Segment-Tube: Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation

OpenAIRE

Le Wang; Xuhuan Duan; Qilin Zhang; Zhenxing Niu; Gang Hua; Nanning Zheng

2018-01-01

Inspired by the recent spatio-temporal action localization efforts with tubelets (sequences of bounding boxes), we present a new spatio-temporal action localization detector Segment-tube, which consists of sequences of per-frame segmentation masks. The proposed Segment-tube detector can temporally pinpoint the starting/ending frame of each action category in the presence of preceding/subsequent interference actions in untrimmed videos. Simultaneously, the Segment-tube detector produces per-fr...

Temporally coherent 4D video segmentation for teleconferencing

Science.gov (United States)

Ehmann, Jana; Guleryuz, Onur G.

2013-09-01

We develop an algorithm for 4-D (RGB+Depth) video segmentation targeting immersive teleconferencing ap- plications on emerging mobile devices. Our algorithm extracts users from their environments and places them onto virtual backgrounds similar to green-screening. The virtual backgrounds increase immersion and interac- tivity, relieving the users of the system from distractions caused by disparate environments. Commodity depth sensors, while providing useful information for segmentation, result in noisy depth maps with a large number of missing depth values. By combining depth and RGB information, our work signi¯cantly improves the other- wise very coarse segmentation. Further imposing temporal coherence yields compositions where the foregrounds seamlessly blend with the virtual backgrounds with minimal °icker and other artifacts. We achieve said improve- ments by correcting the missing information in depth maps before fast RGB-based segmentation, which operates in conjunction with temporal coherence. Simulation results indicate the e±cacy of the proposed system in video conferencing scenarios.

Robust Adaptable Video Copy Detection

DEFF Research Database (Denmark)

Assent, Ira; Kremer, Hardy

2009-01-01

in contrast). Our query processing combines filtering and indexing structures for efficient multistep computation of video copies under this model. We show that our model successfully identifies altered video copies and does so more reliably than existing models.......Video copy detection should be capable of identifying video copies subject to alterations e.g. in video contrast or frame rates. We propose a video copy detection scheme that allows for adaptable detection of videos that are altered temporally (e.g. frame rate change) and/or visually (e.g. change...

Automatic Story Segmentation for TV News Video Using Multiple Modalities

Directory of Open Access Journals (Sweden)

Émilie Dumont

2012-01-01

Full Text Available While video content is often stored in rather large files or broadcasted in continuous streams, users are often interested in retrieving only a particular passage on a topic of interest to them. It is, therefore, necessary to split video documents or streams into shorter segments corresponding to appropriate retrieval units. We propose here a method for the automatic segmentation of TV news videos into stories. A-multiple-descriptor based segmentation approach is proposed. The selected multimodal features are complementary and give good insights about story boundaries. Once extracted, these features are expanded with a local temporal context and combined by an early fusion process. The story boundaries are then predicted using machine learning techniques. We investigate the system by experiments conducted using TRECVID 2003 data and protocol of the story boundary detection task, and we show that the proposed approach outperforms the state-of-the-art methods while requiring a very small amount of manual annotation.

About subjective evaluation of adaptive video streaming

Science.gov (United States)

Tavakoli, Samira; Brunnström, Kjell; Garcia, Narciso

2015-03-01

The usage of HTTP Adaptive Streaming (HAS) technology by content providers is increasing rapidly. Having available the video content in multiple qualities, using HAS allows to adapt the quality of downloaded video to the current network conditions providing smooth video-playback. However, the time-varying video quality by itself introduces a new type of impairment. The quality adaptation can be done in different ways. In order to find the best adaptation strategy maximizing users perceptual quality it is necessary to investigate about the subjective perception of adaptation-related impairments. However, the novelties of these impairments and their comparably long time duration make most of the standardized assessment methodologies fall less suited for studying HAS degradation. Furthermore, in traditional testing methodologies, the quality of the video in audiovisual services is often evaluated separated and not in the presence of audio. Nevertheless, the requirement of jointly evaluating the audio and the video within a subjective test is a relatively under-explored research field. In this work, we address the research question of determining the appropriate assessment methodology to evaluate the sequences with time-varying quality due to the adaptation. This was done by studying the influence of different adaptation related parameters through two different subjective experiments using a methodology developed to evaluate long test sequences. In order to study the impact of audio presence on quality assessment by the test subjects, one of the experiments was done in the presence of audio stimuli. The experimental results were subsequently compared with another experiment using the standardized single stimulus Absolute Category Rating (ACR) methodology.

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.

From image captioning to video summary using deep recurrent networks and unsupervised segmentation

Science.gov (United States)

Morosanu, Bogdan-Andrei; Lemnaru, Camelia

2018-04-01

Automatic captioning systems based on recurrent neural networks have been tremendously successful at providing realistic natural language captions for complex and varied image data. We explore methods for adapting existing models trained on large image caption data sets to a similar problem, that of summarising videos using natural language descriptions and frame selection. These architectures create internal high level representations of the input image that can be used to define probability distributions and distance metrics on these distributions. Specifically, we interpret each hidden unit inside a layer of the caption model as representing the un-normalised log probability of some unknown image feature of interest for the caption generation process. We can then apply well understood statistical divergence measures to express the difference between images and create an unsupervised segmentation of video frames, classifying consecutive images of low divergence as belonging to the same context, and those of high divergence as belonging to different contexts. To provide a final summary of the video, we provide a group of selected frames and a text description accompanying them, allowing a user to perform a quick exploration of large unlabeled video databases.

Content-Aware Video Adaptation under Low-Bitrate Constraint

Directory of Open Access Journals (Sweden)

Hsiao Ming-Ho

2007-01-01

Full Text Available With the development of wireless network and the improvement of mobile device capability, video streaming is more and more widespread in such an environment. Under the condition of limited resource and inherent constraints, appropriate video adaptations have become one of the most important and challenging issues in wireless multimedia applications. In this paper, we propose a novel content-aware video adaptation in order to effectively utilize resource and improve visual perceptual quality. First, the attention model is derived from analyzing the characteristics of brightness, location, motion vector, and energy features in compressed domain to reduce computation complexity. Then, through the integration of attention model, capability of client device and correlational statistic model, attractive regions of video scenes are derived. The information object- (IOB- weighted rate distortion model is used for adjusting the bit allocation. Finally, the video adaptation scheme dynamically adjusts video bitstream in frame level and object level. Experimental results validate that the proposed scheme achieves better visual quality effectively and efficiently.

An improvement analysis on video compression using file segmentation

Science.gov (United States)

Sharma, Shubhankar; Singh, K. John; Priya, M.

2017-11-01

From the past two decades the extreme evolution of the Internet has lead a massive rise in video technology and significantly video consumption over the Internet which inhabits the bulk of data traffic in general. Clearly, video consumes that so much data size on the World Wide Web, to reduce the burden on the Internet and deduction of bandwidth consume by video so that the user can easily access the video data.For this, many video codecs are developed such as HEVC/H.265 and V9. Although after seeing codec like this one gets a dilemma of which would be improved technology in the manner of rate distortion and the coding standard.This paper gives a solution about the difficulty for getting low delay in video compression and video application e.g. ad-hoc video conferencing/streaming or observation by surveillance. Also this paper describes the benchmark of HEVC and V9 technique of video compression on subjective oral estimations of High Definition video content, playback on web browsers. Moreover, this gives the experimental ideology of dividing the video file into several segments for compression and putting back together to improve the efficiency of video compression on the web as well as on the offline mode.

B-Spline Active Contour with Handling of Topology Changes for Fast Video Segmentation

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Frederic Precioso

2002-06-01

Full Text Available This paper deals with video segmentation for MPEG-4 and MPEG-7 applications. Region-based active contour is a powerful technique for segmentation. However most of these methods are implemented using level sets. Although level-set methods provide accurate segmentation, they suffer from large computational cost. We propose to use a regular B-spline parametric method to provide a fast and accurate segmentation. Our B-spline interpolation is based on a fixed number of points 2j depending on the level of the desired details. Through this spatial multiresolution approach, the computational cost of the segmentation is reduced. We introduce a length penalty. This results in improving both smoothness and accuracy. Then we show some experiments on real-video sequences.

A new user-assisted segmentation and tracking technique for an object-based video editing system

Science.gov (United States)

Yu, Hong Y.; Hong, Sung-Hoon; Lee, Mike M.; Choi, Jae-Gark

2004-03-01

This paper presents a semi-automatic segmentation method which can be used to generate video object plane (VOP) for object based coding scheme and multimedia authoring environment. Semi-automatic segmentation can be considered as a user-assisted segmentation technique. A user can initially mark objects of interest around the object boundaries and then the user-guided and selected objects are continuously separated from the unselected areas through time evolution in the image sequences. The proposed segmentation method consists of two processing steps: partially manual intra-frame segmentation and fully automatic inter-frame segmentation. The intra-frame segmentation incorporates user-assistance to define the meaningful complete visual object of interest to be segmentation and decides precise object boundary. The inter-frame segmentation involves boundary and region tracking to obtain temporal coherence of moving object based on the object boundary information of previous frame. The proposed method shows stable efficient results that could be suitable for many digital video applications such as multimedia contents authoring, content based coding and indexing. Based on these results, we have developed objects based video editing system with several convenient editing functions.

Video quality pooling adaptive to perceptual distortion severity.

Science.gov (United States)

Park, Jincheol; Seshadrinathan, Kalpana; Lee, Sanghoon; Bovik, Alan Conrad

2013-02-01

It is generally recognized that severe video distortions that are transient in space and/or time have a large effect on overall perceived video quality. In order to understand this phenomena, we study the distribution of spatio-temporally local quality scores obtained from several video quality assessment (VQA) algorithms on videos suffering from compression and lossy transmission over communication channels. We propose a content adaptive spatial and temporal pooling strategy based on the observed distribution. Our method adaptively emphasizes "worst" scores along both the spatial and temporal dimensions of a video sequence and also considers the perceptual effect of large-area cohesive motion flow such as egomotion. We demonstrate the efficacy of the method by testing it using three different VQA algorithms on the LIVE Video Quality database and the EPFL-PoliMI video quality database.

Stochastic modeling of soundtrack for efficient segmentation and indexing of video

Science.gov (United States)

Naphade, Milind R.; Huang, Thomas S.

1999-12-01

Tools for efficient and intelligent management of digital content are essential for digital video data management. An extremely challenging research area in this context is that of multimedia analysis and understanding. The capabilities of audio analysis in particular for video data management are yet to be fully exploited. We present a novel scheme for indexing and segmentation of video by analyzing the audio track. This analysis is then applied to the segmentation and indexing of movies. We build models for some interesting events in the motion picture soundtrack. The models built include music, human speech and silence. We propose the use of hidden Markov models to model the dynamics of the soundtrack and detect audio-events. Using these models we segment and index the soundtrack. A practical problem in motion picture soundtracks is that the audio in the track is of a composite nature. This corresponds to the mixing of sounds from different sources. Speech in foreground and music in background are common examples. The coexistence of multiple individual audio sources forces us to model such events explicitly. Experiments reveal that explicit modeling gives better result than modeling individual audio events separately.

Adaptive format conversion for scalable video coding

Science.gov (United States)

Wan, Wade K.; Lim, Jae S.

2001-12-01

The enhancement layer in many scalable coding algorithms is composed of residual coding information. There is another type of information that can be transmitted instead of (or in addition to) residual coding. Since the encoder has access to the original sequence, it can utilize adaptive format conversion (AFC) to generate the enhancement layer and transmit the different format conversion methods as enhancement data. This paper investigates the use of adaptive format conversion information as enhancement data in scalable video coding. Experimental results are shown for a wide range of base layer qualities and enhancement bitrates to determine when AFC can improve video scalability. Since the parameters needed for AFC are small compared to residual coding, AFC can provide video scalability at low enhancement layer bitrates that are not possible with residual coding. In addition, AFC can also be used in addition to residual coding to improve video scalability at higher enhancement layer bitrates. Adaptive format conversion has not been studied in detail, but many scalable applications may benefit from it. An example of an application that AFC is well-suited for is the migration path for digital television where AFC can provide immediate video scalability as well as assist future migrations.

A System based on Adaptive Background Subtraction Approach for Moving Object Detection and Tracking in Videos

Directory of Open Access Journals (Sweden)

Bahadır KARASULU

2013-04-01

Full Text Available Video surveillance systems are based on video and image processing research areas in the scope of computer science. Video processing covers various methods which are used to browse the changes in existing scene for specific video. Nowadays, video processing is one of the important areas of computer science. Two-dimensional videos are used to apply various segmentation and object detection and tracking processes which exists in multimedia content-based indexing, information retrieval, visual and distributed cross-camera surveillance systems, people tracking, traffic tracking and similar applications. Background subtraction (BS approach is a frequently used method for moving object detection and tracking. In the literature, there exist similar methods for this issue. In this research study, it is proposed to provide a more efficient method which is an addition to existing methods. According to model which is produced by using adaptive background subtraction (ABS, an object detection and tracking system’s software is implemented in computer environment. The performance of developed system is tested via experimental works with related video datasets. The experimental results and discussion are given in the study

Candidate Smoke Region Segmentation of Fire Video Based on Rough Set Theory

Directory of Open Access Journals (Sweden)

Yaqin Zhao

2015-01-01

Full Text Available Candidate smoke region segmentation is the key link of smoke video detection; an effective and prompt method of candidate smoke region segmentation plays a significant role in a smoke recognition system. However, the interference of heavy fog and smoke-color moving objects greatly degrades the recognition accuracy. In this paper, a novel method of candidate smoke region segmentation based on rough set theory is presented. First, Kalman filtering is used to update video background in order to exclude the interference of static smoke-color objects, such as blue sky. Second, in RGB color space smoke regions are segmented by defining the upper approximation, lower approximation, and roughness of smoke-color distribution. Finally, in HSV color space small smoke regions are merged by the definition of equivalence relation so as to distinguish smoke images from heavy fog images in terms of V component value variety from center to edge of smoke region. The experimental results on smoke region segmentation demonstrated the effectiveness and usefulness of the proposed scheme.

User and Device Adaptation in Summarizing Sports Videos

Science.gov (United States)

Nitta, Naoko; Babaguchi, Noboru

Video summarization is defined as creating a video summary which includes only important scenes in the original video streams. In order to realize automatic video summarization, the significance of each scene needs to be determined. When targeted especially on broadcast sports videos, a play scene, which corresponds to a play, can be considered as a scene unit. The significance of every play scene can generally be determined based on the importance of the play in the game. Furthermore, the following two issues should be considered: 1) what is important depends on each user's preferences, and 2) the summaries should be tailored for media devices that each user has. Considering the above issues, this paper proposes a unified framework for user and device adaptation in summarizing broadcast sports videos. The proposed framework summarizes sports videos by selecting play scenes based on not only the importance of each play itself but also the users' preferences by using the metadata, which describes the semantic content of videos with keywords, and user profiles, which describe users' preference degrees for the keywords. The selected scenes are then presented in a proper way using various types of media such as video, image, or text according to device profiles which describe the device type. We experimentally verified the effectiveness of user adaptation by examining how the generated summaries are changed by different preference degrees and by comparing our results with/without using user profiles. The validity of device adaptation is also evaluated by conducting questionnaires using PCs and mobile phones as the media devices.

Distortion-Based Link Adaptation for Wireless Video Transmission

Directory of Open Access Journals (Sweden)

Andrew Nix

2008-06-01

Full Text Available Wireless local area networks (WLANs such as IEEE 802.11a/g utilise numerous transmission modes, each providing different throughputs and reliability levels. Most link adaptation algorithms proposed in the literature (i maximise the error-free data throughput, (ii do not take into account the content of the data stream, and (iii rely strongly on the use of ARQ. Low-latency applications, such as real-time video transmission, do not permit large numbers of retransmission. In this paper, a novel link adaptation scheme is presented that improves the quality of service (QoS for video transmission. Rather than maximising the error-free throughput, our scheme minimises the video distortion of the received sequence. With the use of simple and local rate distortion measures and end-to-end distortion models at the video encoder, the proposed scheme estimates the received video distortion at the current transmission rate, as well as on the adjacent lower and higher rates. This allows the system to select the link-speed which offers the lowest distortion and to adapt to the channel conditions. Simulation results are presented using the MPEG-4/AVC H.264 video compression standard over IEEE 802.11g. The results show that the proposed system closely follows the optimum theoretic solution.

Subjective Analysis and Objective Characterization of Adaptive Bitrate Videos

DEFF Research Database (Denmark)

Søgaard, Jacob; Tavakoli, Samira; Brunnström, Kjell

2016-01-01

The HTTP Adaptive Streaming (HAS) technology allows video service providers to improve the network utilization and thereby increasing the end-users’ Quality of Experience (QoE).This has made HAS a widely used approach for audiovisual delivery. There are several previous studies aiming to identify...... the factors influencing on subjective QoE of adaptation events.However, adapting the video quality typically lasts in a time scale much longer than what current standardized subjective testing methods are designed for, thus making the full matrix design of the experiment on an event level hard to achieve....... In this study, we investigated the overall subjective QoE of 6 minutes long video sequences containing different sequential adaptation events. This was compared to a data set from our previous work performed to evaluate the individual adaptation events. We could then derive a relationship between the overall...

