention on to the more salient features of a visual scene. A group of alcohol intoxicated and sober participants had their eye movements recorded as they encoded a photographic image featuring a central event of either high or low salience. All participants then recalled the details of the image the following day when sober. We sought to determine whether the alcohol group would pay less attention to the peripheral features of the encoded scene than their sober counterparts, whether this effect of attentional narrowing was stronger for the high-salience event than for the low-salience event, and whether it would lead to a corresponding deficit in peripheral recall. Alcohol was found to narrow the focus of foveal attention to the central features of both images but did not facilitate recall from this region. It also reduced the overall amount of information accurately recalled from each scene. These findings demonstrate that the concept of alcohol myopia originally posited to explain the social consequences of intoxication (Steele & Josephs, 1990) may be extended to explain the relative neglect of peripheral information during the processing of visual scenes.

Camera pose estimation for augmented reality in a small indoor dynamic scene

Science.gov (United States)

Frikha, Rawia; Ejbali, Ridha; Zaied, Mourad

2017-09-01

Camera pose estimation remains a challenging task for augmented reality (AR) applications. Simultaneous localization and mapping (SLAM)-based methods are able to estimate the six degrees of freedom camera motion while constructing a map of an unknown environment. However, these methods do not provide any reference for where to insert virtual objects since they do not have any information about scene structure and may fail in cases of occlusion of three-dimensional (3-D) map points or dynamic objects. This paper presents a real-time monocular piece wise planar SLAM method using the planar scene assumption. Using planar structures in the mapping process allows rendering virtual objects in a meaningful way on the one hand and improving the precision of the camera pose and the quality of 3-D reconstruction of the environment by adding constraints on 3-D points and poses in the optimization process on the other hand. We proposed to benefit from the 3-D planes rigidity motion in the tracking process to enhance the system robustness in the case of dynamic scenes. Experimental results show that using a constrained planar scene improves our system accuracy and robustness compared with the classical SLAM systems.

Relationship between Childhood Meal Scenes at Home Remembered by University Students and their Current Personality

OpenAIRE

恩村, 咲希; Onmura, Saki

2013-01-01

This study examines the relationship between childhood meal scenes at home that are remembered by university students and their current personality. The meal scenes are analyzed in terms of companions, conversation content, conversation frequency, atmosphere, and consideration of meals. The scale of the conversation content in childhood meal scenes was prepared on the basis of the results of a preliminary survey. The result showed that a relationship was found between personality traits and c...

Epistemic uncertainty in California-wide synthetic seismicity simulations

Science.gov (United States)

Pollitz, Fred F.

2011-01-01

The generation of seismicity catalogs on synthetic fault networks holds the promise of providing key inputs into probabilistic seismic-hazard analysis, for example, the coefficient of variation, mean recurrence time as a function of magnitude, the probability of fault-to-fault ruptures, and conditional probabilities for foreshock–mainshock triggering. I employ a seismicity simulator that includes the following ingredients: static stress transfer, viscoelastic relaxation of the lower crust and mantle, and vertical stratification of elastic and viscoelastic material properties. A cascade mechanism combined with a simple Coulomb failure criterion is used to determine the initiation, propagation, and termination of synthetic ruptures. It is employed on a 3D fault network provided by Steve Ward (unpublished data, 2009) for the Southern California Earthquake Center (SCEC) Earthquake Simulators Group. This all-California fault network, initially consisting of 8000 patches, each of ∼12 square kilometers in size, has been rediscretized into Graphic patches, each of ∼1 square kilometer in size, in order to simulate the evolution of California seismicity and crustal stress at magnitude M∼5–8. Resulting synthetic seismicity catalogs spanning 30,000 yr and about one-half million events are evaluated with magnitude-frequency and magnitude-area statistics. For a priori choices of fault-slip rates and mean stress drops, I explore the sensitivity of various constructs on input parameters, particularly mantle viscosity. Slip maps obtained for the southern San Andreas fault show that the ability of segment boundaries to inhibit slip across the boundaries (e.g., to prevent multisegment ruptures) is systematically affected by mantle viscosity.

Integration of an open interface PC scene generator using COTS DVI converter hardware

Science.gov (United States)

Nordland, Todd; Lyles, Patrick; Schultz, Bret

2006-05-01

Commercial-Off-The-Shelf (COTS) personal computer (PC) hardware is increasingly capable of computing high dynamic range (HDR) scenes for military sensor testing at high frame rates. New electro-optical and infrared (EO/IR) scene projectors feature electrical interfaces that can accept the DVI output of these PC systems. However, military Hardware-in-the-loop (HWIL) facilities such as those at the US Army Aviation and Missile Research Development and Engineering Center (AMRDEC) utilize a sizeable inventory of existing projection systems that were designed to use the Silicon Graphics Incorporated (SGI) digital video port (DVP, also known as DVP2 or DD02) interface. To mate the new DVI-based scene generation systems to these legacy projection systems, CG2 Inc., a Quantum3D Company (CG2), has developed a DVI-to-DVP converter called Delta DVP. This device takes progressive scan DVI input, converts it to digital parallel data, and combines and routes color components to derive a 16-bit wide luminance channel replicated on a DVP output interface. The HWIL Functional Area of AMRDEC has developed a suite of modular software to perform deterministic real-time, wave band-specific rendering of sensor scenes, leveraging the features of commodity graphics hardware and open source software. Together, these technologies enable sensor simulation and test facilities to integrate scene generation and projection components with diverse pedigrees.

History of Reading Struggles Linked to Enhanced Learning in Low Spatial Frequency Scenes

Science.gov (United States)

Schneps, Matthew H.; Brockmole, James R.; Sonnert, Gerhard; Pomplun, Marc

2012-01-01

People with dyslexia, who face lifelong struggles with reading, exhibit numerous associated low-level sensory deficits including deficits in focal attention. Countering this, studies have shown that struggling readers outperform typical readers in some visual tasks that integrate distributed information across an expanse. Though such abilities would be expected to facilitate scene memory, prior investigations using the contextual cueing paradigm failed to find corresponding advantages in dyslexia. We suggest that these studies were confounded by task-dependent effects exaggerating known focal attention deficits in dyslexia, and that, if natural scenes were used as the context, advantages would emerge. Here, we investigate this hypothesis by comparing college students with histories of severe lifelong reading difficulties (SR) and typical readers (TR) in contexts that vary attention load. We find no differences in contextual-cueing when spatial contexts are letter-like objects, or when contexts are natural scenes. However, the SR group significantly outperforms the TR group when contexts are low-pass filtered natural scenes [F(3, 39) = 3.15, p<.05]. These findings suggest that perception or memory for low spatial frequency components in scenes is enhanced in dyslexia. These findings are important because they suggest strengths for spatial learning in a population otherwise impaired, carrying implications for the education and support of students who face challenges in school. PMID:22558210

History of reading struggles linked to enhanced learning in low spatial frequency scenes.