In-network adaptation of SHVC video in software-defined networks

Science.gov (United States)

Awobuluyi, Olatunde; Nightingale, James; Wang, Qi; Alcaraz Calero, Jose Maria; Grecos, Christos

2016-04-01

Software Defined Networks (SDN), when combined with Network Function Virtualization (NFV) represents a paradigm shift in how future networks will behave and be managed. SDN's are expected to provide the underpinning technologies for future innovations such as 5G mobile networks and the Internet of Everything. The SDN architecture offers features that facilitate an abstracted and centralized global network view in which packet forwarding or dropping decisions are based on application flows. Software Defined Networks facilitate a wide range of network management tasks, including the adaptation of real-time video streams as they traverse the network. SHVC, the scalable extension to the recent H.265 standard is a new video encoding standard that supports ultra-high definition video streams with spatial resolutions of up to 7680×4320 and frame rates of 60fps or more. The massive increase in bandwidth required to deliver these U-HD video streams dwarfs the bandwidth requirements of current high definition (HD) video. Such large bandwidth increases pose very significant challenges for network operators. In this paper we go substantially beyond the limited number of existing implementations and proposals for video streaming in SDN's all of which have primarily focused on traffic engineering solutions such as load balancing. By implementing and empirically evaluating an SDN enabled Media Adaptation Network Entity (MANE) we provide a valuable empirical insight into the benefits and limitations of SDN enabled video adaptation for real time video applications. The SDN-MANE is the video adaptation component of our Video Quality Assurance Manager (VQAM) SDN control plane application, which also includes an SDN monitoring component to acquire network metrics and a decision making engine using algorithms to determine the optimum adaptation strategy for any real time video application flow given the current network conditions. Our proposed VQAM application has been implemented and

ROBUST MOTION SEGMENTATION FOR HIGH DEFINITION VIDEO SEQUENCES USING A FAST MULTI-RESOLUTION MOTION ESTIMATION BASED ON SPATIO-TEMPORAL TUBES

OpenAIRE

Brouard , Olivier; Delannay , Fabrice; Ricordel , Vincent; Barba , Dominique

2007-01-01

4 pages; International audience; Motion segmentation methods are effective for tracking video objects. However, objects segmentation methods based on motion need to know the global motion of the video in order to back-compensate it before computing the segmentation. In this paper, we propose a method which estimates the global motion of a High Definition (HD) video shot and then segments it using the remaining motion information. First, we develop a fast method for multi-resolution motion est...

GPU-Accelerated Foreground Segmentation and Labeling for Real-Time Video Surveillance

Directory of Open Access Journals (Sweden)

Wei Song

2016-09-01

Full Text Available Real-time and accurate background modeling is an important researching topic in the fields of remote monitoring and video surveillance. Meanwhile, effective foreground detection is a preliminary requirement and decision-making basis for sustainable energy management, especially in smart meters. The environment monitoring results provide a decision-making basis for energy-saving strategies. For real-time moving object detection in video, this paper applies a parallel computing technology to develop a feedback foreground–background segmentation method and a parallel connected component labeling (PCCL algorithm. In the background modeling method, pixel-wise color histograms in graphics processing unit (GPU memory is generated from sequential images. If a pixel color in the current image does not locate around the peaks of its histogram, it is segmented as a foreground pixel. From the foreground segmentation results, a PCCL algorithm is proposed to cluster the foreground pixels into several groups in order to distinguish separate blobs. Because the noisy spot and sparkle in the foreground segmentation results always contain a small quantity of pixels, the small blobs are removed as noise in order to refine the segmentation results. The proposed GPU-based image processing algorithms are implemented using the compute unified device architecture (CUDA toolkit. The testing results show a significant enhancement in both speed and accuracy.

Music video shot segmentation using independent component analysis and keyframe extraction based on image complexity

Science.gov (United States)

Li, Wei; Chen, Ting; Zhang, Wenjun; Shi, Yunyu; Li, Jun

2012-04-01

In recent years, Music video data is increasing at an astonishing speed. Shot segmentation and keyframe extraction constitute a fundamental unit in organizing, indexing, retrieving video content. In this paper a unified framework is proposed to detect the shot boundaries and extract the keyframe of a shot. Music video is first segmented to shots by illumination-invariant chromaticity histogram in independent component (IC) analysis feature space .Then we presents a new metric, image complexity, to extract keyframe in a shot which is computed by ICs. Experimental results show the framework is effective and has a good performance.

Scalable video on demand adaptive Internet-based distribution

CERN Document Server

Zink, Michael

2013-01-01

In recent years, the proliferation of available video content and the popularity of the Internet have encouraged service providers to develop new ways of distributing content to clients. Increasing video scaling ratios and advanced digital signal processing techniques have led to Internet Video-on-Demand applications, but these currently lack efficiency and quality. Scalable Video on Demand: Adaptive Internet-based Distribution examines how current video compression and streaming can be used to deliver high-quality applications over the Internet. In addition to analysing the problems

USABILITY TESTING OF JAPANESE CAPTIONS SEGMENTATION SYSTEM TO SCAFFOLD BEGINNERS TO COMPREHEND JAPANESE VIDEOS

Directory of Open Access Journals (Sweden)

Ya-Fei Yang

2013-06-01

Full Text Available A major learning difficulty of Japanese foreign language (JFL learners is the complex composition of two syllabaries, hiragana and katakana, and kanji characters adopted from logographic Chinese ones. As the number of Japanese language learners increases, computer-assisted Japanese language education gradually gains more attention. This study aimed to adopt a Japanese word segmentation system to help JFL learners overcome literacy problems. This study adopted MeCab, a Japanese morphological analyzer and part-of-speech (POS tagger, to segment Japanese texts into separate morphemes by adding spaces and to attach POS tags to each morpheme for beginners. The participants were asked to participate in three experimental activities involvingwatching two Japanese videos with general or segmented Japanese captions and complete the Nielsen’s Attributes of Usability (NAU survey and the After Scenario Questionnaire (ASQ to evaluate the usability of the learning activities. The results of the system evaluation showed that the videos with the segmented captions could increase the participants’ learning motivation and willingness to adopt the word segmentation system to learn Japanese.

Least-Square Prediction for Backward Adaptive Video Coding

Directory of Open Access Journals (Sweden)

Li Xin

2006-01-01

Full Text Available Almost all existing approaches towards video coding exploit the temporal redundancy by block-matching-based motion estimation and compensation. Regardless of its popularity, block matching still reflects an ad hoc understanding of the relationship between motion and intensity uncertainty models. In this paper, we present a novel backward adaptive approach, named "least-square prediction" (LSP, and demonstrate its potential in video coding. Motivated by the duality between edge contour in images and motion trajectory in video, we propose to derive the best prediction of the current frame from its causal past using least-square method. It is demonstrated that LSP is particularly effective for modeling video material with slow motion and can be extended to handle fast motion by temporal warping and forward adaptation. For typical QCIF test sequences, LSP often achieves smaller MSE than , full-search, quarter-pel block matching algorithm (BMA without the need of transmitting any overhead.

Research on quality metrics of wireless adaptive video streaming

Science.gov (United States)

Li, Xuefei

2018-04-01

With the development of wireless networks and intelligent terminals, video traffic has increased dramatically. Adaptive video streaming has become one of the most promising video transmission technologies. For this type of service, a good QoS (Quality of Service) of wireless network does not always guarantee that all customers have good experience. Thus, new quality metrics have been widely studies recently. Taking this into account, the objective of this paper is to investigate the quality metrics of wireless adaptive video streaming. In this paper, a wireless video streaming simulation platform with DASH mechanism and multi-rate video generator is established. Based on this platform, PSNR model, SSIM model and Quality Level model are implemented. Quality Level Model considers the QoE (Quality of Experience) factors such as image quality, stalling and switching frequency while PSNR Model and SSIM Model mainly consider the quality of the video. To evaluate the performance of these QoE models, three performance metrics (SROCC, PLCC and RMSE) which are used to make a comparison of subjective and predicted MOS (Mean Opinion Score) are calculated. From these performance metrics, the monotonicity, linearity and accuracy of these quality metrics can be observed.

Crowdsourcing based subjective quality assessment of adaptive video streaming

DEFF Research Database (Denmark)

Shahid, M.; Søgaard, Jacob; Pokhrel, J.

2014-01-01

In order to cater for user’s quality of experience (QoE) re- quirements, HTTP adaptive streaming (HAS) based solutions of video services have become popular recently. User QoE feedback can be instrumental in improving the capabilities of such services. Perceptual quality experiments that involve...... humans are considered to be the most valid method of the as- sessment of QoE. Besides lab-based subjective experiments, crowdsourcing based subjective assessment of video quality is gaining popularity as an alternative method. This paper presents insights into a study that investigates perceptual pref......- erences of various adaptive video streaming scenarios through crowdsourcing based subjective quality assessment....

Modeling the time--varying subjective quality of HTTP video streams with rate adaptations.

Science.gov (United States)

Chen, Chao; Choi, Lark Kwon; de Veciana, Gustavo; Caramanis, Constantine; Heath, Robert W; Bovik, Alan C

2014-05-01

Newly developed hypertext transfer protocol (HTTP)-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' quality of experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for online TVSQ prediction in HTTP-based streaming.

Segmentation of Pollen Tube Growth Videos Using Dynamic Bi-Modal Fusion and Seam Carving.

Science.gov (United States)

Tambo, Asongu L; Bhanu, Bir

2016-05-01

The growth of pollen tubes is of significant interest in plant cell biology, as it provides an understanding of internal cell dynamics that affect observable structural characteristics such as cell diameter, length, and growth rate. However, these parameters can only be measured in experimental videos if the complete shape of the cell is known. The challenge is to accurately obtain the cell boundary in noisy video images. Usually, these measurements are performed by a scientist who manually draws regions-of-interest on the images displayed on a computer screen. In this paper, a new automated technique is presented for boundary detection by fusing fluorescence and brightfield images, and a new efficient method of obtaining the final cell boundary through the process of Seam Carving is proposed. This approach takes advantage of the nature of the fusion process and also the shape of the pollen tube to efficiently search for the optimal cell boundary. In video segmentation, the first two frames are used to initialize the segmentation process by creating a search space based on a parametric model of the cell shape. Updates to the search space are performed based on the location of past segmentations and a prediction of the next segmentation.Experimental results show comparable accuracy to a previous method, but significant decrease in processing time. This has the potential for real time applications in pollen tube microscopy.

In-Network Adaptation of Video Streams Using Network Processors

Directory of Open Access Journals (Sweden)

Mohammad Shorfuzzaman

2009-01-01

problem can be addressed, near the network edge, by applying dynamic, in-network adaptation (e.g., transcoding of video streams to meet available connection bandwidth, machine characteristics, and client preferences. In this paper, we extrapolate from earlier work of Shorfuzzaman et al. 2006 in which we implemented and assessed an MPEG-1 transcoding system on the Intel IXP1200 network processor to consider the feasibility of in-network transcoding for other video formats and network processor architectures. The use of “on-the-fly” video adaptation near the edge of the network offers the promise of simpler support for a wide range of end devices with different display, and so forth, characteristics that can be used in different types of environments.

Adaptive geodesic transform for segmentation of vertebrae on CT images

Science.gov (United States)

Gaonkar, Bilwaj; Shu, Liao; Hermosillo, Gerardo; Zhan, Yiqiang

2014-03-01

Vertebral segmentation is a critical first step in any quantitative evaluation of vertebral pathology using CT images. This is especially challenging because bone marrow tissue has the same intensity profile as the muscle surrounding the bone. Thus simple methods such as thresholding or adaptive k-means fail to accurately segment vertebrae. While several other algorithms such as level sets may be used for segmentation any algorithm that is clinically deployable has to work in under a few seconds. To address these dual challenges we present here, a new algorithm based on the geodesic distance transform that is capable of segmenting the spinal vertebrae in under one second. To achieve this we extend the theory of the geodesic distance transforms proposed in1 to incorporate high level anatomical knowledge through adaptive weighting of image gradients. Such knowledge may be provided by the user directly or may be automatically generated by another algorithm. We incorporate information 'learnt' using a previously published machine learning algorithm2 to segment the L1 to L5 vertebrae. While we present a particular application here, the adaptive geodesic transform is a generic concept which can be applied to segmentation of other organs as well.

Applicability of Existing Objective Metrics of Perceptual Quality for Adaptive Video Streaming

DEFF Research Database (Denmark)

Søgaard, Jacob; Krasula, Lukás; Shahid, Muhammad

2016-01-01

Objective video quality metrics are designed to estimate the quality of experience of the end user. However, these objective metrics are usually validated with video streams degraded under common distortion types. In the presented work, we analyze the performance of published and known full......-reference and noreference quality metrics in estimating the perceived quality of adaptive bit-rate video streams knowingly out of scope. Experimental results indicate not surprisingly that state of the art objective quality metrics overlook the perceived degradations in the adaptive video streams and perform poorly...

A NDVI assisted remote sensing image adaptive scale segmentation method

Science.gov (United States)

Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

2018-03-01

Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.

Real-time recursive motion segmentation of video data on a programmable device

NARCIS (Netherlands)

Wittebrood, R.B; Haan, de G.

2001-01-01

We previously reported on a recursive algorithm enabling real-time object-based motion estimation (OME) of standard definition video on a digital signal processor (DSP). The algorithm approximates the motion of the objects in the image with parametric motion models and creates a segmentation mask by

Adaptive Motion Estimation Processor for Autonomous Video Devices

Directory of Open Access Journals (Sweden)

Dias T

2007-01-01

Full Text Available Motion estimation is the most demanding operation of a video encoder, corresponding to at least 80% of the overall computational cost. As a consequence, with the proliferation of autonomous and portable handheld devices that support digital video coding, data-adaptive motion estimation algorithms have been required to dynamically configure the search pattern not only to avoid unnecessary computations and memory accesses but also to save energy. This paper proposes an application-specific instruction set processor (ASIP to implement data-adaptive motion estimation algorithms that is characterized by a specialized datapath and a minimum and optimized instruction set. Due to its low-power nature, this architecture is highly suitable to develop motion estimators for portable, mobile, and battery-supplied devices. Based on the proposed architecture and the considered adaptive algorithms, several motion estimators were synthesized both for a Virtex-II Pro XC2VP30 FPGA from Xilinx, integrated within an ML310 development platform, and using a StdCell library based on a 0.18 μm CMOS process. Experimental results show that the proposed architecture is able to estimate motion vectors in real time for QCIF and CIF video sequences with a very low-power consumption. Moreover, it is also able to adapt the operation to the available energy level in runtime. By adjusting the search pattern and setting up a more convenient operating frequency, it can change the power consumption in the interval between 1.6 mW and 15 mW.

Segmented bimorph mirrors for adaptive optics: morphing strategy.

Science.gov (United States)

Bastaits, Renaud; Alaluf, David; Belloni, Edoardo; Rodrigues, Gonçalo; Preumont, André

2014-08-01

This paper discusses the concept of a light weight segmented bimorph mirror for adaptive optics. It focuses on the morphing strategy and addresses the ill-conditioning of the Jacobian of the segments, which are partly outside the optical pupil. Two options are discussed, one based on truncating the singular values and one called damped least squares, which minimizes a combined measure of the sensor error and the voltage vector. A comparison of various configurations of segmented mirrors was conducted; it is shown that segmentation sharply increases the natural frequency of the system with limited deterioration of the image quality.

An Attention-Information-Based Spatial Adaptation Framework for Browsing Videos via Mobile Devices

Directory of Open Access Journals (Sweden)

Li Houqiang

2007-01-01

Full Text Available With the growing popularity of personal digital assistant devices and smart phones, more and more consumers are becoming quite enthusiastic to appreciate videos via mobile devices. However, limited display size of the mobile devices has been imposing significant barriers for users to enjoy browsing high-resolution videos. In this paper, we present an attention-information-based spatial adaptation framework to address this problem. The whole framework includes two major parts: video content generation and video adaptation system. During video compression, the attention information in video sequences will be detected using an attention model and embedded into bitstreams with proposed supplement-enhanced information (SEI structure. Furthermore, we also develop an innovative scheme to adaptively adjust quantization parameters in order to simultaneously improve the quality of overall encoding and the quality of transcoding the attention areas. When the high-resolution bitstream is transmitted to mobile users, a fast transcoding algorithm we developed earlier will be applied to generate a new bitstream for attention areas in frames. The new low-resolution bitstream containing mostly attention information, instead of the high-resolution one, will be sent to users for display on the mobile devices. Experimental results show that the proposed spatial adaptation scheme is able to improve both subjective and objective video qualities.

A Complexity-Aware Video Adaptation Mechanism for Live Streaming Systems

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Chen Homer H

2007-01-01

Full Text Available The paradigm shift of network design from performance-centric to constraint-centric has called for new signal processing techniques to deal with various aspects of resource-constrained communication and networking. In this paper, we consider the computational constraints of a multimedia communication system and propose a video adaptation mechanism for live video streaming of multiple channels. The video adaptation mechanism includes three salient features. First, it adjusts the computational resource of the streaming server block by block to provide a fine control of the encoding complexity. Second, as far as we know, it is the first mechanism to allocate the computational resource to multiple channels. Third, it utilizes a complexity-distortion model to determine the optimal coding parameter values to achieve global optimization. These techniques constitute the basic building blocks for a successful application of wireless and Internet video to digital home, surveillance, IPTV, and online games.

A Complexity-Aware Video Adaptation Mechanism for Live Streaming Systems

Science.gov (United States)

Lu, Meng-Ting; Yao, Jason J.; Chen, Homer H.

2007-12-01

The paradigm shift of network design from performance-centric to constraint-centric has called for new signal processing techniques to deal with various aspects of resource-constrained communication and networking. In this paper, we consider the computational constraints of a multimedia communication system and propose a video adaptation mechanism for live video streaming of multiple channels. The video adaptation mechanism includes three salient features. First, it adjusts the computational resource of the streaming server block by block to provide a fine control of the encoding complexity. Second, as far as we know, it is the first mechanism to allocate the computational resource to multiple channels. Third, it utilizes a complexity-distortion model to determine the optimal coding parameter values to achieve global optimization. These techniques constitute the basic building blocks for a successful application of wireless and Internet video to digital home, surveillance, IPTV, and online games.

Content-Aware Scalability-Type Selection for Rate Adaptation of Scalable Video

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Tekalp A Murat

2007-01-01

Full Text Available Scalable video coders provide different scaling options, such as temporal, spatial, and SNR scalabilities, where rate reduction by discarding enhancement layers of different scalability-type results in different kinds and/or levels of visual distortion depend on the content and bitrate. This dependency between scalability type, video content, and bitrate is not well investigated in the literature. To this effect, we first propose an objective function that quantifies flatness, blockiness, blurriness, and temporal jerkiness artifacts caused by rate reduction by spatial size, frame rate, and quantization parameter scaling. Next, the weights of this objective function are determined for different content (shot types and different bitrates using a training procedure with subjective evaluation. Finally, a method is proposed for choosing the best scaling type for each temporal segment that results in minimum visual distortion according to this objective function given the content type of temporal segments. Two subjective tests have been performed to validate the proposed procedure for content-aware selection of the best scalability type on soccer videos. Soccer videos scaled from 600 kbps to 100 kbps by the proposed content-aware selection of scalability type have been found visually superior to those that are scaled using a single scalability option over the whole sequence.

Segmentation of the Speaker's Face Region with Audiovisual Correlation

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Liu, Yuyu; Sato, Yoichi

The ability to find the speaker's face region in a video is useful for various applications. In this work, we develop a novel technique to find this region within different time windows, which is robust against the changes of view, scale, and background. The main thrust of our technique is to integrate audiovisual correlation analysis into a video segmentation framework. We analyze the audiovisual correlation locally by computing quadratic mutual information between our audiovisual features. The computation of quadratic mutual information is based on the probability density functions estimated by kernel density estimation with adaptive kernel bandwidth. The results of this audiovisual correlation analysis are incorporated into graph cut-based video segmentation to resolve a globally optimum extraction of the speaker's face region. The setting of any heuristic threshold in this segmentation is avoided by learning the correlation distributions of speaker and background by expectation maximization. Experimental results demonstrate that our method can detect the speaker's face region accurately and robustly for different views, scales, and backgrounds.

Content-Adaptive Packetization and Streaming of Wavelet Video over IP Networks

Directory of Open Access Journals (Sweden)

Chien-Peng Ho

2007-03-01

Full Text Available This paper presents a framework of content-adaptive packetization scheme for streaming of 3D wavelet-based video content over lossy IP networks. The tradeoff between rate and distortion is controlled by jointly adapting scalable source coding rate and level of forward error correction (FEC protection. A content dependent packetization mechanism with data-interleaving and Reed-Solomon protection for wavelet-based video codecs is proposed to provide unequal error protection. This paper also tries to answer an important question for scalable video streaming systems: given extra bandwidth, should one increase the level of channel protection for the most important packets, or transmit more scalable source data? Experimental results show that the proposed framework achieves good balance between quality of the received video and level of error protection under bandwidth-varying lossy IP networks.

Video Object Segmentation through Spatially Accurate and Temporally Dense Extraction of Primary Object Regions (Open Access)

Science.gov (United States)

2013-10-03

fol- low the setup in the literature ([13, 14]), and use 5 (birdfall, cheetah , girl, monkeydog and parachute) of the videos for evaluation (since the...segmentation labeling results of the method, GT is the ground-truth labeling of the video, and F is the (a) Birdfall (b) Cheetah (c) Girl (d) Monkeydog...Video Ours [14] [13] [20] [6] birdfall 155 189 288 252 454 cheetah 633 806 905 1142 1217 girl 1488 1698 1785 1304 1755 monkeydog 365 472 521 563 683

Dynamic Post-Earthquake Image Segmentation with an Adaptive Spectral-Spatial Descriptor

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Genyun Sun

2017-08-01

Full Text Available The region merging algorithm is a widely used segmentation technique for very high resolution (VHR remote sensing images. However, the segmentation of post-earthquake VHR images is more difficult due to the complexity of these images, especially high intra-class and low inter-class variability among damage objects. Herein two key issues must be resolved: the first is to find an appropriate descriptor to measure the similarity of two adjacent regions since they exhibit high complexity among the diverse damage objects, such as landslides, debris flow, and collapsed buildings. The other is how to solve over-segmentation and under-segmentation problems, which are commonly encountered with conventional merging strategies due to their strong dependence on local information. To tackle these two issues, an adaptive dynamic region merging approach (ADRM is introduced, which combines an adaptive spectral-spatial descriptor and a dynamic merging strategy to adapt to the changes of merging regions for successfully detecting objects scattered globally in a post-earthquake image. In the new descriptor, the spectral similarity and spatial similarity of any two adjacent regions are automatically combined to measure their similarity. Accordingly, the new descriptor offers adaptive semantic descriptions for geo-objects and thus is capable of characterizing different damage objects. Besides, in the dynamic region merging strategy, the adaptive spectral-spatial descriptor is embedded in the defined testing order and combined with graph models to construct a dynamic merging strategy. The new strategy can find the global optimal merging order and ensures that the most similar regions are merged at first. With combination of the two strategies, ADRM can identify spatially scattered objects and alleviates the phenomenon of over-segmentation and under-segmentation. The performance of ADRM has been evaluated by comparing with four state-of-the-art segmentation methods

Adaptive deblocking and deringing of H.264/AVC video sequences

DEFF Research Database (Denmark)

Nadernejad, Ehsan; Burini, Nino; Forchhammer, Søren

2013-01-01

We present a method to reduce blocking and ringing artifacts in H.264/AVC video sequences. For deblocking, the proposed method uses a quality measure of a block based coded image to find filtering modes. Based on filtering modes, the images are segmented to three classes and a specific deblocking...

Remote Video Supervision in Adapted Physical Education

Science.gov (United States)

Kelly, Luke; Bishop, Jason

2013-01-01

Supervision for beginning adapted physical education (APE) teachers and inservice general physical education teachers who are learning to work with students with disabilities poses a number of challenges. The purpose of this article is to describe a project aimed at developing a remote video system that could be used by a university supervisor to…

Local Stereo Matching Using Adaptive Local Segmentation

NARCIS (Netherlands)

Damjanovic, S.; van der Heijden, Ferdinand; Spreeuwers, Lieuwe Jan

We propose a new dense local stereo matching framework for gray-level images based on an adaptive local segmentation using a dynamic threshold. We define a new validity domain of the fronto-parallel assumption based on the local intensity variations in the 4-neighborhood of the matching pixel. The

Video Segmentation Using Fast Marching and Region Growing Algorithms

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Eftychis Sifakis

2002-04-01

Full Text Available The algorithm presented in this paper is comprised of three main stages: (1 classification of the image sequence and, in the case of a moving camera, parametric motion estimation, (2 change detection having as reference a fixed frame, an appropriately selected frame or a displaced frame, and (3 object localization using local colour features. The image sequence classification is based on statistical tests on the frame difference. The change detection module uses a two-label fast marching algorithm. Finally, the object localization uses a region growing algorithm based on the colour similarity. Video object segmentation results are shown using the COST 211 data set.

Cross-layer optimized rate adaptation and scheduling for multiple-user wireless video streaming

NARCIS (Netherlands)

Ozcelebi, T.; Sunay, M.O.; Tekalp, A.M.; Civanlar, M.R.

2007-01-01

We present a cross-layer optimized video rate adaptation and user scheduling scheme for multi-user wireless video streaming aiming for maximum quality of service (QoS) for each user,, maximum system video throughput, and QoS fairness among users. These objectives are jointly optimized using a

SVC VIDEO STREAM ALLOCATION AND ADAPTATION IN HETEROGENEOUS NETWORK

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E. A. Pakulova

2016-07-01

Full Text Available The paper deals with video data transmission in format H.264/SVC standard with QoS requirements satisfaction. The Sender-Side Path Scheduling (SSPS algorithm and Sender-Side Video Adaptation (SSVA algorithm were developed. SSPS algorithm gives the possibility to allocate video traffic among several interfaces while SSVA algorithm dynamically changes the quality of video sequence in relation to QoS requirements. It was shown that common usage of two developed algorithms enables to aggregate throughput of access networks, increase parameters of Quality of Experience and decrease losses in comparison with Round Robin algorithm. For evaluation of proposed solution, the set-up was made. The trace files with throughput of existing public networks were used in experiments. Based on this information the throughputs of networks were limited and losses for paths were set. The results of research may be used for study and transmission of video data in heterogeneous wireless networks.

Video Game Adapts To Brain Waves

Science.gov (United States)

Pope, Alan T.; Bogart, Edward H.

1994-01-01

Electronic training system based on video game developed to help children afflicted with attention-deficit disorder (ADD) learn to prolong their attention spans. Uses combination of electroencephalography (EEG) and adaptive control to encourage attentiveness. Monitors trainee's brain-wave activity: if EEG signal indicates attention is waning, system increases difficulty of game, forcing trainee to devote more attention to it. Game designed to make trainees want to win and, in so doing, learn to pay attention for longer times.

Hybrid video-assisted thoracic surgery with segmental-main bronchial sleeve resection for non-small cell lung cancer.

Science.gov (United States)

Li, Shuben; Chai, Huiping; Huang, Jun; Zeng, Guangqiao; Shao, Wenlong; He, Jianxing

2014-04-01

The purpose of the current study is to present the clinical and surgical results in patients who underwent hybrid video-assisted thoracic surgery with segmental-main bronchial sleeve resection. Thirty-one patients, 27 men and 4 women, underwent segmental-main bronchial sleeve anastomoses for non-small cell lung cancer between May 2004 and May 2011. Twenty-six (83.9%) patients had squamous cell carcinoma, and 5 patients had adenocarcinoma. Six patients were at stage IIB, 24 patients at stage IIIA, and 1 patient at stage IIIB. Secondary sleeve anastomosis was performed in 18 patients, and Y-shaped multiple sleeve anastomosis was performed in 8 patients. Single segmental bronchiole anastomosis was performed in 5 cases. The average time for chest tube removal was 5.6 days. The average length of hospital stay was 11.8 days. No anastomosis fistula developed in any of the patients. The 1-, 2-, and 3-year survival rates were 83.9%, 71.0%, and 41.9%, respectively. Hybrid video-assisted thoracic surgery with segmental-main bronchial sleeve resection is a complex technique that requires training and experience, but it is an effective and safe operation for selected patients.

Quality Assessment of Adaptive Bitrate Videos using Image Metrics and Machine Learning

DEFF Research Database (Denmark)

Søgaard, Jacob; Forchhammer, Søren; Brunnström, Kjell

2015-01-01

Adaptive bitrate (ABR) streaming is widely used for distribution of videos over the internet. In this work, we investigate how well we can predict the quality of such videos using well-known image metrics, information about the bitrate levels, and a relatively simple machine learning method...

AdOn HDP-HMM: An Adaptive Online Model for Segmentation and Classification of Sequential Data.

Science.gov (United States)

Bargi, Ava; Xu, Richard Yi Da; Piccardi, Massimo

2017-09-21

Recent years have witnessed an increasing need for the automated classification of sequential data, such as activities of daily living, social media interactions, financial series, and others. With the continuous flow of new data, it is critical to classify the observations on-the-fly and without being limited by a predetermined number of classes. In addition, a model should be able to update its parameters in response to a possible evolution in the distributions of the classes. This compelling problem, however, does not seem to have been adequately addressed in the literature, since most studies focus on offline classification over predefined class sets. In this paper, we present a principled solution for this problem based on an adaptive online system leveraging Markov switching models and hierarchical Dirichlet process priors. This adaptive online approach is capable of classifying the sequential data over an unlimited number of classes while meeting the memory and delay constraints typical of streaming contexts. In this paper, we introduce an adaptive ''learning rate'' that is responsible for balancing the extent to which the model retains its previous parameters or adapts to new observations. Experimental results on stationary and evolving synthetic data and two video data sets, TUM Assistive Kitchen and collated Weizmann, show a remarkable performance in terms of segmentation and classification, particularly for sequences from evolutionary distributions and/or those containing previously unseen classes.

Background-Modeling-Based Adaptive Prediction for Surveillance Video Coding.

Science.gov (United States)

Zhang, Xianguo; Huang, Tiejun; Tian, Yonghong; Gao, Wen

2014-02-01

The exponential growth of surveillance videos presents an unprecedented challenge for high-efficiency surveillance video coding technology. Compared with the existing coding standards that were basically developed for generic videos, surveillance video coding should be designed to make the best use of the special characteristics of surveillance videos (e.g., relative static background). To do so, this paper first conducts two analyses on how to improve the background and foreground prediction efficiencies in surveillance video coding. Following the analysis results, we propose a background-modeling-based adaptive prediction (BMAP) method. In this method, all blocks to be encoded are firstly classified into three categories. Then, according to the category of each block, two novel inter predictions are selectively utilized, namely, the background reference prediction (BRP) that uses the background modeled from the original input frames as the long-term reference and the background difference prediction (BDP) that predicts the current data in the background difference domain. For background blocks, the BRP can effectively improve the prediction efficiency using the higher quality background as the reference; whereas for foreground-background-hybrid blocks, the BDP can provide a better reference after subtracting its background pixels. Experimental results show that the BMAP can achieve at least twice the compression ratio on surveillance videos as AVC (MPEG-4 Advanced Video Coding) high profile, yet with a slightly additional encoding complexity. Moreover, for the foreground coding performance, which is crucial to the subjective quality of moving objects in surveillance videos, BMAP also obtains remarkable gains over several state-of-the-art methods.

On subjective quality assessment of adaptive video streaming via crowdsourcing and laboratory based experiments

DEFF Research Database (Denmark)

Søgaard, Jacob; Shahid, Muhammad; Pokhrel, Jeevan

2017-01-01

Video streaming services are offered over the Internet and since the service providers do not have full control over the network conditions all the way to the end user, streaming technologies have been developed to maintain the quality of service in these varying network conditions i.e. so called...... adaptive video streaming. In order to cater for users' Quality of Experience (QoE) requirements, HTTP based adaptive streaming solutions of video services have become popular. However, the keys to ensure the users a good QoE with this technology is still not completely understood. User QoE feedback...

Scalable Video Streaming Adaptive to Time-Varying IEEE 802.11 MAC Parameters

Science.gov (United States)

Lee, Kyung-Jun; Suh, Doug-Young; Park, Gwang-Hoon; Huh, Jae-Doo

This letter proposes a QoS control method for video streaming service over wireless networks. Based on statistical analysis, the time-varying MAC parameters highly related to channel condition are selected to predict available bitrate. Adaptive bitrate control of scalably-encoded video guarantees continuity in streaming service even if the channel condition changes abruptly.

Cross-Layer Techniques for Adaptive Video Streaming over Wireless Networks

Directory of Open Access Journals (Sweden)

Yufeng Shan

2005-02-01

Full Text Available Real-time streaming media over wireless networks is a challenging proposition due to the characteristics of video data and wireless channels. In this paper, we propose a set of cross-layer techniques for adaptive real-time video streaming over wireless networks. The adaptation is done with respect to both channel and data. The proposed novel packetization scheme constructs the application layer packet in such a way that it is decomposed exactly into an integer number of equal-sized radio link protocol (RLP packets. FEC codes are applied within an application packet at the RLP packet level rather than across different application packets and thus reduce delay at the receiver. A priority-based ARQ, together with a scheduling algorithm, is applied at the application layer to retransmit only the corrupted RLP packets within an application layer packet. Our approach combines the flexibility and programmability of application layer adaptations, with low delay and bandwidth efficiency of link layer techniques. Socket-level simulations are presented to verify the effectiveness of our approach.

Video segmentation for post-production

Science.gov (United States)

Wills, Ciaran

2001-12-01

Specialist post-production is an industry that has much to gain from the application of content-based video analysis techniques. However the types of material handled in specialist post-production, such as television commercials, pop music videos and special effects are quite different in nature from the typical broadcast material which many video analysis techniques are designed to work with; shots are short and highly dynamic, and the transitions are often novel or ambiguous. We address the problem of scene change detection and develop a new algorithm which tackles some of the common aspects of post-production material that cause difficulties for past algorithms, such as illumination changes and jump cuts. Operating in the compressed domain on Motion JPEG compressed video, our algorithm detects cuts and fades by analyzing each JPEG macroblock in the context of its temporal and spatial neighbors. Analyzing the DCT coefficients directly we can extract the mean color of a block and an approximate detail level. We can also perform an approximated cross-correlation between two blocks. The algorithm is part of a set of tools being developed to work with an automated asset management system designed specifically for use in post-production facilities.

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.

Temporal Segmentation of MPEG Video Streams

Directory of Open Access Journals (Sweden)

Janko Calic

2002-06-01

Full Text Available Many algorithms for temporal video partitioning rely on the analysis of uncompressed video features. Since the information relevant to the partitioning process can be extracted directly from the MPEG compressed stream, higher efficiency can be achieved utilizing information from the MPEG compressed domain. This paper introduces a real-time algorithm for scene change detection that analyses the statistics of the macroblock features extracted directly from the MPEG stream. A method for extraction of the continuous frame difference that transforms the 3D video stream into a 1D curve is presented. This transform is then further employed to extract temporal units within the analysed video sequence. Results of computer simulations are reported.

Hierarchical video summarization based on context clustering

Science.gov (United States)

Tseng, Belle L.; Smith, John R.