Directory of Open Access Journals (Sweden)

Matthew H Schneps

Full Text Available People with dyslexia, who face lifelong struggles with reading, exhibit numerous associated low-level sensory deficits including deficits in focal attention. Countering this, studies have shown that struggling readers outperform typical readers in some visual tasks that integrate distributed information across an expanse. Though such abilities would be expected to facilitate scene memory, prior investigations using the contextual cueing paradigm failed to find corresponding advantages in dyslexia. We suggest that these studies were confounded by task-dependent effects exaggerating known focal attention deficits in dyslexia, and that, if natural scenes were used as the context, advantages would emerge. Here, we investigate this hypothesis by comparing college students with histories of severe lifelong reading difficulties (SR and typical readers (TR in contexts that vary attention load. We find no differences in contextual-cueing when spatial contexts are letter-like objects, or when contexts are natural scenes. However, the SR group significantly outperforms the TR group when contexts are low-pass filtered natural scenes [F(3, 39 = 3.15, p<.05]. These findings suggest that perception or memory for low spatial frequency components in scenes is enhanced in dyslexia. These findings are important because they suggest strengths for spatial learning in a population otherwise impaired, carrying implications for the education and support of students who face challenges in school.

The Hip-Hop club scene: Gender, grinding and sex.

Science.gov (United States)

Muñoz-Laboy, Miguel; Weinstein, Hannah; Parker, Richard

2007-01-01

Hip-Hop culture is a key social medium through which many young men and women from communities of colour in the USA construct their gender. In this study, we focused on the Hip-Hop club scene in New York City with the intention of unpacking narratives of gender dynamics from the perspective of young men and women, and how these relate to their sexual experiences. We conducted a three-year ethnographic study that included ethnographic observations of Hip-Hop clubs and their social scene, and in-depth interviews with young men and young women aged 15-21. This paper describes how young people negotiate gender relations on the dance floor of Hip-Hop clubs. The Hip-Hop club scene represents a context or setting where young men's masculinities are contested by the social environment, where women challenge hypermasculine privilege and where young people can set the stage for what happens next in their sexual and emotional interactions. Hip-Hop culture therefore provides a window into the gender and sexual scripts of many urban minority youth. A fuller understanding of these patterns can offer key insights into the social construction of sexual risk, as well as the possibilities for sexual health promotion, among young people in urban minority populations.

Scene Classification Using High Spatial Resolution Multispectral Data

National Research Council Canada - National Science Library

Garner, Jamada

2002-01-01

...), High-spatial resolution (8-meter), 4-color MSI data from IKONOS provide a new tool for scene classification, The utility of these data are studied for the purpose of classifying the Elkhorn Slough and surrounding wetlands in central...

NEGOTIATING PLACE AND GENDERED VIOLENCE IN CANADA’S LARGEST OPEN DRUG SCENE

Science.gov (United States)

McNeil, Ryan; Shannon, Kate; Shaver, Laura; Kerr, Thomas; Small, Will

2014-01-01

Background Vancouver’s Downtown Eastside is home to Canada’s largest street-based drug scene and only supervised injection facility (Insite). High levels of violence among men and women have been documented in this neighbourhood. This study was undertaken to explore the role of violence in shaping the socio-spatial relations of women and ‘marginal men’ (i.e., those occupying subordinate positions within the drug scene) in the Downtown Eastside, including access to Insite. Methods Semi-structured qualitative interviews were conducted with 23 people who inject drugs (PWID) recruited through the Vancouver Area Network of Drug Users, a local drug user organization. Interviews included a mapping exercise. Interview transcripts and maps were analyzed thematically, with an emphasis on how gendered violence shaped participants’ spatial practices. Results Hegemonic forms of masculinity operating within the Downtown Eastside framed the everyday violence experienced by women and marginal men. This violence shaped the spatial practices of women and marginal men, in that they avoided drug scene milieus where they had experienced violence or that they perceived to be dangerous. Some men linked their spatial restrictions to the perceived 'dope quality' of neighbourhood drug dealers to maintain claims to dominant masculinities while enacting spatial strategies to promote safety. Environmental supports provided by health and social care agencies were critical in enabling women and marginal men to negotiate place and survival within the context of drug scene violence. Access to Insite did not motivate participants to enter into “dangerous” drug scene milieus but they did venture into these areas if necessary to obtain drugs or generate income. Conclusion Gendered violence is critical in restricting the geographies of men and marginal men within the street-based drug scene. There is a need to scale up existing environmental interventions, including supervised injection

Spectral feature characterization methods for blood stain detection in crime scene backgrounds

Science.gov (United States)

Yang, Jie; Mathew, Jobin J.; Dube, Roger R.; Messinger, David W.

2016-05-01

Blood stains are one of the most important types of evidence for forensic investigation. They contain valuable DNA information, and the pattern of the stains can suggest specifics about the nature of the violence that transpired at the scene. Blood spectral signatures containing unique reflectance or absorption features are important both for forensic on-site investigation and laboratory testing. They can be used for target detection and identification applied to crime scene hyperspectral imagery, and also be utilized to analyze the spectral variation of blood on various backgrounds. Non-blood stains often mislead the detection and can generate false alarms at a real crime scene, especially for dark and red backgrounds. This paper measured the reflectance of liquid blood and 9 kinds of non-blood samples in the range of 350 nm - 2500 nm in various crime scene backgrounds, such as pure samples contained in petri dish with various thicknesses, mixed samples with different colors and materials of fabrics, and mixed samples with wood, all of which are examined to provide sub-visual evidence for detecting and recognizing blood from non-blood samples in a realistic crime scene. The spectral difference between blood and non-blood samples are examined and spectral features such as "peaks" and "depths" of reflectance are selected. Two blood stain detection methods are proposed in this paper. The first method uses index to denote the ratio of "depth" minus "peak" over"depth" add"peak" within a wavelength range of the reflectance spectrum. The second method uses relative band depth of the selected wavelength ranges of the reflectance spectrum. Results show that the index method is able to discriminate blood from non-blood samples in most tested crime scene backgrounds, but is not able to detect it from black felt. Whereas the relative band depth method is able to discriminate blood from non-blood samples on all of the tested background material types and colors.

"Spice" (Synthetic Marijuana) Induced Acute Myocardial Infarction: A Case Series.

Science.gov (United States)

Ul Haq, E; Shafiq, A; Khan, A A; Awan, A A; Ezad, S; Minteer, W J; Omar, B

2017-01-01

Marijuana is the most widely abused "recreational" substance in the United States, with highest prevalence in young adults. It is reported to cause ischemic strokes, hepatitis, anxiety, and psychosis. Although it is associated with dose dependent tachycardia and can lead to coronary vasospasm, it has not been directly related to acute myocardial infarction (AMI). Marijuana induced coronary vasospasm can result in endothelial denudation at the site of a vulnerable atherosclerotic plaque in response to hemodynamic stressors, potentially causing an AMI. Spice refers to herbal mixture with composition and effects similar to that of marijuana and therefore is referred to as "synthetic marijuana." Herein, we report 3 cases of spice induced ST-segment elevation myocardial infarction. All patients were relatively young and had few or absolutely no risk factors for cardiovascular disease. All patients underwent emergent coronary angiography, with two needing stent placement and the third requiring only aspiration thrombectomy. Our case series emphasizes the importance of suspecting and investigating synthetic marijuana use in low risk young adults presenting with AMI.