2003-11-01

A personalized video summary is dynamically generated in our video personalization and summarization system based on user preference and usage environment. The three-tier personalization system adopts the server-middleware-client architecture in order to maintain, select, adapt, and deliver rich media content to the user. The server stores the content sources along with their corresponding MPEG-7 metadata descriptions. In this paper, the metadata includes visual semantic annotations and automatic speech transcriptions. Our personalization and summarization engine in the middleware selects the optimal set of desired video segments by matching shot annotations and sentence transcripts with user preferences. Besides finding the desired contents, the objective is to present a coherent summary. There are diverse methods for creating summaries, and we focus on the challenges of generating a hierarchical video summary based on context information. In our summarization algorithm, three inputs are used to generate the hierarchical video summary output. These inputs are (1) MPEG-7 metadata descriptions of the contents in the server, (2) user preference and usage environment declarations from the user client, and (3) context information including MPEG-7 controlled term list and classification scheme. In a video sequence, descriptions and relevance scores are assigned to each shot. Based on these shot descriptions, context clustering is performed to collect consecutively similar shots to correspond to hierarchical scene representations. The context clustering is based on the available context information, and may be derived from domain knowledge or rules engines. Finally, the selection of structured video segments to generate the hierarchical summary efficiently balances between scene representation and shot selection.

Pupil-segmentation-based adaptive optics for microscopy

Science.gov (United States)

Ji, Na; Milkie, Daniel E.; Betzig, Eric

2011-03-01

Inhomogeneous optical properties of biological samples make it difficult to obtain diffraction-limited resolution in depth. Correcting the sample-induced optical aberrations needs adaptive optics (AO). However, the direct wavefront-sensing approach commonly used in astronomy is not suitable for most biological samples due to their strong scattering of light. We developed an image-based AO approach that is insensitive to sample scattering. By comparing images of the sample taken with different segments of the pupil illuminated, local tilt in the wavefront is measured from image shift. The aberrated wavefront is then obtained either by measuring the local phase directly using interference or with phase reconstruction algorithms similar to those used in astronomical AO. We implemented this pupil-segmentation-based approach in a two-photon fluorescence microscope and demonstrated that diffraction-limited resolution can be recovered from nonbiological and biological samples.

An Adaptive Motion Estimation Scheme for Video Coding

Directory of Open Access Journals (Sweden)

Pengyu Liu

2014-01-01

Full Text Available The unsymmetrical-cross multihexagon-grid search (UMHexagonS is one of the best fast Motion Estimation (ME algorithms in video encoding software. It achieves an excellent coding performance by using hybrid block matching search pattern and multiple initial search point predictors at the cost of the computational complexity of ME increased. Reducing time consuming of ME is one of the key factors to improve video coding efficiency. In this paper, we propose an adaptive motion estimation scheme to further reduce the calculation redundancy of UMHexagonS. Firstly, new motion estimation search patterns have been designed according to the statistical results of motion vector (MV distribution information. Then, design a MV distribution prediction method, including prediction of the size of MV and the direction of MV. At last, according to the MV distribution prediction results, achieve self-adaptive subregional searching by the new estimation search patterns. Experimental results show that more than 50% of total search points are dramatically reduced compared to the UMHexagonS algorithm in JM 18.4 of H.264/AVC. As a result, the proposed algorithm scheme can save the ME time up to 20.86% while the rate-distortion performance is not compromised.

Part Two: Learning Science Through Digital Video: Student Views on Watching and Creating Videos

Science.gov (United States)

Wade, P.; Courtney, A. R.

2014-12-01

The use of digital video for science education has become common with the wide availability of video imagery. This study continues research into aspects of using digital video as a primary teaching tool to enhance student learning in undergraduate science courses. Two survey instruments were administered to undergraduate non-science majors. Survey One focused on: a) What science is being learned from watching science videos such as a "YouTube" clip of a volcanic eruption or an informational video on geologic time and b) What are student preferences with regard to their learning (e.g. using video versus traditional modes of delivery)? Survey Two addressed students' perspectives on the storytelling aspect of the video with respect to: a) sustaining interest, b) providing science information, c) style of video and d) quality of the video. Undergraduate non-science majors were the primary focus group in this study. Students were asked to view video segments and respond to a survey focused on what they learned from the segments. The storytelling aspect of each video was also addressed by students. Students watched 15-20 shorter (3-15 minute science videos) created within the last four years. Initial results of this research support that shorter video segments were preferred and the storytelling quality of each video related to student learning.

Unequal Protection of Video Streaming through Adaptive Modulation with a Trizone Buffer over Bluetooth Enhanced Data Rate

Directory of Open Access Journals (Sweden)

Razavi Rouzbeh

2008-01-01

Full Text Available Abstract Bluetooth enhanced data rate wireless channel can support higher-quality video streams compared to previous versions of Bluetooth. Packet loss when transmitting compressed data has an effect on the delivered video quality that endures over multiple frames. To reduce the impact of radio frequency noise and interference, this paper proposes adaptive modulation based on content type at the video frame level and content importance at the macroblock level. Because the bit rate of protected data is reduced, the paper proposes buffer management to reduce the risk of buffer overflow. A trizone buffer is introduced, with a varying unequal protection policy in each zone. Application of this policy together with adaptive modulation results in up to 4 dB improvement in objective video quality compared to fixed rate scheme for an additive white Gaussian noise channel and around 10 dB for a Gilbert-Elliott channel. The paper also reports a consistent improvement in video quality over a scheme that adapts to channel conditions by varying the data rate without accounting for the video frame packet type or buffer congestion.

Unequal Protection of Video Streaming through Adaptive Modulation with a Trizone Buffer over Bluetooth Enhanced Data Rate

Directory of Open Access Journals (Sweden)

Rouzbeh Razavi

2007-12-01

Full Text Available Bluetooth enhanced data rate wireless channel can support higher-quality video streams compared to previous versions of Bluetooth. Packet loss when transmitting compressed data has an effect on the delivered video quality that endures over multiple frames. To reduce the impact of radio frequency noise and interference, this paper proposes adaptive modulation based on content type at the video frame level and content importance at the macroblock level. Because the bit rate of protected data is reduced, the paper proposes buffer management to reduce the risk of buffer overflow. A trizone buffer is introduced, with a varying unequal protection policy in each zone. Application of this policy together with adaptive modulation results in up to 4 dB improvement in objective video quality compared to fixed rate scheme for an additive white Gaussian noise channel and around 10 dB for a Gilbert-Elliott channel. The paper also reports a consistent improvement in video quality over a scheme that adapts to channel conditions by varying the data rate without accounting for the video frame packet type or buffer congestion.

Context adaptive binary arithmetic coding-based data hiding in partially encrypted H.264/AVC videos

Science.gov (United States)

Xu, Dawen; Wang, Rangding

2015-05-01

A scheme of data hiding directly in a partially encrypted version of H.264/AVC videos is proposed which includes three parts, i.e., selective encryption, data embedding and data extraction. Selective encryption is performed on context adaptive binary arithmetic coding (CABAC) bin-strings via stream ciphers. By careful selection of CABAC entropy coder syntax elements for selective encryption, the encrypted bitstream is format-compliant and has exactly the same bit rate. Then a data-hider embeds the additional data into partially encrypted H.264/AVC videos using a CABAC bin-string substitution technique without accessing the plaintext of the video content. Since bin-string substitution is carried out on those residual coefficients with approximately the same magnitude, the quality of the decrypted video is satisfactory. Video file size is strictly preserved even after data embedding. In order to adapt to different application scenarios, data extraction can be done either in the encrypted domain or in the decrypted domain. Experimental results have demonstrated the feasibility and efficiency of the proposed scheme.

Learning Motivation and Adaptive Video Caption Filtering for EFL Learners Using Handheld Devices

Science.gov (United States)

Hsu, Ching-Kun

2015-01-01

The aim of this study was to provide adaptive assistance to improve the listening comprehension of eleventh grade students. This study developed a video-based language learning system for handheld devices, using three levels of caption filtering adapted to student needs. Elementary level captioning excluded 220 English sight words (see Section 1…

Magnet system optimization for segmented adaptive-gap in-vacuum undulator

Energy Technology Data Exchange (ETDEWEB)

Kitegi, C., E-mail: ckitegi@bnl.gov; Chubar, O.; Eng, C. [Energy Sciences Directorates, Brookhaven National Laboratory, Upton NY1 1973 (United States)

2016-07-27

Segmented Adaptive Gap in-vacuum Undulator (SAGU), in which different segments have different gaps and periods, promises a considerable spectral performance gain over a conventional undulator with uniform gap and period. According to calculations, this gain can be comparable to the gain achievable with a superior undulator technology (e.g. a room-temperature in-vacuum hybrid SAGU would perform as a cryo-cooled hybrid in-vacuum undulator with uniform gap and period). However, for reaching the high spectral performance, SAGU magnetic design has to include compensation of kicks experienced by the electron beam at segment junctions because of different deflection parameter values in the segments. We show that such compensation to large extent can be accomplished by using a passive correction, however, simple correction coils are nevertheless required as well to reach perfect compensation over a whole SAGU tuning range. Magnetic optimizations performed with Radia code, and the resulting undulator radiation spectra calculated using SRW code, demonstrating a possibility of nearly perfect correction, are presented.

Segmentation of sows in farrowing pens

DEFF Research Database (Denmark)

Tu, Gang Jun; Karstoft, Henrik; Pedersen, Lene Juul

2014-01-01

The correct segmentation of a foreground object in video recordings is an important task for many surveillance systems. The development of an effective and practical algorithm to segment sows in grayscale video recordings captured under commercial production conditions is described...

Segmentation of object-based video of gaze communication

DEFF Research Database (Denmark)

Aghito, Shankar Manuel; Stegmann, Mikkel Bille; Forchhammer, Søren

2005-01-01

Aspects of video communication based on gaze interaction are considered. The overall idea is to use gaze interaction to control video, e.g. for video conferencing. Towards this goal, animation of a facial mask is demonstrated. The animation is based on images using Active Appearance Models (AAM......). Good quality reproduction of (low-resolution) coded video of an animated facial mask as low as 10-20 kbit/s using MPEG-4 object based video is demonstated....

Neonatal Brain Tissue Classification with Morphological Adaptation and Unified Segmentation

Directory of Open Access Journals (Sweden)

Richard eBeare

2016-03-01

Full Text Available Measuring the distribution of brain tissue types (tissue classification in neonates is necessary for studying typical and atypical brain development, such as that associated with preterm birth, and may provide biomarkers for neurodevelopmental outcomes. Compared with magnetic resonance images of adults, neonatal images present specific challenges that require the development of specialized, population-specific methods. This paper introduces MANTiS (Morphologically Adaptive Neonatal Tissue Segmentation, which extends the unified segmentation approach to tissue classification implemented in Statistical Parametric Mapping (SPM software to neonates. MANTiS utilizes a combination of unified segmentation, template adaptation via morphological segmentation tools and topological filtering, to segment the neonatal brain into eight tissue classes: cortical gray matter, white matter, deep nuclear gray matter, cerebellum, brainstem, cerebrospinal fluid (CSF, hippocampus and amygdala. We evaluated the performance of MANTiS using two independent datasets. The first dataset, provided by the NeoBrainS12 challenge, consisted of coronal T2-weighted images of preterm infants (born ≤30 weeks’ gestation acquired at 30 weeks’ corrected gestational age (n= 5, coronal T2-weighted images of preterm infants acquired at 40 weeks’ corrected gestational age (n= 5 and axial T2-weighted images of preterm infants acquired at 40 weeks’ corrected gestational age (n= 5. The second dataset, provided by the Washington University NeuroDevelopmental Research (WUNDeR group, consisted of T2-weighted images of preterm infants (born <30 weeks’ gestation acquired shortly after birth (n= 12, preterm infants acquired at term-equivalent age (n= 12, and healthy term-born infants (born ≥38 weeks’ gestation acquired within the first nine days of life (n= 12. For the NeoBrainS12 dataset, mean Dice scores comparing MANTiS with manual segmentations were all above 0.7, except for

Research on a Pulmonary Nodule Segmentation Method Combining Fast Self-Adaptive FCM and Classification

Directory of Open Access Journals (Sweden)

Hui Liu

2015-01-01

Full Text Available The key problem of computer-aided diagnosis (CAD of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO pulmonary nodules than other typical algorithms.

HIERARCHICAL ADAPTIVE ROOD PATTERN SEARCH FOR MOTION ESTIMATION AT VIDEO SEQUENCE ANALYSIS

Directory of Open Access Journals (Sweden)

V. T. Nguyen

2016-05-01

Full Text Available Subject of Research.The paper deals with the motion estimation algorithms for the analysis of video sequences in compression standards MPEG-4 Visual and H.264. Anew algorithm has been offered based on the analysis of the advantages and disadvantages of existing algorithms. Method. Thealgorithm is called hierarchical adaptive rood pattern search (Hierarchical ARPS, HARPS. This new algorithm includes the classic adaptive rood pattern search ARPS and hierarchical search MP (Hierarchical search or Mean pyramid. All motion estimation algorithms have been implemented using MATLAB package and tested with several video sequences. Main Results. The criteria for evaluating the algorithms were: speed, peak signal to noise ratio, mean square error and mean absolute deviation. The proposed method showed a much better performance at a comparable error and deviation. The peak signal to noise ratio in different video sequences shows better and worse results than characteristics of known algorithms so it requires further investigation. Practical Relevance. Application of this algorithm in MPEG-4 and H.264 codecs instead of the standard can significantly reduce compression time. This feature enables to recommend it in telecommunication systems for multimedia data storing, transmission and processing.

Minimizing the impact of delay on live SVC-based HTTP adaptive streaming services

OpenAIRE

Bouten, Niels; Latré, Steven; Famaey, Jeroen; Van Leekwijck, W; De Turck, Filip

2013-01-01

HTTP Adaptive Streaming (HAS) is becoming the de-facto standard for Over-The-Top video streaming services. Video content is temporally split into segments which are offered at multiple qualities to the clients. These clients autonomously select the quality layer matching the current state of the network through a quality selection heuristic. Recently, academia and industry have begun evaluating the feasibility of adopting layered video coding for HAS. Instead of downloading one file for a cer...

Hierarchical video summarization

Science.gov (United States)

Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.

1998-12-01

We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.

Adaptive rate selection scheme for video transmission to resolve IEEE 802.11 performance anomaly

Science.gov (United States)

Tang, Guijin; Zhu, Xiuchang

2011-10-01

Multi-rate transmission may lead to performance anomaly in an IEEE 802.11 network. It will decrease the throughputs of all the higher rate stations. This paper proposes an adaptive rate selection scheme for video service when performance anomaly occurs. Considering that video has the characteristic of tolerance to packet loss, we actively drop several packets so as to select the rates as high as possible for transmitting packets. Experiment shows our algorithm can decrease the delay and jitter of video, and improve the system throughput as well.

Learning to Segment Human by Watching YouTube.

Science.gov (United States)

Liang, Xiaodan; Wei, Yunchao; Chen, Yunpeng; Shen, Xiaohui; Yang, Jianchao; Lin, Liang; Yan, Shuicheng

2016-08-05

An intuition on human segmentation is that when a human is moving in a video, the video-context (e.g., appearance and motion clues) may potentially infer reasonable mask information for the whole human body. Inspired by this, based on popular deep convolutional neural networks (CNN), we explore a very-weakly supervised learning framework for human segmentation task, where only an imperfect human detector is available along with massive weakly-labeled YouTube videos. In our solution, the video-context guided human mask inference and CNN based segmentation network learning iterate to mutually enhance each other until no further improvement gains. In the first step, each video is decomposed into supervoxels by the unsupervised video segmentation. The superpixels within the supervoxels are then classified as human or non-human by graph optimization with unary energies from the imperfect human detection results and the predicted confidence maps by the CNN trained in the previous iteration. In the second step, the video-context derived human masks are used as direct labels to train CNN. Extensive experiments on the challenging PASCAL VOC 2012 semantic segmentation benchmark demonstrate that the proposed framework has already achieved superior results than all previous weakly-supervised methods with object class or bounding box annotations. In addition, by augmenting with the annotated masks from PASCAL VOC 2012, our method reaches a new stateof- the-art performance on the human segmentation task.

Automatic video segmentation employing object/camera modeling techniques

NARCIS (Netherlands)

Farin, D.S.

2005-01-01

Practically established video compression and storage techniques still process video sequences as rectangular images without further semantic structure. However, humans watching a video sequence immediately recognize acting objects as semantic units. This semantic object separation is currently not

Roadside video data analysis deep learning

CERN Document Server

Verma, Brijesh; Stockwell, David

2017-01-01

This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning concepts for roadside video data processing, and offers a detailed analysis of the segmentation, feature extraction and classification processes. Lastly, it demonstrates the applications of roadside video data analysis including scene labelling, roadside vegetation classification and vegetation biomass estimation in fire risk assessment.

Dosimetric Evaluation of Automatic Segmentation for Adaptive IMRT for Head-and-Neck Cancer

International Nuclear Information System (INIS)

Tsuji, Stuart Y.; Hwang, Andrew; Weinberg, Vivian; Yom, Sue S.; Quivey, Jeanne M.; Xia Ping

2010-01-01

Purpose: Adaptive planning to accommodate anatomic changes during treatment requires repeat segmentation. This study uses dosimetric endpoints to assess automatically deformed contours. Methods and Materials: Sixteen patients with head-and-neck cancer had adaptive plans because of anatomic change during radiotherapy. Contours from the initial planning computed tomography (CT) were deformed to the mid-treatment CT using an intensity-based free-form registration algorithm then compared with the manually drawn contours for the same CT using the Dice similarity coefficient and an overlap index. The automatic contours were used to create new adaptive plans. The original and automatic adaptive plans were compared based on dosimetric outcomes of the manual contours and on plan conformality. Results: Volumes from the manual and automatic segmentation were similar; only the gross tumor volume (GTV) was significantly different. Automatic plans achieved lower mean coverage for the GTV: V95: 98.6 ± 1.9% vs. 89.9 ± 10.1% (p = 0.004) and clinical target volume: V95: 98.4 ± 0.8% vs. 89.8 ± 6.2% (p 3 of the spinal cord 39.9 ± 3.7 Gy vs. 42.8 ± 5.4 Gy (p = 0.034), but no difference for the remaining structures. Conclusions: Automatic segmentation is not robust enough to substitute for physician-drawn volumes, particularly for the GTV. However, it generates normal structure contours of sufficient accuracy when assessed by dosimetric end points.