Synthetic generation of myocardial blood-oxygen-level-dependent MRI time series via structural sparse decomposition modeling.

Science.gov (United States)

Rusu, Cristian; Morisi, Rita; Boschetto, Davide; Dharmakumar, Rohan; Tsaftaris, Sotirios A

2014-07-01

This paper aims to identify approaches that generate appropriate synthetic data (computer generated) for cardiac phase-resolved blood-oxygen-level-dependent (CP-BOLD) MRI. CP-BOLD MRI is a new contrast agent- and stress-free approach for examining changes in myocardial oxygenation in response to coronary artery disease. However, since signal intensity changes are subtle, rapid visualization is not possible with the naked eye. Quantifying and visualizing the extent of disease relies on myocardial segmentation and registration to isolate the myocardium and establish temporal correspondences and ischemia detection algorithms to identify temporal differences in BOLD signal intensity patterns. If transmurality of the defect is of interest pixel-level analysis is necessary and thus a higher precision in registration is required. Such precision is currently not available affecting the design and performance of the ischemia detection algorithms. In this work, to enable algorithmic developments of ischemia detection irrespective to registration accuracy, we propose an approach that generates synthetic pixel-level myocardial time series. We do this by 1) modeling the temporal changes in BOLD signal intensity based on sparse multi-component dictionary learning, whereby segmentally derived myocardial time series are extracted from canine experimental data to learn the model; and 2) demonstrating the resemblance between real and synthetic time series for validation purposes. We envision that the proposed approach has the capacity to accelerate development of tools for ischemia detection while markedly reducing experimental costs so that cardiac BOLD MRI can be rapidly translated into the clinical arena for the noninvasive assessment of ischemic heart disease.

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

OpenAIRE

Li, Yuhong; Zhang, Xiaofan; Chen, Deming

2018-01-01

We propose a network for Congested Scene Recognition called CSRNet to provide a data-driven and deep learning method that can understand highly congested scenes and perform accurate count estimation as well as present high-quality density maps. The proposed CSRNet is composed of two major components: a convolutional neural network (CNN) as the front-end for 2D feature extraction and a dilated CNN for the back-end, which uses dilated kernels to deliver larger reception fields and to replace po...

Computer-aided fiber analysis for crime scene forensics

Science.gov (United States)

Hildebrandt, Mario; Arndt, Christian; Makrushin, Andrey; Dittmann, Jana

2012-03-01

The forensic analysis of fibers is currently completely manual and therefore time consuming. The automation of analysis steps can significantly support forensic experts and reduce the time, required for the investigation. Moreover, a subjective expert belief is extended by objective machine estimation. This work proposes the pattern recognition pipeline containing the digital acquisition of a fiber media, the pre-processing for fiber segmentation, and the extraction of the distinctive characteristics of fibers. Currently, basic geometrical features like width, height, area of optically dominant fibers are investigated. In order to support the automatic classification of fibers, supervised machine learning algorithms are evaluated. The experimental setup includes a car seat and two pieces clothing of a different fabric. As preliminary work, acrylic as synthetic and sheep wool as natural fiber are chosen to be classified. While sitting on the seat, a test person leaves textile fibers. The test aims at automatic distinguishing of clothes through the fiber traces gained from the seat with the help of adhesive tape. The digitalization of fiber samples is provided by a contactless chromatic white light sensor. First test results showed, that two optically very different fibers can be properly assigned to their corresponding fiber type. The best classifier achieves an accuracy of 75 percent correctly classified samples for our suggested features.

Dynamic programming in parallel boundary detection with application to ultrasound intima-media segmentation.

Science.gov (United States)

Zhou, Yuan; Cheng, Xinyao; Xu, Xiangyang; Song, Enmin

2013-12-01

Segmentation of carotid artery intima-media in longitudinal ultrasound images for measuring its thickness to predict cardiovascular diseases can be simplified as detecting two nearly parallel boundaries within a certain distance range, when plaque with irregular shapes is not considered. In this paper, we improve the implementation of two dynamic programming (DP) based approaches to parallel boundary detection, dual dynamic programming (DDP) and piecewise linear dual dynamic programming (PL-DDP). Then, a novel DP based approach, dual line detection (DLD), which translates the original 2-D curve position to a 4-D parameter space representing two line segments in a local image segment, is proposed to solve the problem while maintaining efficiency and rotation invariance. To apply the DLD to ultrasound intima-media segmentation, it is imbedded in a framework that employs an edge map obtained from multiplication of the responses of two edge detectors with different scales and a coupled snake model that simultaneously deforms the two contours for maintaining parallelism. The experimental results on synthetic images and carotid arteries of clinical ultrasound images indicate improved performance of the proposed DLD compared to DDP and PL-DDP, with respect to accuracy and efficiency. Copyright © 2013 Elsevier B.V. All rights reserved.

Behind the scenes at the LHC inauguration

CERN Document Server

2008-01-01

On 21 October the LHC inauguration ceremony will take place and people from all over CERN have been busy preparing. With delegations from 38 countries attending, including ministers and heads of state, the Bulletin has gone behind the scenes to see what it takes to put together an event of this scale.

Desirable and undesirable future thoughts call for different scene construction processes.

Science.gov (United States)

de Vito, S; Neroni, M A; Gamboz, N; Della Sala, S; Brandimonte, M A

2015-01-01

Despite the growing interest in the ability of foreseeing (episodic future thinking), it is still unclear how healthy people construct possible future scenarios. We suggest that different future thoughts require different processes of scene construction. Thirty-five participants were asked to imagine desirable and less desirable future events. Imagining desirable events increased the ease of scene construction, the frequency of life scripts, the number of internal details, and the clarity of sensorial and spatial temporal information. The initial description of general personal knowledge lasted longer in undesirable than in desirable anticipations. Finally, participants were more prone to explicitly indicate autobiographical memory as the main source of their simulations of undesirable episodes, whereas they equally related the simulations of desirable events to autobiographical events or semantic knowledge. These findings show that desirable and undesirable scenarios call for different mechanisms of scene construction. The present study emphasizes that future thinking cannot be considered as a monolithic entity.

Application of composite small calibration objects in traffic accident scene photogrammetry.

Science.gov (United States)

Chen, Qiang; Xu, Hongguo; Tan, Lidong

2015-01-01

In order to address the difficulty of arranging large calibration objects and the low measurement accuracy of small calibration objects in traffic accident scene photogrammetry, a photogrammetric method based on a composite of small calibration objects is proposed. Several small calibration objects are placed around the traffic accident scene, and the coordinate system of the composite calibration object is given based on one of them. By maintaining the relative position and coplanar relationship of the small calibration objects, the local coordinate system of each small calibration object is transformed into the coordinate system of the composite calibration object. The two-dimensional direct linear transformation method is improved based on minimizing the reprojection error of the calibration points of all objects. A rectified image is obtained using the nonlinear optimization method. The increased accuracy of traffic accident scene photogrammetry using a composite small calibration object is demonstrated through the analysis of field experiments and case studies.

Application of composite small calibration objects in traffic accident scene photogrammetry.

Directory of Open Access Journals (Sweden)

Qiang Chen

Full Text Available In order to address the difficulty of arranging large calibration objects and the low measurement accuracy of small calibration objects in traffic accident scene photogrammetry, a photogrammetric method based on a composite of small calibration objects is proposed. Several small calibration objects are placed around the traffic accident scene, and the coordinate system of the composite calibration object is given based on one of them. By maintaining the relative position and coplanar relationship of the small calibration objects, the local coordinate system of each small calibration object is transformed into the coordinate system of the composite calibration object. The two-dimensional direct linear transformation method is improved based on minimizing the reprojection error of the calibration points of all objects. A rectified image is obtained using the nonlinear optimization method. The increased accuracy of traffic accident scene photogrammetry using a composite small calibration object is demonstrated through the analysis of field experiments and case studies.

Number 13 / Part I. Music. 3. Mad Scenes: A Warning against Overwhelming Passions

Directory of Open Access Journals (Sweden)

Marisi Rossella

2017-03-01

Full Text Available This study focuses on mad scenes in poetry and musical theatre, stressing that, according to Aristotle’s theory on catharsis and the Affektenlehre, they had a pedagogical role on the audience. Some mad scenes by J.S. Bach, Handel and Mozart are briefly analyzed, highlighting their most relevant textual and musical characteristics.

Improving Remote Sensing Scene Classification by Integrating Global-Context and Local-Object Features

Directory of Open Access Journals (Sweden)

Dan Zeng

2018-05-01

Full Text Available Recently, many researchers have been dedicated to using convolutional neural networks (CNNs to extract global-context features (GCFs for remote-sensing scene classification. Commonly, accurate classification of scenes requires knowledge about both the global context and local objects. However, unlike the natural images in which the objects cover most of the image, objects in remote-sensing images are generally small and decentralized. Thus, it is hard for vanilla CNNs to focus on both global context and small local objects. To address this issue, this paper proposes a novel end-to-end CNN by integrating the GCFs and local-object-level features (LOFs. The proposed network includes two branches, the local object branch (LOB and global semantic branch (GSB, which are used to generate the LOFs and GCFs, respectively. Then, the concatenation of features extracted from the two branches allows our method to be more discriminative in scene classification. Three challenging benchmark remote-sensing datasets were extensively experimented on; the proposed approach outperformed the existing scene classification methods and achieved state-of-the-art results for all three datasets.

Out of Mind, Out of Sight: Unexpected Scene Elements Frequently Go Unnoticed Until Primed.

Science.gov (United States)

Slavich, George M; Zimbardo, Philip G

2013-12-01

The human visual system employs a sophisticated set of strategies for scanning the environment and directing attention to stimuli that can be expected given the context and a person's past experience. Although these strategies enable us to navigate a very complex physical and social environment, they can also cause highly salient, but unexpected stimuli to go completely unnoticed. To examine the generality of this phenomenon, we conducted eight studies that included 15 different experimental conditions and 1,577 participants in all. These studies revealed that a large majority of participants do not report having seen a woman in the center of an urban scene who was photographed in midair as she was committing suicide. Despite seeing the scene repeatedly, 46 % of all participants failed to report seeing a central figure and only 4.8 % reported seeing a falling person. Frequency of noticing the suicidal woman was highest for participants who read a narrative priming story that increased the extent to which she was schematically congruent with the scene. In contrast to this robust effect of inattentional blindness , a majority of participants reported seeing other peripheral objects in the visual scene that were equally difficult to detect, yet more consistent with the scene. Follow-up qualitative analyses revealed that participants reported seeing many elements that were not actually present, but which could have been expected given the overall context of the scene. Together, these findings demonstrate the robustness of inattentional blindness and highlight the specificity with which different visual primes may increase noticing behavior.

Influence of semantic consistency and perceptual features on visual attention during scene viewing in toddlers.

Science.gov (United States)

Helo, Andrea; van Ommen, Sandrien; Pannasch, Sebastian; Danteny-Dordoigne, Lucile; Rämä, Pia

2017-11-01

Conceptual representations of everyday scenes are built in interaction with visual environment and these representations guide our visual attention. Perceptual features and object-scene semantic consistency have been found to attract our attention during scene exploration. The present study examined how visual attention in 24-month-old toddlers is attracted by semantic violations and how perceptual features (i. e. saliency, centre distance, clutter and object size) and linguistic properties (i. e. object label frequency and label length) affect gaze distribution. We compared eye movements of 24-month-old toddlers and adults while exploring everyday scenes which either contained an inconsistent (e.g., soap on a breakfast table) or consistent (e.g., soap in a bathroom) object. Perceptual features such as saliency, centre distance and clutter of the scene affected looking times in the toddler group during the whole viewing time whereas looking times in adults were affected only by centre distance during the early viewing time. Adults looked longer to inconsistent than consistent objects either if the objects had a high or a low saliency. In contrast, toddlers presented semantic consistency effect only when objects were highly salient. Additionally, toddlers with lower vocabulary skills looked longer to inconsistent objects while toddlers with higher vocabulary skills look equally long to both consistent and inconsistent objects. Our results indicate that 24-month-old children use scene context to guide visual attention when exploring the visual environment. However, perceptual features have a stronger influence in eye movement guidance in toddlers than in adults. Our results also indicate that language skills influence cognitive but not perceptual guidance of eye movements during scene perception in toddlers. Copyright © 2017 Elsevier Inc. All rights reserved.

Image segmentation and dynamic lineage analysis in single-cell fluorescence microscopy.

Science.gov (United States)

Wang, Quanli; Niemi, Jarad; Tan, Chee-Meng; You, Lingchong; West, Mike

2010-01-01

An increasingly common component of studies in synthetic and systems biology is analysis of dynamics of gene expression at the single-cell level, a context that is heavily dependent on the use of time-lapse movies. Extracting quantitative data on the single-cell temporal dynamics from such movies remains a major challenge. Here, we describe novel methods for automating key steps in the analysis of single-cell, fluorescent images-segmentation and lineage reconstruction-to recognize and track individual cells over time. The automated analysis iteratively combines a set of extended morphological methods for segmentation, and uses a neighborhood-based scoring method for frame-to-frame lineage linking. Our studies with bacteria, budding yeast and human cells, demonstrate the portability and usability of these methods, whether using phase, bright field or fluorescent images. These examples also demonstrate the utility of our integrated approach in facilitating analyses of engineered and natural cellular networks in diverse settings. The automated methods are implemented in freely available, open-source software.