Adaptive Breast Radiation Therapy Using Modeling of Tissue Mechanics: A Breast Tissue Segmentation Study

International Nuclear Information System (INIS)

Juneja, Prabhjot; Harris, Emma J.; Kirby, Anna M.; Evans, Philip M.

2012-01-01

Purpose: To validate and compare the accuracy of breast tissue segmentation methods applied to computed tomography (CT) scans used for radiation therapy planning and to study the effect of tissue distribution on the segmentation accuracy for the purpose of developing models for use in adaptive breast radiation therapy. Methods and Materials: Twenty-four patients receiving postlumpectomy radiation therapy for breast cancer underwent CT imaging in prone and supine positions. The whole-breast clinical target volume was outlined. Clinical target volumes were segmented into fibroglandular and fatty tissue using the following algorithms: physical density thresholding; interactive thresholding; fuzzy c-means with 3 classes (FCM3) and 4 classes (FCM4); and k-means. The segmentation algorithms were evaluated in 2 stages: first, an approach based on the assumption that the breast composition should be the same in both prone and supine position; and second, comparison of segmentation with tissue outlines from 3 experts using the Dice similarity coefficient (DSC). Breast datasets were grouped into nonsparse and sparse fibroglandular tissue distributions according to expert assessment and used to assess the accuracy of the segmentation methods and the agreement between experts. Results: Prone and supine breast composition analysis showed differences between the methods. Validation against expert outlines found significant differences (P<.001) between FCM3 and FCM4. Fuzzy c-means with 3 classes generated segmentation results (mean DSC = 0.70) closest to the experts' outlines. There was good agreement (mean DSC = 0.85) among experts for breast tissue outlining. Segmentation accuracy and expert agreement was significantly higher (P<.005) in the nonsparse group than in the sparse group. Conclusions: The FCM3 gave the most accurate segmentation of breast tissues on CT data and could therefore be used in adaptive radiation therapy-based on tissue modeling. Breast tissue segmentation

Adaptive Breast Radiation Therapy Using Modeling of Tissue Mechanics: A Breast Tissue Segmentation Study

Energy Technology Data Exchange (ETDEWEB)

Juneja, Prabhjot, E-mail: Prabhjot.Juneja@icr.ac.uk [Joint Department of Physics, Institute of Cancer Research, Sutton (United Kingdom); Harris, Emma J. [Joint Department of Physics, Institute of Cancer Research, Sutton (United Kingdom); Kirby, Anna M. [Department of Academic Radiotherapy, Royal Marsden National Health Service Foundation Trust, Sutton (United Kingdom); Evans, Philip M. [Joint Department of Physics, Institute of Cancer Research, Sutton (United Kingdom)

2012-11-01

Purpose: To validate and compare the accuracy of breast tissue segmentation methods applied to computed tomography (CT) scans used for radiation therapy planning and to study the effect of tissue distribution on the segmentation accuracy for the purpose of developing models for use in adaptive breast radiation therapy. Methods and Materials: Twenty-four patients receiving postlumpectomy radiation therapy for breast cancer underwent CT imaging in prone and supine positions. The whole-breast clinical target volume was outlined. Clinical target volumes were segmented into fibroglandular and fatty tissue using the following algorithms: physical density thresholding; interactive thresholding; fuzzy c-means with 3 classes (FCM3) and 4 classes (FCM4); and k-means. The segmentation algorithms were evaluated in 2 stages: first, an approach based on the assumption that the breast composition should be the same in both prone and supine position; and second, comparison of segmentation with tissue outlines from 3 experts using the Dice similarity coefficient (DSC). Breast datasets were grouped into nonsparse and sparse fibroglandular tissue distributions according to expert assessment and used to assess the accuracy of the segmentation methods and the agreement between experts. Results: Prone and supine breast composition analysis showed differences between the methods. Validation against expert outlines found significant differences (P<.001) between FCM3 and FCM4. Fuzzy c-means with 3 classes generated segmentation results (mean DSC = 0.70) closest to the experts' outlines. There was good agreement (mean DSC = 0.85) among experts for breast tissue outlining. Segmentation accuracy and expert agreement was significantly higher (P<.005) in the nonsparse group than in the sparse group. Conclusions: The FCM3 gave the most accurate segmentation of breast tissues on CT data and could therefore be used in adaptive radiation therapy-based on tissue modeling. Breast tissue

Anthropocentric Video Segmentation for Lecture Webcasts

Directory of Open Access Journals (Sweden)

Rojas Raul

2007-01-01

Full Text Available Abstract Many lecture recording and presentation systems transmit slides or chalkboard content along with a small video of the instructor. As a result, two areas of the screen are competing for the viewer's attention, causing the widely known split-attention effect. Face and body gestures, such as pointing, do not appear in the context of the slides or the board. To eliminate this problem, this article proposes to extract the lecturer from the video stream and paste his or her image onto the board or slide image. As a result, the lecturer acting in front of the board or slides becomes the center of attention. The entire lecture presentation becomes more human-centered. This article presents both an analysis of the underlying psychological problems and an explanation of signal processing techniques that are applied in a concrete system. The presented algorithm is able to extract and overlay the lecturer online and in real time at full video resolution.

Anthropocentric Video Segmentation for Lecture Webcasts

Directory of Open Access Journals (Sweden)

Raul Rojas

2008-03-01

Full Text Available Many lecture recording and presentation systems transmit slides or chalkboard content along with a small video of the instructor. As a result, two areas of the screen are competing for the viewer's attention, causing the widely known split-attention effect. Face and body gestures, such as pointing, do not appear in the context of the slides or the board. To eliminate this problem, this article proposes to extract the lecturer from the video stream and paste his or her image onto the board or slide image. As a result, the lecturer acting in front of the board or slides becomes the center of attention. The entire lecture presentation becomes more human-centered. This article presents both an analysis of the underlying psychological problems and an explanation of signal processing techniques that are applied in a concrete system. The presented algorithm is able to extract and overlay the lecturer online and in real time at full video resolution.

An adaptive segment method for smoothing lidar signal based on noise estimation

Science.gov (United States)

Wang, Yuzhao; Luo, Pingping

2014-10-01

An adaptive segmentation smoothing method (ASSM) is introduced in the paper to smooth the signal and suppress the noise. In the ASSM, the noise is defined as the 3σ of the background signal. An integer number N is defined for finding the changing positions in the signal curve. If the difference of adjacent two points is greater than 3Nσ, the position is recorded as an end point of the smoothing segment. All the end points detected as above are recorded and the curves between them will be smoothed separately. In the traditional method, the end points of the smoothing windows in the signals are fixed. The ASSM creates changing end points in different signals and the smoothing windows could be set adaptively. The windows are always set as the half of the segmentations and then the average smoothing method will be applied in the segmentations. The Iterative process is required for reducing the end-point aberration effect in the average smoothing method and two or three times are enough. In ASSM, the signals are smoothed in the spacial area nor frequent area, that means the frequent disturbance will be avoided. A lidar echo was simulated in the experimental work. The echo was supposed to be created by a space-born lidar (e.g. CALIOP). And white Gaussian noise was added to the echo to act as the random noise resulted from environment and the detector. The novel method, ASSM, was applied to the noisy echo to filter the noise. In the test, N was set to 3 and the Iteration time is two. The results show that, the signal could be smoothed adaptively by the ASSM, but the N and the Iteration time might be optimized when the ASSM is applied in a different lidar.

New robust algorithm for tracking cells in videos of Drosophila morphogenesis based on finding an ideal path in segmented spatio-temporal cellular structures.

Science.gov (United States)

Bellaïche, Yohanns; Bosveld, Floris; Graner, François; Mikula, Karol; Remesíková, Mariana; Smísek, Michal

2011-01-01

In this paper, we present a novel algorithm for tracking cells in time lapse confocal microscopy movie of a Drosophila epithelial tissue during pupal morphogenesis. We consider a 2D + time video as a 3D static image, where frames are stacked atop each other, and using a spatio-temporal segmentation algorithm we obtain information about spatio-temporal 3D tubes representing evolutions of cells. The main idea for tracking is the usage of two distance functions--first one from the cells in the initial frame and second one from segmented boundaries. We track the cells backwards in time. The first distance function attracts the subsequently constructed cell trajectories to the cells in the initial frame and the second one forces them to be close to centerlines of the segmented tubular structures. This makes our tracking algorithm robust against noise and missing spatio-temporal boundaries. This approach can be generalized to a 3D + time video analysis, where spatio-temporal tubes are 4D objects.

Automatic topics segmentation for TV news video

Science.gov (United States)

Hmayda, Mounira; Ejbali, Ridha; Zaied, Mourad

2017-03-01

Automatic identification of television programs in the TV stream is an important task for operating archives. This article proposes a new spatio-temporal approach to identify the programs in TV stream into two main steps: First, a reference catalogue for video features visual jingles built. We operate the features that characterize the instances of the same program type to identify the different types of programs in the flow of television. The role of video features is to represent the visual invariants for each visual jingle using appropriate automatic descriptors for each television program. On the other hand, programs in television streams are identified by examining the similarity of the video signal for visual grammars in the catalogue. The main idea of the identification process is to compare the visual similarity of the video signal features in the flow of television to the catalogue. After presenting the proposed approach, the paper overviews encouraging experimental results on several streams extracted from different channels and compounds of several programs.

Intra-patient semi-automated segmentation of the cervix-uterus in CT-images for adaptive radiotherapy of cervical cancer

Science.gov (United States)

Luiza Bondar, M.; Hoogeman, Mischa; Schillemans, Wilco; Heijmen, Ben

2013-08-01

For online adaptive radiotherapy of cervical cancer, fast and accurate image segmentation is required to facilitate daily treatment adaptation. Our aim was twofold: (1) to test and compare three intra-patient automated segmentation methods for the cervix-uterus structure in CT-images and (2) to improve the segmentation accuracy by including prior knowledge on the daily bladder volume or on the daily coordinates of implanted fiducial markers. The tested methods were: shape deformation (SD) and atlas-based segmentation (ABAS) using two non-rigid registration methods: demons and a hierarchical algorithm. Tests on 102 CT-scans of 13 patients demonstrated that the segmentation accuracy significantly increased by including the bladder volume predicted with a simple 1D model based on a manually defined bladder top. Moreover, manually identified implanted fiducial markers significantly improved the accuracy of the SD method. For patients with large cervix-uterus volume regression, the use of CT-data acquired toward the end of the treatment was required to improve segmentation accuracy. Including prior knowledge, the segmentation results of SD (Dice similarity coefficient 85 ± 6%, error margin 2.2 ± 2.3 mm, average time around 1 min) and of ABAS using hierarchical non-rigid registration (Dice 82 ± 10%, error margin 3.1 ± 2.3 mm, average time around 30 s) support their use for image guided online adaptive radiotherapy of cervical cancer.

Adaptive Noise Model for Transform Domain Wyner-Ziv Video using Clustering of DCT Blocks

DEFF Research Database (Denmark)

Luong, Huynh Van; Huang, Xin; Forchhammer, Søren

2011-01-01

The noise model is one of the most important aspects influencing the coding performance of Distributed Video Coding. This paper proposes a novel noise model for Transform Domain Wyner-Ziv (TDWZ) video coding by using clustering of DCT blocks. The clustering algorithm takes advantage of the residual...... modelling. Furthermore, the proposed cluster level noise model is adaptively combined with a coefficient level noise model in this paper to robustly improve coding performance of TDWZ video codec up to 1.24 dB (by Bjøntegaard metric) compared to the DISCOVER TDWZ video codec....... information of all frequency bands, iteratively classifies blocks into different categories and estimates the noise parameter in each category. The experimental results show that the coding performance of the proposed cluster level noise model is competitive with state-ofthe- art coefficient level noise...

AN ADAPTIVE APPROACH FOR SEGMENTATION OF 3D LASER POINT CLOUD

Directory of Open Access Journals (Sweden)

Z. Lari

2012-09-01

Full Text Available Automatic processing and object extraction from 3D laser point cloud is one of the major research topics in the field of photogrammetry. Segmentation is an essential step in the processing of laser point cloud, and the quality of extracted objects from laser data is highly dependent on the validity of the segmentation results. This paper presents a new approach for reliable and efficient segmentation of planar patches from a 3D laser point cloud. In this method, the neighbourhood of each point is firstly established using an adaptive cylinder while considering the local point density and surface trend. This neighbourhood definition has a major effect on the computational accuracy of the segmentation attributes. In order to efficiently cluster planar surfaces and prevent introducing ambiguities, the coordinates of the origin's projection on each point's best fitted plane are used as the clustering attributes. Then, an octree space partitioning method is utilized to detect and extract peaks from the attribute space. Each detected peak represents a specific cluster of points which are located on a distinct planar surface in the object space. Experimental results show the potential and feasibility of applying this method for segmentation of both airborne and terrestrial laser data.

Video modeling by experts with video feedback to enhance gymnastics skills.

Science.gov (United States)

Boyer, Eva; Miltenberger, Raymond G; Batsche, Catherine; Fogel, Victoria

2009-01-01

The effects of combining video modeling by experts with video feedback were analyzed with 4 female competitive gymnasts (7 to 10 years old) in a multiple baseline design across behaviors. During the intervention, after the gymnast performed a specific gymnastics skill, she viewed a video segment showing an expert gymnast performing the same skill and then viewed a video replay of her own performance of the skill. The results showed that all gymnasts demonstrated improved performance across three gymnastics skills following exposure to the intervention.

High-throughput sample adaptive offset hardware architecture for high-efficiency video coding

Science.gov (United States)

Zhou, Wei; Yan, Chang; Zhang, Jingzhi; Zhou, Xin

2018-03-01

A high-throughput hardware architecture for a sample adaptive offset (SAO) filter in the high-efficiency video coding video coding standard is presented. First, an implementation-friendly and simplified bitrate estimation method of rate-distortion cost calculation is proposed to reduce the computational complexity in the mode decision of SAO. Then, a high-throughput VLSI architecture for SAO is presented based on the proposed bitrate estimation method. Furthermore, multiparallel VLSI architecture for in-loop filters, which integrates both deblocking filter and SAO filter, is proposed. Six parallel strategies are applied in the proposed in-loop filters architecture to improve the system throughput and filtering speed. Experimental results show that the proposed in-loop filters architecture can achieve up to 48% higher throughput in comparison with prior work. The proposed architecture can reach a high-operating clock frequency of 297 MHz with TSMC 65-nm library and meet the real-time requirement of the in-loop filters for 8 K × 4 K video format at 132 fps.

Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection.

Science.gov (United States)

Park, Sang Hyun; Gao, Yaozong; Shi, Yinghuan; Shen, Dinggang

2014-11-01

Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to evaluate both the efficiency

Learning Science Through Digital Video: Views on Watching and Creating Videos

Science.gov (United States)

Wade, P.; Courtney, A. R.

2013-12-01

In science, the use of digital video to document phenomena, experiments and demonstrations has rapidly increased during the last decade. The use of digital video for science education also has become common with the wide availability of video over the internet. However, as with using any technology as a teaching tool, some questions should be asked: What science is being learned from watching a YouTube clip of a volcanic eruption or an informational video on hydroelectric power generation? What are student preferences (e.g. multimedia versus traditional mode of delivery) with regard to their learning? This study describes 1) the efficacy of watching digital video in the science classroom to enhance student learning, 2) student preferences of instruction with regard to multimedia versus traditional delivery modes, and 3) the use of creating digital video as a project-based educational strategy to enhance learning. Undergraduate non-science majors were the primary focus group in this study. Students were asked to view video segments and respond to a survey focused on what they learned from the segments. Additionally, they were asked about their preference for instruction (e.g. text only, lecture-PowerPoint style delivery, or multimedia-video). A majority of students indicated that well-made video, accompanied with scientific explanations or demonstration of the phenomena was most useful and preferred over text-only or lecture instruction for learning scientific information while video-only delivery with little or no explanation was deemed not very useful in learning science concepts. The use of student generated video projects as learning vehicles for the creators and other class members as viewers also will be discussed.

Adaptive end-to-end optimization of mobile video streaming using QoS negotiation

NARCIS (Netherlands)

Taal, Jacco R.; Langendoen, Koen; van der Schaaf, Arjen; van Dijk, H.W.; Lagendijk, R. (Inald) L.

Video streaming over wireless links is a non-trivial problem due to the large and frequent changes in the quality of the underlying radio channel combined with latency constraints. We believe that every layer in a mobile system must be prepared to adapt its behavior to its environment. Thus layers

Adaptive Binary Arithmetic Coder-Based Image Feature and Segmentation in the Compressed Domain

Directory of Open Access Journals (Sweden)

Hsi-Chin Hsin

2012-01-01

Full Text Available Image compression is necessary in various applications, especially for efficient transmission over a band-limited channel. It is thus desirable to be able to segment an image in the compressed domain directly such that the burden of decompressing computation can be avoided. Motivated by the adaptive binary arithmetic coder (MQ coder of JPEG2000, we propose an efficient scheme to segment the feature vectors that are extracted from the code stream of an image. We modify the Compression-based Texture Merging (CTM algorithm to alleviate the influence of overmerging problem by making use of the rate distortion information. Experimental results show that the MQ coder-based image segmentation is preferable in terms of the boundary displacement error (BDE measure. It has the advantage of saving computational cost as the segmentation results even at low rates of bits per pixel (bpp are satisfactory.