The Interplay of Episodic and Semantic Memory in Guiding Repeated Search in Scenes

Science.gov (United States)

Vo, Melissa L.-H.; Wolfe, Jeremy M.

2013-01-01

It seems intuitive to think that previous exposure or interaction with an environment should make it easier to search through it and, no doubt, this is true in many real-world situations. However, in a recent study, we demonstrated that previous exposure to a scene does not necessarily speed search within that scene. For instance, when observers…

Tachistoscopic illumination and masking of real scenes.

Science.gov (United States)

Chichka, David; Philbeck, John W; Gajewski, Daniel A

2015-03-01

Tachistoscopic presentation of scenes has been valuable for studying the emerging properties of visual scene representations. The spatial aspects of this work have generally been focused on the conceptual locations (e.g., next to the refrigerator) and directional locations of objects in 2-D arrays and/or images. Less is known about how the perceived egocentric distance of objects develops. Here we describe a novel system for presenting brief glimpses of a real-world environment, followed by a mask. The system includes projectors with mechanical shutters for projecting the fixation and masking images, a set of LED floodlights for illuminating the environment, and computer-controlled electronics to set the timing and initiate the process. Because a real environment is used, most visual distance and depth cues can be manipulated using traditional methods. The system is inexpensive, robust, and its components are readily available in the marketplace. This article describes the system and the timing characteristics of each component. We verified the system's ability to control exposure to time scales as low as a few milliseconds.

Evaluating Color Descriptors for Object and Scene Recognition

NARCIS (Netherlands)

van de Sande, K.E.A.; Gevers, T.; Snoek, C.G.M.

2010-01-01

Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used for feature extraction at salient points. To increase illumination invariance and discriminative power, color descriptors have been

Falling out of time: enhanced memory for scenes presented at behaviorally irrelevant points in time in posttraumatic stress disorder (PTSD).

Science.gov (United States)

Levy-Gigi, Einat; Kéri, Szabolcs

2012-01-01

Spontaneous encoding of the visual environment depends on the behavioral relevance of the task performed simultaneously. If participants identify target letters or auditory tones while viewing a series of briefly presented natural and urban scenes, they demonstrate effective scene recognition only when a target, but not a behaviorally irrelevant distractor, appears together with the scene. Here, we show that individuals with posttraumatic stress disorder (PTSD), who witnessed the red sludge disaster in Hungary, show the opposite pattern of performance: enhanced recognition of scenes presented together with distractors and deficient recognition of scenes presented with targets. The recognition of trauma-related and neutral scenes was not different in individuals with PTSD. We found a positive correlation between memory for scenes presented with auditory distractors and re-experiencing symptoms (memory intrusions and flashbacks). These results suggest that abnormal encoding of visual scenes at behaviorally irrelevant events might be associated with intrusive experiences by disrupting the flow of time.

Falling out of time: enhanced memory for scenes presented at behaviorally irrelevant points in time in posttraumatic stress disorder (PTSD.

Directory of Open Access Journals (Sweden)

Einat Levy-Gigi

Full Text Available Spontaneous encoding of the visual environment depends on the behavioral relevance of the task performed simultaneously. If participants identify target letters or auditory tones while viewing a series of briefly presented natural and urban scenes, they demonstrate effective scene recognition only when a target, but not a behaviorally irrelevant distractor, appears together with the scene. Here, we show that individuals with posttraumatic stress disorder (PTSD, who witnessed the red sludge disaster in Hungary, show the opposite pattern of performance: enhanced recognition of scenes presented together with distractors and deficient recognition of scenes presented with targets. The recognition of trauma-related and neutral scenes was not different in individuals with PTSD. We found a positive correlation between memory for scenes presented with auditory distractors and re-experiencing symptoms (memory intrusions and flashbacks. These results suggest that abnormal encoding of visual scenes at behaviorally irrelevant events might be associated with intrusive experiences by disrupting the flow of time.

Contribution to the tracking and the 3D reconstruction of scenes composed of torus from image sequences a acquired by a moving camera

International Nuclear Information System (INIS)

Naudet, S.

1997-01-01

The three-dimensional perception of the environment is often necessary for a robot to correctly perform its tasks. One solution, based on the dynamic vision, consists in analysing time-varying monocular images to estimate the spatial geometry of the scene. This thesis deals with the reconstruction of torus by dynamic vision. Though this object class is restrictive, it enables to tackle the problem of reconstruction of bent pipes usually encountered in industrial environments. The proposed method is based on the evolution of apparent contours of objects in the sequence. Using the expression of torus limb boundaries, it is possible to recursively estimate the object three-dimensional parameters by minimising the error between the predicted projected contours and the image contours. This process, which is performed by a Kalman filter, does not need a precise knowledge of the camera displacement or any matching of the tow limbs belonging to the same object. To complete this work, temporal tracking of objects which deals with occlusion situations is proposed. The approach consists in modeling and interpreting the apparent motion of objects in the successive images. The motion interpretation, based on a simplified representation of the scene, allows to recover pertinent three-dimensional information which is used to manage occlusion situations. Experiments, on synthetic and real images, proves he validity of the tracking and the reconstruction processes. (author)

Using 3D range cameras for crime scene documentation and legal medicine

Science.gov (United States)

Cavagnini, Gianluca; Sansoni, Giovanna; Trebeschi, Marco

2009-01-01

Crime scene documentation and legal medicine analysis are part of a very complex process which is aimed at identifying the offender starting from the collection of the evidences on the scene. This part of the investigation is very critical, since the crime scene is extremely volatile, and once it is removed, it can not be precisely created again. For this reason, the documentation process should be as complete as possible, with minimum invasiveness. The use of optical 3D imaging sensors has been considered as a possible aid to perform the documentation step, since (i) the measurement is contactless and (ii) the process required to editing and modeling the 3D data is quite similar to the reverse engineering procedures originally developed for the manufacturing field. In this paper we show the most important results obtained in the experimentation.

Making a scene: exploring the dimensions of place through Dutch popular music, 1960-2010

NARCIS (Netherlands)

Brandellero, A.; Pfeffer, K.

2015-01-01

This paper applies a multi-layered conceptualisation of place to the analysis of particular music scenes in the Netherlands, 1960-2010. We focus on: the clustering of music-related activities in locations; the delineation of spatially tied music scenes, based on a shared identity, reproduced over

Cortical networks dynamically emerge with the interplay of slow and fast oscillations for memory of a natural scene.

Science.gov (United States)

Mizuhara, Hiroaki; Sato, Naoyuki; Yamaguchi, Yoko

2015-05-01

Neural oscillations are crucial for revealing dynamic cortical networks and for serving as a possible mechanism of inter-cortical communication, especially in association with mnemonic function. The interplay of the slow and fast oscillations might dynamically coordinate the mnemonic cortical circuits to rehearse stored items during working memory retention. We recorded simultaneous EEG-fMRI during a working memory task involving a natural scene to verify whether the cortical networks emerge with the neural oscillations for memory of the natural scene. The slow EEG power was enhanced in association with the better accuracy of working memory retention, and accompanied cortical activities in the mnemonic circuits for the natural scene. Fast oscillation showed a phase-amplitude coupling to the slow oscillation, and its power was tightly coupled with the cortical activities for representing the visual images of natural scenes. The mnemonic cortical circuit with the slow neural oscillations would rehearse the distributed natural scene representations with the fast oscillation for working memory retention. The coincidence of the natural scene representations could be obtained by the slow oscillation phase to create a coherent whole of the natural scene in the working memory. Copyright © 2015 Elsevier Inc. All rights reserved.

How children remember neutral and emotional pictures: boundary extension in children's scene memories.

Science.gov (United States)

Candel, Ingrid; Merckelbach, Harald; Houben, Katrijn; Vandyck, Inne

2004-01-01

Boundary extension is the tendency to remember more of a scene than was actually shown. The dominant interpretation of this memory illusion is that it originates from schemata that people construct when viewing a scene. Evidence of boundary extension has been obtained primarily with adult participants who remember neutral pictures. The current study addressed the developmental stability of this phenomenon. Therefore, we investigated whether children aged 10-12 years display boundary extension for neutral pictures. Moreover, we examined emotional scene memory. Eighty-seven children drew pictures from memory after they had seen either neutral or emotional pictures. Both their neutral and emotional drawings revealed boundary extension. Apparently, the schema construction that underlies boundary extension is a robust and ubiquitous process.

A higher-order tensor vessel tractography for segmentation of vascular structures.

Science.gov (United States)

Cetin, Suheyla; Unal, Gozde

2015-10-01

A new vascular structure segmentation method, which is based on a cylindrical flux-based higher order tensor (HOT), is presented. On a vessel structure, the HOT naturally models branching points, which create challenges for vessel segmentation algorithms. In a general linear HOT model embedded in 3D, one has to work with an even order tensor due to an enforced antipodal-symmetry on the unit sphere. However, in scenarios such as in a bifurcation, the antipodally-symmetric tensor embedded in 3D will not be useful. In order to overcome that limitation, we embed the tensor in 4D and obtain a structure that can model asymmetric junction scenarios. During construction of a higher order tensor (e.g. third or fourth order) in 4D, the orientation vectors lie on the unit 3-sphere, in contrast to the unit 2-sphere in 3D tensor modeling. This 4D tensor is exploited in a seed-based vessel segmentation algorithm, where the principal directions of the 4D HOT is obtained by decomposition, and used in a HOT tractography approach. We demonstrate quantitative validation of the proposed algorithm on both synthetic complex tubular structures as well as real cerebral vasculature in Magnetic Resonance Angiography (MRA) datasets and coronary arteries from Computed Tomography Angiography (CTA) volumes.

Using selected scenes from Brazilian films to teach about substance use disorders, within medical education.

Science.gov (United States)

Castaldelli-Maia, João Mauricio; Oliveira, Hercílio Pereira; Andrade, Arthur Guerra; Lotufo-Neto, Francisco; Bhugra, Dinesh

2012-01-01

Themes like alcohol and drug abuse, relationship difficulties, psychoses, autism and personality dissociation disorders have been widely used in films. Psychiatry and psychiatric conditions in various cultural settings are increasingly taught using films. Many articles on cinema and psychiatry have been published but none have presented any methodology on how to select material. Here, the authors look at the portrayal of abusive use of alcohol and drugs during the Brazilian cinema revival period (1994 to 2008). Qualitative study at two universities in the state of São Paulo. Scenes were selected from films available at rental stores and were analyzed using a specifically designed protocol. We assessed how realistic these scenes were and their applicability for teaching. One author selected 70 scenes from 50 films (graded for realism and teaching applicability > 8). These were then rated by another two judges. Rating differences among the three judges were assessed using nonparametric tests (P 8) were defined as "quality scenes". Thirty-nine scenes from 27 films were identified as "quality scenes". Alcohol, cannabis, cocaine, hallucinogens and inhalants were included in these. Signs and symptoms of intoxication, abusive/harmful use and dependence were shown. We have produced rich teaching material for discussing psychopathology relating to alcohol and drug use that can be used both at undergraduate and at postgraduate level. Moreover, it could be seen that certain drug use behavioral patterns are deeply rooted in some Brazilian films and groups.

Two-Phase and Graph-Based Clustering Methods for Accurate and Efficient Segmentation of Large Mass Spectrometry Images.

Science.gov (United States)

Dexter, Alex; Race, Alan M; Steven, Rory T; Barnes, Jennifer R; Hulme, Heather; Goodwin, Richard J A; Styles, Iain B; Bunch, Josephine

2017-11-07

Clustering is widely used in MSI to segment anatomical features and differentiate tissue types, but existing approaches are both CPU and memory-intensive, limiting their application to small, single data sets. We propose a new approach that uses a graph-based algorithm with a two-phase sampling method that overcomes this limitation. We demonstrate the algorithm on a range of sample types and show that it can segment anatomical features that are not identified using commonly employed algorithms in MSI, and we validate our results on synthetic MSI data. We show that the algorithm is robust to fluctuations in data quality by successfully clustering data with a designed-in variance using data acquired with varying laser fluence. Finally, we show that this method is capable of generating accurate segmentations of large MSI data sets acquired on the newest generation of MSI instruments and evaluate these results by comparison with histopathology.

Land-use Scene Classification in High-Resolution Remote Sensing Images by Multiscale Deeply Described Correlatons

Science.gov (United States)

Qi, K.; Qingfeng, G.

2017-12-01

With the popular use of High-Resolution Satellite (HRS) images, more and more research efforts have been placed on land-use scene classification. However, it makes the task difficult with HRS images for the complex background and multiple land-cover classes or objects. This article presents a multiscale deeply described correlaton model for land-use scene classification. Specifically, the convolutional neural network is introduced to learn and characterize the local features at different scales. Then, learnt multiscale deep features are explored to generate visual words. The spatial arrangement of visual words is achieved through the introduction of adaptive vector quantized correlograms at different scales. Experiments on two publicly available land-use scene datasets demonstrate that the proposed model is compact and yet discriminative for efficient representation of land-use scene images, and achieves competitive classification results with the state-of-art methods.

Automatic Segmentation and Quantification of Filamentous Structures in Electron Tomography.

Science.gov (United States)

Loss, Leandro A; Bebis, George; Chang, Hang; Auer, Manfred; Sarkar, Purbasha; Parvin, Bahram

2012-10-01

Electron tomography is a promising technology for imaging ultrastructures at nanoscale resolutions. However, image and quantitative analyses are often hindered by high levels of noise, staining heterogeneity, and material damage either as a result of the electron beam or sample preparation. We have developed and built a framework that allows for automatic segmentation and quantification of filamentous objects in 3D electron tomography. Our approach consists of three steps: (i) local enhancement of filaments by Hessian filtering; (ii) detection and completion (e.g., gap filling) of filamentous structures through tensor voting; and (iii) delineation of the filamentous networks. Our approach allows for quantification of filamentous networks in terms of their compositional and morphological features. We first validate our approach using a set of specifically designed synthetic data. We then apply our segmentation framework to tomograms of plant cell walls that have undergone different chemical treatments for polysaccharide extraction. The subsequent compositional and morphological analyses of the plant cell walls reveal their organizational characteristics and the effects of the different chemical protocols on specific polysaccharides.