Local adaptive tone mapping for video enhancement

Science.gov (United States)

Lachine, Vladimir; Dai, Min (.

2015-03-01

As new technologies like High Dynamic Range cameras, AMOLED and high resolution displays emerge on consumer electronics market, it becomes very important to deliver the best picture quality for mobile devices. Tone Mapping (TM) is a popular technique to enhance visual quality. However, the traditional implementation of Tone Mapping procedure is limited by pixel's value to value mapping, and the performance is restricted in terms of local sharpness and colorfulness. To overcome the drawbacks of traditional TM, we propose a spatial-frequency based framework in this paper. In the proposed solution, intensity component of an input video/image signal is split on low pass filtered (LPF) and high pass filtered (HPF) bands. Tone Mapping (TM) function is applied to LPF band to improve the global contrast/brightness, and HPF band is added back afterwards to keep the local contrast. The HPF band may be adjusted by a coring function to avoid noise boosting and signal overshooting. Colorfulness of an original image may be preserved or enhanced by chroma components correction by means of saturation function. Localized content adaptation is further improved by dividing an image to a set of non-overlapped regions and modifying each region individually. The suggested framework allows users to implement a wide range of tone mapping applications with perceptional local sharpness and colorfulness preserved or enhanced. Corresponding hardware circuit may be integrated in camera, video or display pipeline with minimal hardware budget

Sealing Clay Text Segmentation Based on Radon-Like Features and Adaptive Enhancement Filters

Directory of Open Access Journals (Sweden)

Xia Zheng

2015-01-01

Full Text Available Text extraction is a key issue in sealing clay research. The traditional method based on rubbings increases the risk of sealing clay damage and is unfavorable to sealing clay protection. Therefore, using digital image of sealing clay, a new method for text segmentation based on Radon-like features and adaptive enhancement filters is proposed in this paper. First, adaptive enhancement LM filter bank is used to get the maximum energy image; second, the edge image of the maximum energy image is calculated; finally, Radon-like feature images are generated by combining maximum energy image and its edge image. The average image of Radon-like feature images is segmented by the image thresholding method. Compared with 2D Otsu, GA, and FastFCM, the experiment result shows that this method can perform better in terms of accuracy and completeness of the text.

Automatic generation of pictorial transcripts of video programs

Science.gov (United States)

Shahraray, Behzad; Gibbon, David C.

1995-03-01

An automatic authoring system for the generation of pictorial transcripts of video programs which are accompanied by closed caption information is presented. A number of key frames, each of which represents the visual information in a segment of the video (i.e., a scene), are selected automatically by performing a content-based sampling of the video program. The textual information is recovered from the closed caption signal and is initially segmented based on its implied temporal relationship with the video segments. The text segmentation boundaries are then adjusted, based on lexical analysis and/or caption control information, to account for synchronization errors due to possible delays in the detection of scene boundaries or the transmission of the caption information. The closed caption text is further refined through linguistic processing for conversion to lower- case with correct capitalization. The key frames and the related text generate a compact multimedia presentation of the contents of the video program which lends itself to efficient storage and transmission. This compact representation can be viewed on a computer screen, or used to generate the input to a commercial text processing package to generate a printed version of the program.

Video flow active control by means of adaptive shifted foveal geometries

Science.gov (United States)

Urdiales, Cristina; Rodriguez, Juan A.; Bandera, Antonio J.; Sandoval, Francisco

2000-10-01

This paper presents a control mechanism for video transmission that relies on transmitting non-uniform resolution images depending on the delay of the communication channel. These images are built in an active way to keep the areas of interest of the image at the highest resolution available. In order to shift the area of high resolution over the image and to achieve a data structure easy to process by using conventional algorithms, a shifted fovea multi resolution geometry of adaptive size is used. Besides, if delays are nevertheless too high, the different areas of resolution of the image can be transmitted at different rates. A functional system has been developed for corridor surveillance with static cameras. Tests with real video images have proven that the method allows an almost constant rate of images per second as long as the channel is not collapsed.

Fuzzy Logic Control of Adaptive ARQ for Video Distribution over a Bluetooth Wireless Link

Directory of Open Access Journals (Sweden)

R. Razavi

2007-01-01

Full Text Available Bluetooth's default automatic repeat request (ARQ scheme is not suited to video distribution resulting in missed display and decoded deadlines. Adaptive ARQ with active discard of expired packets from the send buffer is an alternative approach. However, even with the addition of cross-layer adaptation to picture-type packet importance, ARQ is not ideal in conditions of a deteriorating RF channel. The paper presents fuzzy logic control of ARQ, based on send buffer fullness and the head-of-line packet's deadline. The advantage of the fuzzy logic approach, which also scales its output according to picture type importance, is that the impact of delay can be directly introduced to the model, causing retransmissions to be reduced compared to all other schemes. The scheme considers both the delay constraints of the video stream and at the same time avoids send buffer overflow. Tests explore a variety of Bluetooth send buffer sizes and channel conditions. For adverse channel conditions and buffer size, the tests show an improvement of at least 4 dB in video quality compared to nonfuzzy schemes. The scheme can be applied to any codec with I-, P-, and (possibly B-slices by inspection of packet headers without the need for encoder intervention.

Design of a Low-Power VLSI Macrocell for Nonlinear Adaptive Video Noise Reduction

Directory of Open Access Journals (Sweden)

Sergio Saponara

2004-09-01

Full Text Available A VLSI macrocell for edge-preserving video noise reduction is proposed in the paper. It is based on a nonlinear rational filter enhanced by a noise estimator for blind and dynamic adaptation of the filtering parameters to the input signal statistics. The VLSI filter features a modular architecture allowing the extension of both mask size and filtering directions. Both spatial and spatiotemporal algorithms are supported. Simulation results with monochrome test videos prove its efficiency for many noise distributions with PSNR improvements up to 3.8 dB with respect to a nonadaptive solution. The VLSI macrocell has been realized in a 0.18 μm CMOS technology using a standard-cells library; it allows for real-time processing of main video formats, up to 30 fps (frames per second 4CIF, with a power consumption in the order of few mW.

Temporal Scalability through Adaptive -Band Filter Banks for Robust H.264/MPEG-4 AVC Video Coding

Directory of Open Access Journals (Sweden)

Pau G

2006-01-01

Full Text Available This paper presents different structures that use adaptive -band hierarchical filter banks for temporal scalability. Open-loop and closed-loop configurations are introduced and illustrated using existing video codecs. In particular, it is shown that the H.264/MPEG-4 AVC codec allows us to introduce scalability by frame shuffling operations, thus keeping backward compatibility with the standard. The large set of shuffling patterns introduced here can be exploited to adapt the encoding process to the video content features, as well as to the user equipment and transmission channel characteristics. Furthermore, simulation results show that this scalability is obtained with no degradation in terms of subjective and objective quality in error-free environments, while in error-prone channels the scalable versions provide increased robustness.

Automated Music Video Generation Using Multi-level Feature-based Segmentation

Science.gov (United States)

Yoon, Jong-Chul; Lee, In-Kwon; Byun, Siwoo

The expansion of the home video market has created a requirement for video editing tools to allow ordinary people to assemble videos from short clips. However, professional skills are still necessary to create a music video, which requires a stream to be synchronized with pre-composed music. Because the music and the video are pre-generated in separate environments, even a professional producer usually requires a number of trials to obtain a satisfactory synchronization, which is something that most amateurs are unable to achieve.

Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

Energy Technology Data Exchange (ETDEWEB)

Park, Sang Hyun [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Gao, Yaozong, E-mail: yzgao@cs.unc.edu [Department of Computer Science, Department of Radiology, and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Shi, Yinghuan, E-mail: syh@nju.edu.cn [State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023 (China); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul 136-713 (Korea, Republic of)

2014-11-01

Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to

Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

International Nuclear Information System (INIS)

Park, Sang Hyun; Gao, Yaozong; Shi, Yinghuan; Shen, Dinggang

2014-01-01

Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to

Integer-linear-programing optimization in scalable video multicast with adaptive modulation and coding in wireless networks.

Science.gov (United States)

Lee, Dongyul; Lee, Chaewoo

2014-01-01

The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm.

Integer-Linear-Programing Optimization in Scalable Video Multicast with Adaptive Modulation and Coding in Wireless Networks

Directory of Open Access Journals (Sweden)

Dongyul Lee

2014-01-01

Full Text Available The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC with adaptive modulation and coding (AMC provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm.

Content Adaptive True Motion Estimator for H.264 Video Compression

Directory of Open Access Journals (Sweden)

P. Kulla

2007-12-01

Full Text Available Content adaptive true motion estimator for H.264 video coding is a fast block-based matching estimator with implemented multi-stage approach to estimate motion fields between two image frames. It considers the theory of 3D scene objects projection into 2D image plane for selection of motion vector candidates from the higher stages. The stages of the algorithm and its hierarchy are defined upon motion estimation reliability measurement (image blocks including two different directions of spatial gradient, blocks with one dominant spatial gradient and blocks including minimal spatial gradient. Parameters of the image classification into stages are set adaptively upon image structure. Due to search strategy are the estimated motion fields more corresponding to a true motion in an image sequence as in the case of conventional motion estimation algorithms that use fixed sets of motion vector candidates from tight neighborhood.

Multi-modal highlight generation for sports videos using an information-theoretic excitability measure

Science.gov (United States)

Hasan, Taufiq; Bořil, Hynek; Sangwan, Abhijeet; L Hansen, John H.

2013-12-01

The ability to detect and organize `hot spots' representing areas of excitement within video streams is a challenging research problem when techniques rely exclusively on video content. A generic method for sports video highlight selection is presented in this study which leverages both video/image structure as well as audio/speech properties. Processing begins where the video is partitioned into small segments and several multi-modal features are extracted from each segment. Excitability is computed based on the likelihood of the segmental features residing in certain regions of their joint probability density function space which are considered both exciting and rare. The proposed measure is used to rank order the partitioned segments to compress the overall video sequence and produce a contiguous set of highlights. Experiments are performed on baseball videos based on signal processing advancements for excitement assessment in the commentators' speech, audio energy, slow motion replay, scene cut density, and motion activity as features. Detailed analysis on correlation between user excitability and various speech production parameters is conducted and an effective scheme is designed to estimate the excitement level of commentator's speech from the sports videos. Subjective evaluation of excitability and ranking of video segments demonstrate a higher correlation with the proposed measure compared to well-established techniques indicating the effectiveness of the overall approach.

Adaptive block online learning target tracking based on super pixel segmentation

Science.gov (United States)

Cheng, Yue; Li, Jianzeng

2018-04-01

Video target tracking technology under the unremitting exploration of predecessors has made big progress, but there are still lots of problems not solved. This paper proposed a new algorithm of target tracking based on image segmentation technology. Firstly we divide the selected region using simple linear iterative clustering (SLIC) algorithm, after that, we block the area with the improved density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm. Each sub-block independently trained classifier and tracked, then the algorithm ignore the failed tracking sub-block while reintegrate the rest of the sub-blocks into tracking box to complete the target tracking. The experimental results show that our algorithm can work effectively under occlusion interference, rotation change, scale change and many other problems in target tracking compared with the current mainstream algorithms.

Adaptation of the Maracas algorithm for carotid artery segmentation and stenosis quantification on CT images

International Nuclear Information System (INIS)

Maria A Zuluaga; Maciej Orkisz; Edgar J F Delgado; Vincent Dore; Alfredo Morales Pinzon; Marcela Hernandez Hoyos

2010-01-01

This paper describes the adaptations of Maracas algorithm to the segmentation and quantification of vascular structures in CTA images of the carotid artery. The maracas algorithm, which is based on an elastic model and on a multi-scale Eigen-analysis of the inertia matrix, was originally designed to segment a single artery in MRA images. The modifications are primarily aimed at addressing the specificities of CT images and the bifurcations. The algorithms implemented in this new version are classified into two levels. 1. The low-level processing (filtering of noise and directional artifacts, enhancement and pre-segmentation) to improve the quality of the image and to pre-segment it. These techniques are based on a priori information about noise, artifacts and typical gray levels ranges of lumen, background and calcifications. 2. The high-level processing to extract the centerline of the artery, to segment the lumen and to quantify the stenosis. At this level, we apply a priori knowledge of shape and anatomy of vascular structures. The method was evaluated on 31 datasets from the carotid lumen segmentation and stenosis grading grand challenge 2009. The segmentation results obtained an average of 80:4% dice similarity score, compared to reference segmentation, and the mean stenosis quantification error was 14.4%.

Automatic speech signal segmentation based on the innovation adaptive filter

Directory of Open Access Journals (Sweden)

Makowski Ryszard

2014-06-01

Full Text Available Speech segmentation is an essential stage in designing automatic speech recognition systems and one can find several algorithms proposed in the literature. It is a difficult problem, as speech is immensely variable. The aim of the authors’ studies was to design an algorithm that could be employed at the stage of automatic speech recognition. This would make it possible to avoid some problems related to speech signal parametrization. Posing the problem in such a way requires the algorithm to be capable of working in real time. The only such algorithm was proposed by Tyagi et al., (2006, and it is a modified version of Brandt’s algorithm. The article presents a new algorithm for unsupervised automatic speech signal segmentation. It performs segmentation without access to information about the phonetic content of the utterances, relying exclusively on second-order statistics of a speech signal. The starting point for the proposed method is time-varying Schur coefficients of an innovation adaptive filter. The Schur algorithm is known to be fast, precise, stable and capable of rapidly tracking changes in second order signal statistics. A transfer from one phoneme to another in the speech signal always indicates a change in signal statistics caused by vocal track changes. In order to allow for the properties of human hearing, detection of inter-phoneme boundaries is performed based on statistics defined on the mel spectrum determined from the reflection coefficients. The paper presents the structure of the algorithm, defines its properties, lists parameter values, describes detection efficiency results, and compares them with those for another algorithm. The obtained segmentation results, are satisfactory.

Common and Innovative Visuals: A sparsity modeling framework for video.

Science.gov (United States)

Abdolhosseini Moghadam, Abdolreza; Kumar, Mrityunjay; Radha, Hayder

2014-05-02

Efficient video representation models are critical for many video analysis and processing tasks. In this paper, we present a framework based on the concept of finding the sparsest solution to model video frames. To model the spatio-temporal information, frames from one scene are decomposed into two components: (i) a common frame, which describes the visual information common to all the frames in the scene/segment, and (ii) a set of innovative frames, which depicts the dynamic behaviour of the scene. The proposed approach exploits and builds on recent results in the field of compressed sensing to jointly estimate the common frame and the innovative frames for each video segment. We refer to the proposed modeling framework by CIV (Common and Innovative Visuals). We show how the proposed model can be utilized to find scene change boundaries and extend CIV to videos from multiple scenes. Furthermore, the proposed model is robust to noise and can be used for various video processing applications without relying on motion estimation and detection or image segmentation. Results for object tracking, video editing (object removal, inpainting) and scene change detection are presented to demonstrate the efficiency and the performance of the proposed model.

Visual hashing of digital video : applications and techniques

NARCIS (Netherlands)

Oostveen, J.; Kalker, A.A.C.M.; Haitsma, J.A.; Tescher, A.G.

2001-01-01

his paper present the concept of robust video hashing as a tool for video identification. We present considerations and a technique for (i) extracting essential perceptual features from a moving image sequences and (ii) for identifying any sufficiently long unknown video segment by efficiently

A content-based news video retrieval system: NVRS

Science.gov (United States)

Liu, Huayong; He, Tingting

2009-10-01

This paper focus on TV news programs and design a content-based news video browsing and retrieval system, NVRS, which is convenient for users to fast browsing and retrieving news video by different categories such as political, finance, amusement, etc. Combining audiovisual features and caption text information, the system automatically segments a complete news program into separate news stories. NVRS supports keyword-based news story retrieval, category-based news story browsing and generates key-frame-based video abstract for each story. Experiments show that the method of story segmentation is effective and the retrieval is also efficient.

Video personalization for usage environment

Science.gov (United States)

Tseng, Belle L.; Lin, Ching-Yung; Smith, John R.

2002-07-01

A video personalization and summarization system is designed and implemented incorporating usage environment to dynamically generate a personalized video summary. The personalization system adopts the three-tier server-middleware-client architecture in order to select, adapt, and deliver rich media content to the user. The server stores the content sources along with their corresponding MPEG-7 metadata descriptions. Our semantic metadata is provided through the use of the VideoAnnEx MPEG-7 Video Annotation Tool. When the user initiates a request for content, the client communicates the MPEG-21 usage environment description along with the user query to the middleware. The middleware is powered by the personalization engine and the content adaptation engine. Our personalization engine includes the VideoSue Summarization on Usage Environment engine that selects the optimal set of desired contents according to user preferences. Afterwards, the adaptation engine performs the required transformations and compositions of the selected contents for the specific usage environment using our VideoEd Editing and Composition Tool. Finally, two personalization and summarization systems are demonstrated for the IBM Websphere Portal Server and for the pervasive PDA devices.

vm119_0601b-- Video mosaic segments

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Canadian ROPOS remotely operated vehicle (ROV) outfitted with video equipment (and other devices) was deployed from the NOAA Ship McAurthurII during May-June...