Fixation and saliency during search of natural scenes: the case of visual agnosia.

Science.gov (United States)

Foulsham, Tom; Barton, Jason J S; Kingstone, Alan; Dewhurst, Richard; Underwood, Geoffrey

2009-07-01

Models of eye movement control in natural scenes often distinguish between stimulus-driven processes (which guide the eyes to visually salient regions) and those based on task and object knowledge (which depend on expectations or identification of objects and scene gist). In the present investigation, the eye movements of a patient with visual agnosia were recorded while she searched for objects within photographs of natural scenes and compared to those made by students and age-matched controls. Agnosia is assumed to disrupt the top-down knowledge available in this task, and so may increase the reliance on bottom-up cues. The patient's deficit in object recognition was seen in poor search performance and inefficient scanning. The low-level saliency of target objects had an effect on responses in visual agnosia, and the most salient region in the scene was more likely to be fixated by the patient than by controls. An analysis of model-predicted saliency at fixation locations indicated a closer match between fixations and low-level saliency in agnosia than in controls. These findings are discussed in relation to saliency-map models and the balance between high and low-level factors in eye guidance.

Extracting flat-field images from scene-based image sequences using phase correlation

Energy Technology Data Exchange (ETDEWEB)

Caron, James N., E-mail: Caron@RSImd.com [Research Support Instruments, 4325-B Forbes Boulevard, Lanham, Maryland 20706 (United States); Montes, Marcos J. [Naval Research Laboratory, Code 7231, 4555 Overlook Avenue, SW, Washington, DC 20375 (United States); Obermark, Jerome L. [Naval Research Laboratory, Code 8231, 4555 Overlook Avenue, SW, Washington, DC 20375 (United States)

2016-06-15

Flat-field image processing is an essential step in producing high-quality and radiometrically calibrated images. Flat-fielding corrects for variations in the gain of focal plane array electronics and unequal illumination from the system optics. Typically, a flat-field image is captured by imaging a radiometrically uniform surface. The flat-field image is normalized and removed from the images. There are circumstances, such as with remote sensing, where a flat-field image cannot be acquired in this manner. For these cases, we developed a phase-correlation method that allows the extraction of an effective flat-field image from a sequence of scene-based displaced images. The method uses sub-pixel phase correlation image registration to align the sequence to estimate the static scene. The scene is removed from sequence producing a sequence of misaligned flat-field images. An average flat-field image is derived from the realigned flat-field sequence.

The perception of naturalness correlates with low-level visual features of environmental scenes.

Directory of Open Access Journals (Sweden)

Marc G Berman

Full Text Available Previous research has shown that interacting with natural environments vs. more urban or built environments can have salubrious psychological effects, such as improvements in attention and memory. Even viewing pictures of nature vs. pictures of built environments can produce similar effects. A major question is: What is it about natural environments that produces these benefits? Problematically, there are many differing qualities between natural and urban environments, making it difficult to narrow down the dimensions of nature that may lead to these benefits. In this study, we set out to uncover visual features that related to individuals' perceptions of naturalness in images. We quantified naturalness in two ways: first, implicitly using a multidimensional scaling analysis and second, explicitly with direct naturalness ratings. Features that seemed most related to perceptions of naturalness were related to the density of contrast changes in the scene, the density of straight lines in the scene, the average color saturation in the scene and the average hue diversity in the scene. We then trained a machine-learning algorithm to predict whether a scene was perceived as being natural or not based on these low-level visual features and we could do so with 81% accuracy. As such we were able to reliably predict subjective perceptions of naturalness with objective low-level visual features. Our results can be used in future studies to determine if these features, which are related to naturalness, may also lead to the benefits attained from interacting with nature.

Attention in natural scenes: Affective-motivational factors guide gaze independently of visual salience.

Science.gov (United States)

Schomaker, Judith; Walper, Daniel; Wittmann, Bianca C; Einhäuser, Wolfgang

2017-04-01

In addition to low-level stimulus characteristics and current goals, our previous experience with stimuli can also guide attentional deployment. It remains unclear, however, if such effects act independently or whether they interact in guiding attention. In the current study, we presented natural scenes including every-day objects that differed in affective-motivational impact. In the first free-viewing experiment, we presented visually-matched triads of scenes in which one critical object was replaced that varied mainly in terms of motivational value, but also in terms of valence and arousal, as confirmed by ratings by a large set of observers. Treating motivation as a categorical factor, we found that it affected gaze. A linear-effect model showed that arousal, valence, and motivation predicted fixations above and beyond visual characteristics, like object size, eccentricity, or visual salience. In a second experiment, we experimentally investigated whether the effects of emotion and motivation could be modulated by visual salience. In a medium-salience condition, we presented the same unmodified scenes as in the first experiment. In a high-salience condition, we retained the saturation of the critical object in the scene, and decreased the saturation of the background, and in a low-salience condition, we desaturated the critical object while retaining the original saturation of the background. We found that highly salient objects guided gaze, but still found additional additive effects of arousal, valence and motivation, confirming that higher-level factors can also guide attention, as measured by fixations towards objects in natural scenes. Copyright © 2017 Elsevier Ltd. All rights reserved.

“Spice” (Synthetic Marijuana Induced Acute Myocardial Infarction: A Case Series

Directory of Open Access Journals (Sweden)

E. Ul Haq

2017-01-01

Full Text Available Marijuana is the most widely abused “recreational” substance in the United States, with highest prevalence in young adults. It is reported to cause ischemic strokes, hepatitis, anxiety, and psychosis. Although it is associated with dose dependent tachycardia and can lead to coronary vasospasm, it has not been directly related to acute myocardial infarction (AMI. Marijuana induced coronary vasospasm can result in endothelial denudation at the site of a vulnerable atherosclerotic plaque in response to hemodynamic stressors, potentially causing an AMI. Spice refers to herbal mixture with composition and effects similar to that of marijuana and therefore is referred to as “synthetic marijuana.” Herein, we report 3 cases of spice induced ST-segment elevation myocardial infarction. All patients were relatively young and had few or absolutely no risk factors for cardiovascular disease. All patients underwent emergent coronary angiography, with two needing stent placement and the third requiring only aspiration thrombectomy. Our case series emphasizes the importance of suspecting and investigating synthetic marijuana use in low risk young adults presenting with AMI.

Parts & Pools: A Framework for Modular Design of Synthetic Gene Circuits

Energy Technology Data Exchange (ETDEWEB)

Marchisio, Mario Andrea, E-mail: marchisio@hit.edu.cn [School of Life Science and Technology, Harbin Institute of Technology, Harbin (China)

2014-10-06

Published in 2008, Parts & Pools represents one of the first attempts to conceptualize the modular design of bacterial synthetic gene circuits with Standard Biological Parts (DNA segments) and Pools of molecules referred to as common signal carriers (e.g., RNA polymerases and ribosomes). The original framework for modeling bacterial components and designing prokaryotic circuits evolved over the last years and brought, first, to the development of an algorithm for the automatic design of Boolean gene circuits. This is a remarkable achievement since gene digital circuits have a broad range of applications that goes from biosensors for health and environment care to computational devices. More recently, Parts & Pools was enabled to give a proper formal description of eukaryotic biological circuit components. This was possible by employing a rule-based modeling approach, a technique that permits a faithful calculation of all the species and reactions involved in complex systems such as eukaryotic cells and compartments. In this way, Parts & Pools is currently suitable for the visual and modular design of synthetic gene circuits in yeast and mammalian cells too.

Parts & Pools: A Framework for Modular Design of Synthetic Gene Circuits

International Nuclear Information System (INIS)

Marchisio, Mario Andrea

2014-01-01

Published in 2008, Parts & Pools represents one of the first attempts to conceptualize the modular design of bacterial synthetic gene circuits with Standard Biological Parts (DNA segments) and Pools of molecules referred to as common signal carriers (e.g., RNA polymerases and ribosomes). The original framework for modeling bacterial components and designing prokaryotic circuits evolved over the last years and brought, first, to the development of an algorithm for the automatic design of Boolean gene circuits. This is a remarkable achievement since gene digital circuits have a broad range of applications that goes from biosensors for health and environment care to computational devices. More recently, Parts & Pools was enabled to give a proper formal description of eukaryotic biological circuit components. This was possible by employing a rule-based modeling approach, a technique that permits a faithful calculation of all the species and reactions involved in complex systems such as eukaryotic cells and compartments. In this way, Parts & Pools is currently suitable for the visual and modular design of synthetic gene circuits in yeast and mammalian cells too.

Effect of Viewing Smoking Scenes in Motion Pictures on Subsequent Smoking Desire in Audiences in South Korea.

Science.gov (United States)

Sohn, Minsung; Jung, Minsoo

2017-07-17

In the modern era of heightened awareness of public health, smoking scenes in movies remain relatively free from public monitoring. The effect of smoking scenes in movies on the promotion of viewers' smoking desire remains unknown. The study aimed to explore whether exposure of adolescent smokers to images of smoking in fılms could stimulate smoking behavior. Data were derived from a national Web-based sample survey of 748 Korean high-school students. Participants aged 16-18 years were randomly assigned to watch three short video clips with or without smoking scenes. After adjusting covariates using propensity score matching, paired sample t test and logistic regression analyses compared the difference in smoking desire before and after exposure of participants to smoking scenes. For male adolescents, cigarette craving was significantly higher in those who watched movies with smoking scenes than in the control group who did not view smoking scenes (t 307.96 =2.066, Pfilms and assigning a smoking-related screening grade to films is warranted. ©Minsung Sohn, Minsoo Jung. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 17.07.2017.

Position-Invariant Robust Features for Long-Term Recognition of Dynamic Outdoor Scenes

Science.gov (United States)

Kawewong, Aram; Tangruamsub, Sirinart; Hasegawa, Osamu

A novel Position-Invariant Robust Feature, designated as PIRF, is presented to address the problem of highly dynamic scene recognition. The PIRF is obtained by identifying existing local features (i.e. SIFT) that have a wide baseline visibility within a place (one place contains more than one sequential images). These wide-baseline visible features are then represented as a single PIRF, which is computed as an average of all descriptors associated with the PIRF. Particularly, PIRFs are robust against highly dynamical changes in scene: a single PIRF can be matched correctly against many features from many dynamical images. This paper also describes an approach to using these features for scene recognition. Recognition proceeds by matching an individual PIRF to a set of features from test images, with subsequent majority voting to identify a place with the highest matched PIRF. The PIRF system is trained and tested on 2000+ outdoor omnidirectional images and on COLD datasets. Despite its simplicity, PIRF offers a markedly better rate of recognition for dynamic outdoor scenes (ca. 90%) than the use of other features. Additionally, a robot navigation system based on PIRF (PIRF-Nav) can outperform other incremental topological mapping methods in terms of time (70% less) and memory. The number of PIRFs can be reduced further to reduce the time while retaining high accuracy, which makes it suitable for long-term recognition and localization.

Designing synthetic biology.

Science.gov (United States)

Agapakis, Christina M

2014-03-21

Synthetic biology is frequently defined as the application of engineering design principles to biology. Such principles are intended to streamline the practice of biological engineering, to shorten the time required to design, build, and test synthetic gene networks. This streamlining of iterative design cycles can facilitate the future construction of biological systems for a range of applications in the production of fuels, foods, materials, and medicines. The promise of these potential applications as well as the emphasis on design has prompted critical reflection on synthetic biology from design theorists and practicing designers from many fields, who can bring valuable perspectives to the discipline. While interdisciplinary connections between biologists and engineers have built synthetic biology via the science and the technology of biology, interdisciplinary collaboration with artists, designers, and social theorists can provide insight on the connections between technology and society. Such collaborations can open up new avenues and new principles for research and design, as well as shed new light on the challenging context-dependence-both biological and social-that face living technologies at many scales. This review is inspired by the session titled "Design and Synthetic Biology: Connecting People and Technology" at Synthetic Biology 6.0 and covers a range of literature on design practice in synthetic biology and beyond. Critical engagement with how design is used to shape the discipline opens up new possibilities for how we might design the future of synthetic biology.

The probability of object-scene co-occurrence influences object identification processes.

Science.gov (United States)

Sauvé, Geneviève; Harmand, Mariane; Vanni, Léa; Brodeur, Mathieu B

2017-07-01

Contextual information allows the human brain to make predictions about the identity of objects that might be seen and irregularities between an object and its background slow down perception and identification processes. Bar and colleagues modeled the mechanisms underlying this beneficial effect suggesting that the brain stocks information about the statistical regularities of object and scene co-occurrence. Their model suggests that these recurring regularities could be conceptualized along a continuum in which the probability of seeing an object within a given scene can be high (probable condition), moderate (improbable condition) or null (impossible condition). In the present experiment, we propose to disentangle the electrophysiological correlates of these context effects by directly comparing object-scene pairs found along this continuum. We recorded the event-related potentials of 30 healthy participants (18-34 years old) and analyzed their brain activity in three time windows associated with context effects. We observed anterior negativities between 250 and 500 ms after object onset for the improbable and impossible conditions (improbable more negative than impossible) compared to the probable condition as well as a parieto-occipital positivity (improbable more positive than impossible). The brain may use different processing pathways to identify objects depending on whether the probability of co-occurrence with the scene is moderate (rely more on top-down effects) or null (rely more on bottom-up influences). The posterior positivity could index error monitoring aimed to ensure that no false information is integrated into mental representations of the world.

Semantic Categorization Precedes Affective Evaluation of Visual Scenes

Science.gov (United States)