Innovative Solution to Video Enhancement

Science.gov (United States)

2001-01-01

Through a licensing agreement, Intergraph Government Solutions adapted a technology originally developed at NASA's Marshall Space Flight Center for enhanced video imaging by developing its Video Analyst(TM) System. Marshall's scientists developed the Video Image Stabilization and Registration (VISAR) technology to help FBI agents analyze video footage of the deadly 1996 Olympic Summer Games bombing in Atlanta, Georgia. VISAR technology enhanced nighttime videotapes made with hand-held camcorders, revealing important details about the explosion. Intergraph's Video Analyst System is a simple, effective, and affordable tool for video enhancement and analysis. The benefits associated with the Video Analyst System include support of full-resolution digital video, frame-by-frame analysis, and the ability to store analog video in digital format. Up to 12 hours of digital video can be stored and maintained for reliable footage analysis. The system also includes state-of-the-art features such as stabilization, image enhancement, and convolution to help improve the visibility of subjects in the video without altering underlying footage. Adaptable to many uses, Intergraph#s Video Analyst System meets the stringent demands of the law enforcement industry in the areas of surveillance, crime scene footage, sting operations, and dash-mounted video cameras.

Video Classification and Adaptive QoP/QoS Control for Multiresolution Video Applications on IPTV

Directory of Open Access Journals (Sweden)

Huang Shyh-Fang

2012-01-01

Full Text Available With the development of heterogeneous networks and video coding standards, multiresolution video applications over networks become important. It is critical to ensure the service quality of the network for time-sensitive video services. Worldwide Interoperability for Microwave Access (WIMAX is a good candidate for delivering video signals because through WIMAX the delivery quality based on the quality-of-service (QoS setting can be guaranteed. The selection of suitable QoS parameters is, however, not trivial for service users. Instead, what a video service user really concerns with is the video quality of presentation (QoP which includes the video resolution, the fidelity, and the frame rate. In this paper, we present a quality control mechanism in multiresolution video coding structures over WIMAX networks and also investigate the relationship between QoP and QoS in end-to-end connections. Consequently, the video presentation quality can be simply mapped to the network requirements by a mapping table, and then the end-to-end QoS is achieved. We performed experiments with multiresolution MPEG coding over WIMAX networks. In addition to the QoP parameters, the video characteristics, such as, the picture activity and the video mobility, also affect the QoS significantly.

Artifact reduction of compressed images and video combining adaptive fuzzy filtering and directional anisotropic diffusion

DEFF Research Database (Denmark)

Nadernejad, Ehsan; Forchhammer, Søren; Korhonen, Jari

2011-01-01

and ringing artifacts, we have applied directional anisotropic diffusion. Besides that, the selection of the adaptive threshold parameter for the diffusion coefficient has also improved the performance of the algorithm. Experimental results on JPEG compressed images as well as MJPEG and H.264 compressed......Fuzzy filtering is one of the recently developed methods for reducing distortion in compressed images and video. In this paper, we combine the powerful anisotropic diffusion equations with fuzzy filtering in order to reduce the impact of artifacts. Based on the directional nature of the blocking...... videos show improvement in artifact reduction of the proposed algorithm over other directional and spatial fuzzy filters....

Study of Temporal Effects on Subjective Video Quality of Experience.

Science.gov (United States)

Bampis, Christos George; Zhi Li; Moorthy, Anush Krishna; Katsavounidis, Ioannis; Aaron, Anne; Bovik, Alan Conrad

2017-11-01

HTTP adaptive streaming is being increasingly deployed by network content providers, such as Netflix and YouTube. By dividing video content into data chunks encoded at different bitrates, a client is able to request the appropriate bitrate for the segment to be played next based on the estimated network conditions. However, this can introduce a number of impairments, including compression artifacts and rebuffering events, which can severely impact an end-user's quality of experience (QoE). We have recently created a new video quality database, which simulates a typical video streaming application, using long video sequences and interesting Netflix content. Going beyond previous efforts, the new database contains highly diverse and contemporary content, and it includes the subjective opinions of a sizable number of human subjects regarding the effects on QoE of both rebuffering and compression distortions. We observed that rebuffering is always obvious and unpleasant to subjects, while bitrate changes may be less obvious due to content-related dependencies. Transient bitrate drops were preferable over rebuffering only on low complexity video content, while consistently low bitrates were poorly tolerated. We evaluated different objective video quality assessment algorithms on our database and found that objective video quality models are unreliable for QoE prediction on videos suffering from both rebuffering events and bitrate changes. This implies the need for more general QoE models that take into account objective quality models, rebuffering-aware information, and memory. The publicly available video content as well as metadata for all of the videos in the new database can be found at http://live.ece.utexas.edu/research/LIVE_NFLXStudy/nflx_index.html.

Reactive power and voltage control strategy based on dynamic and adaptive segment for DG inverter

Science.gov (United States)

Zhai, Jianwei; Lin, Xiaoming; Zhang, Yongjun

2018-03-01

The inverter of distributed generation (DG) can support reactive power to help solve the problem of out-of-limit voltage in active distribution network (ADN). Therefore, a reactive voltage control strategy based on dynamic and adaptive segment for DG inverter is put forward to actively control voltage in this paper. The proposed strategy adjusts the segmented voltage threshold of Q(U) droop curve dynamically and adaptively according to the voltage of grid-connected point and the power direction of adjacent downstream line. And then the reactive power reference of DG inverter can be got through modified Q(U) control strategy. The reactive power of inverter is controlled to trace the reference value. The proposed control strategy can not only control the local voltage of grid-connected point but also help to maintain voltage within qualified range considering the terminal voltage of distribution feeder and the reactive support for adjacent downstream DG. The scheme using the proposed strategy is compared with the scheme without the reactive support of DG inverter and the scheme using the Q(U) control strategy with constant segmented voltage threshold. The simulation results suggest that the proposed method has a significant improvement on solving the problem of out-of-limit voltage, restraining voltage variation and improving voltage quality.

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

Scalable gastroscopic video summarization via similar-inhibition dictionary selection.

Science.gov (United States)

Wang, Shuai; Cong, Yang; Cao, Jun; Yang, Yunsheng; Tang, Yandong; Zhao, Huaici; Yu, Haibin

2016-01-01

This paper aims at developing an automated gastroscopic video summarization algorithm to assist clinicians to more effectively go through the abnormal contents of the video. To select the most representative frames from the original video sequence, we formulate the problem of gastroscopic video summarization as a dictionary selection issue. Different from the traditional dictionary selection methods, which take into account only the number and reconstruction ability of selected key frames, our model introduces the similar-inhibition constraint to reinforce the diversity of selected key frames. We calculate the attention cost by merging both gaze and content change into a prior cue to help select the frames with more high-level semantic information. Moreover, we adopt an image quality evaluation process to eliminate the interference of the poor quality images and a segmentation process to reduce the computational complexity. For experiments, we build a new gastroscopic video dataset captured from 30 volunteers with more than 400k images and compare our method with the state-of-the-arts using the content consistency, index consistency and content-index consistency with the ground truth. Compared with all competitors, our method obtains the best results in 23 of 30 videos evaluated based on content consistency, 24 of 30 videos evaluated based on index consistency and all videos evaluated based on content-index consistency. For gastroscopic video summarization, we propose an automated annotation method via similar-inhibition dictionary selection. Our model can achieve better performance compared with other state-of-the-art models and supplies more suitable key frames for diagnosis. The developed algorithm can be automatically adapted to various real applications, such as the training of young clinicians, computer-aided diagnosis or medical report generation. Copyright © 2015 Elsevier B.V. All rights reserved.

Complexity control algorithm based on adaptive mode selection for interframe coding in high efficiency video coding

Science.gov (United States)

Chen, Gang; Yang, Bing; Zhang, Xiaoyun; Gao, Zhiyong

2017-07-01

The latest high efficiency video coding (HEVC) standard significantly increases the encoding complexity for improving its coding efficiency. Due to the limited computational capability of handheld devices, complexity constrained video coding has drawn great attention in recent years. A complexity control algorithm based on adaptive mode selection is proposed for interframe coding in HEVC. Considering the direct proportionality between encoding time and computational complexity, the computational complexity is measured in terms of encoding time. First, complexity is mapped to a target in terms of prediction modes. Then, an adaptive mode selection algorithm is proposed for the mode decision process. Specifically, the optimal mode combination scheme that is chosen through offline statistics is developed at low complexity. If the complexity budget has not been used up, an adaptive mode sorting method is employed to further improve coding efficiency. The experimental results show that the proposed algorithm achieves a very large complexity control range (as low as 10%) for the HEVC encoder while maintaining good rate-distortion performance. For the lowdelayP condition, compared with the direct resource allocation method and the state-of-the-art method, an average gain of 0.63 and 0.17 dB in BDPSNR is observed for 18 sequences when the target complexity is around 40%.

AUTOMATIC FAST VIDEO OBJECT DETECTION AND TRACKING ON VIDEO SURVEILLANCE SYSTEM

Directory of Open Access Journals (Sweden)

V. Arunachalam

2012-08-01

Full Text Available This paper describes the advance techniques for object detection and tracking in video. Most visual surveillance systems start with motion detection. Motion detection methods attempt to locate connected regions of pixels that represent the moving objects within the scene; different approaches include frame-to-frame difference, background subtraction and motion analysis. The motion detection can be achieved by Principle Component Analysis (PCA and then separate an objects from background using background subtraction. The detected object can be segmented. Segmentation consists of two schemes: one for spatial segmentation and the other for temporal segmentation. Tracking approach can be done in each frame of detected Object. Pixel label problem can be alleviated by the MAP (Maximum a Posteriori technique.

Task-oriented quality assessment and adaptation in real-time mission critical video streaming applications

Science.gov (United States)

Nightingale, James; Wang, Qi; Grecos, Christos

2015-02-01

In recent years video traffic has become the dominant application on the Internet with global year-on-year increases in video-oriented consumer services. Driven by improved bandwidth in both mobile and fixed networks, steadily reducing hardware costs and the development of new technologies, many existing and new classes of commercial and industrial video applications are now being upgraded or emerging. Some of the use cases for these applications include areas such as public and private security monitoring for loss prevention or intruder detection, industrial process monitoring and critical infrastructure monitoring. The use of video is becoming commonplace in defence, security, commercial, industrial, educational and health contexts. Towards optimal performances, the design or optimisation in each of these applications should be context aware and task oriented with the characteristics of the video stream (frame rate, spatial resolution, bandwidth etc.) chosen to match the use case requirements. For example, in the security domain, a task-oriented consideration may be that higher resolution video would be required to identify an intruder than to simply detect his presence. Whilst in the same case, contextual factors such as the requirement to transmit over a resource-limited wireless link, may impose constraints on the selection of optimum task-oriented parameters. This paper presents a novel, conceptually simple and easily implemented method of assessing video quality relative to its suitability for a particular task and dynamically adapting videos streams during transmission to ensure that the task can be successfully completed. Firstly we defined two principle classes of tasks: recognition tasks and event detection tasks. These task classes are further subdivided into a set of task-related profiles, each of which is associated with a set of taskoriented attributes (minimum spatial resolution, minimum frame rate etc.). For example, in the detection class

Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall

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Jedlovec, Gary; Srikishen, Jayanthi; Edwards, Rita; Cross, David; Welch, Jon; Smith, Matt

2013-01-01

The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of "big data" available from new high resolution remote sensing satellite sensors or four-dimensional numerical model simulations is propelling the wider adoption of ultra-resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well-integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Shortterm Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display-to-dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data-intensive information. This information can be digital-cinema animations, high-resolution images, high-definition video

Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall

Science.gov (United States)

Jedlovec, G.; Srikishen, J.; Edwards, R.; Cross, D.; Welch, J. D.; Smith, M. R.

2013-12-01

The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of 'big data' available from new high resolution remote sensing satellite sensors or four-dimensional numerical model simulations is propelling the wider adoption of ultra-resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well-integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Short-term Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display-to-dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data-intensive information. This information can be digital-cinema animations, high-resolution images, high-definition video

Multi-view video segmentation and tracking for video surveillance

Science.gov (United States)

Mohammadi, Gelareh; Dufaux, Frederic; Minh, Thien Ha; Ebrahimi, Touradj

2009-05-01

Tracking moving objects is a critical step for smart video surveillance systems. Despite the complexity increase, multiple camera systems exhibit the undoubted advantages of covering wide areas and handling the occurrence of occlusions by exploiting the different viewpoints. The technical problems in multiple camera systems are several: installation, calibration, objects matching, switching, data fusion, and occlusion handling. In this paper, we address the issue of tracking moving objects in an environment covered by multiple un-calibrated cameras with overlapping fields of view, typical of most surveillance setups. Our main objective is to create a framework that can be used to integrate objecttracking information from multiple video sources. Basically, the proposed technique consists of the following steps. We first perform a single-view tracking algorithm on each camera view, and then apply a consistent object labeling algorithm on all views. In the next step, we verify objects in each view separately for inconsistencies. Correspondent objects are extracted through a Homography transform from one view to the other and vice versa. Having found the correspondent objects of different views, we partition each object into homogeneous regions. In the last step, we apply the Homography transform to find the region map of first view in the second view and vice versa. For each region (in the main frame and mapped frame) a set of descriptors are extracted to find the best match between two views based on region descriptors similarity. This method is able to deal with multiple objects. Track management issues such as occlusion, appearance and disappearance of objects are resolved using information from all views. This method is capable of tracking rigid and deformable objects and this versatility lets it to be suitable for different application scenarios.

Adapting Mask-RCNN for Automatic Nucleus Segmentation

OpenAIRE

Johnson, Jeremiah W.

2018-01-01

Automatic segmentation of microscopy images is an important task in medical image processing and analysis. Nucleus detection is an important example of this task. Mask-RCNN is a recently proposed state-of-the-art algorithm for object detection, object localization, and object instance segmentation of natural images. In this paper we demonstrate that Mask-RCNN can be used to perform highly effective and efficient automatic segmentations of a wide range of microscopy images of cell nuclei, for ...

Adaptive Kalman Filter Applied to Vision Based Head Gesture Tracking for Playing Video Games

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Mohammadreza Asghari Oskoei

2017-11-01

Full Text Available This paper proposes an adaptive Kalman filter (AKF to improve the performance of a vision-based human machine interface (HMI applied to a video game. The HMI identifies head gestures and decodes them into corresponding commands. Face detection and feature tracking algorithms are used to detect optical flow produced by head gestures. Such approaches often fail due to changes in head posture, occlusion and varying illumination. The adaptive Kalman filter is applied to estimate motion information and reduce the effect of missing frames in a real-time application. Failure in head gesture tracking eventually leads to malfunctioning game control, reducing the scores achieved, so the performance of the proposed vision-based HMI is examined using a game scoring mechanism. The experimental results show that the proposed interface has a good response time, and the adaptive Kalman filter improves the game scores by ten percent.

Adaptive region-growing with maximum curvature strategy for tumor segmentation in 18F-FDG PET

Science.gov (United States)

Tan, Shan; Li, Laquan; Choi, Wookjin; Kang, Min Kyu; D'Souza, Warren D.; Lu, Wei

2017-07-01

Accurate tumor segmentation in PET is crucial in many oncology applications. We developed an adaptive region-growing (ARG) algorithm with a maximum curvature strategy (ARG_MC) for tumor segmentation in PET. The ARG_MC repeatedly applied a confidence connected region-growing algorithm with increasing relaxing factor f. The optimal relaxing factor (ORF) was then determined at the transition point on the f-volume curve, where the volume just grew from the tumor into the surrounding normal tissues. The ARG_MC along with five widely used algorithms were tested on a phantom with 6 spheres at different signal to background ratios and on two clinic datasets including 20 patients with esophageal cancer and 11 patients with non-Hodgkin lymphoma (NHL). The ARG_MC did not require any phantom calibration or any a priori knowledge of the tumor or PET scanner. The identified ORF varied with tumor types (mean ORF  =  9.61, 3.78 and 2.55 respectively for the phantom, esophageal cancer, and NHL datasets), and varied from one tumor to another. For the phantom, the ARG_MC ranked the second in segmentation accuracy with an average Dice similarity index (DSI) of 0.86, only slightly worse than Daisne’s adaptive thresholding method (DSI  =  0.87), which required phantom calibration. For both the esophageal cancer dataset and the NHL dataset, the ARG_MC had the highest accuracy with an average DSI of 0.87 and 0.84, respectively. The ARG_MC was robust to parameter settings and region of interest selection, and it did not depend on scanners, imaging protocols, or tumor types. Furthermore, the ARG_MC made no assumption about the tumor size or tumor uptake distribution, making it suitable for segmenting tumors with heterogeneous FDG uptake. In conclusion, the ARG_MC was accurate, robust and easy to use, it provides a highly potential tool for PET tumor segmentation in clinic.

Smoke regions extraction based on two steps segmentation and motion detection in early fire

Science.gov (United States)

Jian, Wenlin; Wu, Kaizhi; Yu, Zirong; Chen, Lijuan

2018-03-01

Aiming at the early problems of video-based smoke detection in fire video, this paper proposes a method to extract smoke suspected regions by combining two steps segmentation and motion characteristics. Early smoldering smoke can be seen as gray or gray-white regions. In the first stage, regions of interests (ROIs) with smoke are obtained by using two step segmentation methods. Then, suspected smoke regions are detected by combining the two step segmentation and motion detection. Finally, morphological processing is used for smoke regions extracting. The Otsu algorithm is used as segmentation method and the ViBe algorithm is used to detect the motion of smoke. The proposed method was tested on 6 test videos with smoke. The experimental results show the effectiveness of our proposed method over visual observation.

Adjustable Two-Tier Cache for IPTV Based on Segmented Streaming

Directory of Open Access Journals (Sweden)

Kai-Chun Liang

2012-01-01

Full Text Available Internet protocol TV (IPTV is a promising Internet killer application, which integrates video, voice, and data onto a single IP network, and offers viewers an innovative set of choices and control over their TV content. To provide high-quality IPTV services, an effective strategy is based on caching. This work proposes a segment-based two-tier caching approach, which divides each video into multiple segments to be cached. This approach also partitions the cache space into two layers, where the first layer mainly caches to-be-played segments and the second layer saves possibly played segments. As the segment access becomes frequent, the proposed approach enlarges the first layer and reduces the second layer, and vice versa. Because requested segments may not be accessed frequently, this work further designs an admission control mechanism to determine whether an incoming segment should be cached or not. The cache architecture takes forward/stop playback into account and may replace the unused segments under the interrupted playback. Finally, we conduct comprehensive simulation experiments to evaluate the performance of the proposed approach. The results show that our approach can yield higher hit ratio than previous work under various environmental parameters.

A video event trigger for high frame rate, high resolution video technology

Science.gov (United States)

Williams, Glenn L.

1991-12-01

When video replaces film the digitized video data accumulates very rapidly, leading to a difficult and costly data storage problem. One solution exists for cases when the video images represent continuously repetitive 'static scenes' containing negligible activity, occasionally interrupted by short events of interest. Minutes or hours of redundant video frames can be ignored, and not stored, until activity begins. A new, highly parallel digital state machine generates a digital trigger signal at the onset of a video event. High capacity random access memory storage coupled with newly available fuzzy logic devices permits the monitoring of a video image stream for long term or short term changes caused by spatial translation, dilation, appearance, disappearance, or color change in a video object. Pretrigger and post-trigger storage techniques are then adaptable for archiving the digital stream from only the significant video images.

Video steganography based on bit-plane decomposition of wavelet-transformed video

Science.gov (United States)

Noda, Hideki; Furuta, Tomofumi; Niimi, Michiharu; Kawaguchi, Eiji

2004-06-01

This paper presents a steganography method using lossy compressed video which provides a natural way to send a large amount of secret data. The proposed method is based on wavelet compression for video data and bit-plane complexity segmentation (BPCS) steganography. BPCS steganography makes use of bit-plane decomposition and the characteristics of the human vision system, where noise-like regions in bit-planes of a dummy image are replaced with secret data without deteriorating image quality. In wavelet-based video compression methods such as 3-D set partitioning in hierarchical trees (SPIHT) algorithm and Motion-JPEG2000, wavelet coefficients in discrete wavelet transformed video are quantized into a bit-plane structure and therefore BPCS steganography can be applied in the wavelet domain. 3-D SPIHT-BPCS steganography and Motion-JPEG2000-BPCS steganography are presented and tested, which are the integration of 3-D SPIHT video coding and BPCS steganography, and that of Motion-JPEG2000 and BPCS, respectively. Experimental results show that 3-D SPIHT-BPCS is superior to Motion-JPEG2000-BPCS with regard to embedding performance. In 3-D SPIHT-BPCS steganography, embedding rates of around 28% of the compressed video size are achieved for twelve bit representation of wavelet coefficients with no noticeable degradation in video quality.

Adaptive live multicast video streaming of SVC with UEP FEC

Science.gov (United States)

Lev, Avram; Lasry, Amir; Loants, Maoz; Hadar, Ofer

2014-09-01

Ideally, video streaming systems should provide the best quality video a user's device can handle without compromising on downloading speed. In this article, an improved video transmission system is presented which dynamically enhances the video quality based on a user's current network state and repairs errors from data lost in the video transmission. The system incorporates three main components: Scalable Video Coding (SVC) with three layers, multicast based on Receiver Layered Multicast (RLM) and an UnEqual Forward Error Correction (FEC) algorithm. The SVC provides an efficient method for providing different levels of video quality, stored as enhancement layers. In the presented system, a proportional-integral-derivative (PID) controller was implemented to dynamically adjust the video quality, adding or subtracting quality layers as appropriate. In addition, an FEC algorithm was added to compensate for data lost in transmission. A two dimensional FEC was used. The FEC algorithm came from the Pro MPEG code of practice #3 release 2. Several bit errors scenarios were tested (step function, cosine wave) with different bandwidth size and error values were simulated. The suggested scheme which includes SVC video encoding with 3 layers over IP Multicast with Unequal FEC algorithm was investigated under different channel conditions, variable bandwidths and different bit error rates. The results indicate improvement of the video quality in terms of PSNR over previous transmission schemes.

Segmented socioeconomic adaptation of New Eastern European professionals in the United States.

Science.gov (United States)

Michalikova, Nina

2018-01-01

This study examines the socioeconomic adaptation of post-1991 Eastern European professionals in the United States. The data were obtained from the pooled 2006-2010 American Community Surveys. The analysis includes recent immigrants between ages of 25-65 who have at least an associate's degree. Skilled immigrants in professional or managerial occupations are compared with non-professionals or managers to examine and compare socioeconomic outcomes. The findings presented in this study support the segmented assimilation theory and reveal cross-group and cross-country disparities in socioeconomic adaptation. Despite the high amount of human capital, Eastern European skilled immigrants tend to have a lower share of professionals and managers than other groups. Their average income is lower than the income of some other groups in the analysis, especially immigrants from Northern and Western Europe, suggesting these immigrants experience difficulties in transferring human capital. Among the three largest Eastern European groups - Russia, Ukraine, and Poland - there is a clear hierarchy in socioeconomic status with Russian professionals having the highest educational attainment and income, followed by immigrants from Ukraine and Poland. Results also revealed gender differences in socioeconomic adaptation. Women from Eastern Europe are highly professional, but they tend to be concentrated in different occupations than men, leading to a significant gender-wage gap. The effect of selected individual and country-level characteristics on skilled immigrants' socioeconomic adaptation is discussed.

IBES: A Tool for Creating Instructions Based on Event Segmentation

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Katharina eMura

2013-12-01

Full Text Available Receiving informative, well-structured, and well-designed instructions supports performance and memory in assembly tasks. We describe IBES, a tool with which users can quickly and easily create multimedia, step-by-step instructions by segmenting a video of a task into segments. In a validation study we demonstrate that the step-by-step structure of the visual instructions created by the tool corresponds to the natural event boundaries, which are assessed by event segmentation and are known to play an important role in memory processes. In one part of the study, twenty participants created instructions based on videos of two different scenarios by using the proposed tool. In the other part of the study, ten and twelve participants respectively segmented videos of the same scenarios yielding event boundaries for coarse and fine events. We found that the visual steps chosen by the participants for creating the instruction manual had corresponding events in the event segmentation. The number of instructional steps was a compromise between the number of fine and coarse events. Our interpretation of results is that the tool picks up on natural human event perception processes of segmenting an ongoing activity into events and enables the convenient transfer into meaningful multimedia instructions for assembly tasks. We discuss the practical application of IBES, for example, creating manuals for differing expertise levels, and give suggestions for research on user-oriented instructional design based on this tool.

IBES: a tool for creating instructions based on event segmentation.

Science.gov (United States)

Mura, Katharina; Petersen, Nils; Huff, Markus; Ghose, Tandra

2013-12-26

Receiving informative, well-structured, and well-designed instructions supports performance and memory in assembly tasks. We describe IBES, a tool with which users can quickly and easily create multimedia, step-by-step instructions by segmenting a video of a task into segments. In a validation study we demonstrate that the step-by-step structure of the visual instructions created by the tool corresponds to the natural event boundaries, which are assessed by event segmentation and are known to play an important role in memory processes. In one part of the study, 20 participants created instructions based on videos of two different scenarios by using the proposed tool. In the other part of the study, 10 and 12 participants respectively segmented videos of the same scenarios yielding event boundaries for coarse and fine events. We found that the visual steps chosen by the participants for creating the instruction manual had corresponding events in the event segmentation. The number of instructional steps was a compromise between the number of fine and coarse events. Our interpretation of results is that the tool picks up on natural human event perception processes of segmenting an ongoing activity into events and enables the convenient transfer into meaningful multimedia instructions for assembly tasks. We discuss the practical application of IBES, for example, creating manuals for differing expertise levels, and give suggestions for research on user-oriented instructional design based on this tool.

Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy C-Means Clustering

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Ahmed Elazab

2015-01-01

Full Text Available An adaptively regularized kernel-based fuzzy C-means clustering framework is proposed for segmentation of brain magnetic resonance images. The framework can be in the form of three algorithms for the local average grayscale being replaced by the grayscale of the average filter, median filter, and devised weighted images, respectively. The algorithms employ the heterogeneity of grayscales in the neighborhood and exploit this measure for local contextual information and replace the standard Euclidean distance with Gaussian radial basis kernel functions. The main advantages are adaptiveness to local context, enhanced robustness to preserve image details, independence of clustering parameters, and decreased computational costs. The algorithms have been validated against both synthetic and clinical magnetic resonance images with different types and levels of noises and compared with 6 recent soft clustering algorithms. Experimental results show that the proposed algorithms are superior in preserving image details and segmentation accuracy while maintaining a low computational complexity.

Adaptive metric learning with deep neural networks for video-based facial expression recognition

Science.gov (United States)

Liu, Xiaofeng; Ge, Yubin; Yang, Chao; Jia, Ping

2018-01-01

Video-based facial expression recognition has become increasingly important for plenty of applications in the real world. Despite that numerous efforts have been made for the single sequence, how to balance the complex distribution of intra- and interclass variations well between sequences has remained a great difficulty in this area. We propose the adaptive (N+M)-tuplet clusters loss function and optimize it with the softmax loss simultaneously in the training phrase. The variations introduced by personal attributes are alleviated using the similarity measurements of multiple samples in the feature space with many fewer comparison times as conventional deep metric learning approaches, which enables the metric calculations for large data applications (e.g., videos). Both the spatial and temporal relations are well explored by a unified framework that consists of an Inception-ResNet network with long short term memory and the two fully connected layer branches structure. Our proposed method has been evaluated with three well-known databases, and the experimental results show that our method outperforms many state-of-the-art approaches.

Storyboard-Based Video Browsing Using Color and Concept Indices

NARCIS (Netherlands)

Hürst, W.O.; Ip Vai Ching, Algernon; Schoeffmann, K.; Primus, Manfred J.

2017-01-01

We present an interface for interactive video browsing where users visually skim storyboard representations of the files in search for known items (known-item search tasks) and textually described subjects, objects, or events (ad-hoc search tasks). Individual segments of the video are represented as

Spatio-Temporal Video Segmentation with Shape Growth or Shrinkage Constraint

Science.gov (United States)

Tarabalka, Yuliya; Charpiat, Guillaume; Brucker, Ludovic; Menze, Bjoern H.

2014-01-01

We propose a new method for joint segmentation of monotonously growing or shrinking shapes in a time sequence of noisy images. The task of segmenting the image time series is expressed as an optimization problem using the spatio-temporal graph of pixels, in which we are able to impose the constraint of shape growth or of shrinkage by introducing monodirectional infinite links connecting pixels at the same spatial locations in successive image frames. The globally optimal solution is computed with a graph cut. The performance of the proposed method is validated on three applications: segmentation of melting sea ice floes and of growing burned areas from time series of 2D satellite images, and segmentation of a growing brain tumor from sequences of 3D medical scans. In the latter application, we impose an additional intersequences inclusion constraint by adding directed infinite links between pixels of dependent image structures.

Large-Scale Query-by-Image Video Retrieval Using Bloom Filters

OpenAIRE

Araujo, Andre; Chaves, Jason; Lakshman, Haricharan; Angst, Roland; Girod, Bernd

2016-01-01

We consider the problem of using image queries to retrieve videos from a database. Our focus is on large-scale applications, where it is infeasible to index each database video frame independently. Our main contribution is a framework based on Bloom filters, which can be used to index long video segments, enabling efficient image-to-video comparisons. Using this framework, we investigate several retrieval architectures, by considering different types of aggregation and different functions to ...

Video Quality Prediction Models Based on Video Content Dynamics for H.264 Video over UMTS Networks

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Asiya Khan

2010-01-01

Full Text Available The aim of this paper is to present video quality prediction models for objective non-intrusive, prediction of H.264 encoded video for all content types combining parameters both in the physical and application layer over Universal Mobile Telecommunication Systems (UMTS networks. In order to characterize the Quality of Service (QoS level, a learning model based on Adaptive Neural Fuzzy Inference System (ANFIS and a second model based on non-linear regression analysis is proposed to predict the video quality in terms of the Mean Opinion Score (MOS. The objective of the paper is two-fold. First, to find the impact of QoS parameters on end-to-end video quality for H.264 encoded video. Second, to develop learning models based on ANFIS and non-linear regression analysis to predict video quality over UMTS networks by considering the impact of radio link loss models. The loss models considered are 2-state Markov models. Both the models are trained with a combination of physical and application layer parameters and validated with unseen dataset. Preliminary results show that good prediction accuracy was obtained from both the models. The work should help in the development of a reference-free video prediction model and QoS control methods for video over UMTS networks.

SU-E-J-208: Fast and Accurate Auto-Segmentation of Abdominal Organs at Risk for Online Adaptive Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Gupta, V; Wang, Y; Romero, A; Heijmen, B; Hoogeman, M [Erasmus MC Cancer Institute, Rotterdam (Netherlands); Myronenko, A; Jordan, P [Accuray Incorporated, Sunnyvale, United States. (United States)

2014-06-01

Purpose: Various studies have demonstrated that online adaptive radiotherapy by real-time re-optimization of the treatment plan can improve organs-at-risk (OARs) sparing in the abdominal region. Its clinical implementation, however, requires fast and accurate auto-segmentation of OARs in CT scans acquired just before each treatment fraction. Autosegmentation is particularly challenging in the abdominal region due to the frequently observed large deformations. We present a clinical validation of a new auto-segmentation method that uses fully automated non-rigid registration for propagating abdominal OAR contours from planning to daily treatment CT scans. Methods: OARs were manually contoured by an expert panel to obtain ground truth contours for repeat CT scans (3 per patient) of 10 patients. For the non-rigid alignment, we used a new non-rigid registration method that estimates the deformation field by optimizing local normalized correlation coefficient with smoothness regularization. This field was used to propagate planning contours to repeat CTs. To quantify the performance of the auto-segmentation, we compared the propagated and ground truth contours using two widely used metrics- Dice coefficient (Dc) and Hausdorff distance (Hd). The proposed method was benchmarked against translation and rigid alignment based auto-segmentation. Results: For all organs, the auto-segmentation performed better than the baseline (translation) with an average processing time of 15 s per fraction CT. The overall improvements ranged from 2% (heart) to 32% (pancreas) in Dc, and 27% (heart) to 62% (spinal cord) in Hd. For liver, kidneys, gall bladder, stomach, spinal cord and heart, Dc above 0.85 was achieved. Duodenum and pancreas were the most challenging organs with both showing relatively larger spreads and medians of 0.79 and 2.1 mm for Dc and Hd, respectively. Conclusion: Based on the achieved accuracy and computational time we conclude that the investigated auto-segmentation

SU-E-J-208: Fast and Accurate Auto-Segmentation of Abdominal Organs at Risk for Online Adaptive Radiotherapy

International Nuclear Information System (INIS)

Gupta, V; Wang, Y; Romero, A; Heijmen, B; Hoogeman, M; Myronenko, A; Jordan, P

2014-01-01

Purpose: Various studies have demonstrated that online adaptive radiotherapy by real-time re-optimization of the treatment plan can improve organs-at-risk (OARs) sparing in the abdominal region. Its clinical implementation, however, requires fast and accurate auto-segmentation of OARs in CT scans acquired just before each treatment fraction. Autosegmentation is particularly challenging in the abdominal region due to the frequently observed large deformations. We present a clinical validation of a new auto-segmentation method that uses fully automated non-rigid registration for propagating abdominal OAR contours from planning to daily treatment CT scans. Methods: OARs were manually contoured by an expert panel to obtain ground truth contours for repeat CT scans (3 per patient) of 10 patients. For the non-rigid alignment, we used a new non-rigid registration method that estimates the deformation field by optimizing local normalized correlation coefficient with smoothness regularization. This field was used to propagate planning contours to repeat CTs. To quantify the performance of the auto-segmentation, we compared the propagated and ground truth contours using two widely used metrics- Dice coefficient (Dc) and Hausdorff distance (Hd). The proposed method was benchmarked against translation and rigid alignment based auto-segmentation. Results: For all organs, the auto-segmentation performed better than the baseline (translation) with an average processing time of 15 s per fraction CT. The overall improvements ranged from 2% (heart) to 32% (pancreas) in Dc, and 27% (heart) to 62% (spinal cord) in Hd. For liver, kidneys, gall bladder, stomach, spinal cord and heart, Dc above 0.85 was achieved. Duodenum and pancreas were the most challenging organs with both showing relatively larger spreads and medians of 0.79 and 2.1 mm for Dc and Hd, respectively. Conclusion: Based on the achieved accuracy and computational time we conclude that the investigated auto-segmentation

People detection in nuclear plants by video processing for safety purpose

Energy Technology Data Exchange (ETDEWEB)

Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A., E-mail: calexandre@ien.gov.b, E-mail: mol@ien.gov.b [Instituto de Engenharia Nuclear (IEN/CNEN), Rio de Janeiro, RJ (Brazil); Seixas, Jose M.; Silva, Eduardo Antonio B., E-mail: seixas@lps.ufrj.b, E-mail: eduardo@lps.ufrj.b [Coordenacao dos Programas de Pos-Graduacao de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Eletrica; Cota, Raphael E.; Ramos, Bruno L., E-mail: brunolange@poli.ufrj.b [Universidade Federal do Rio de Janeiro (EP/UFRJ), RJ (Brazil). Dept. de Engenharia Eletronica e de Computacao

2011-07-01

This work describes the development of a surveillance system for safety purposes in nuclear plants. The final objective is to track people online in videos, in order to estimate the dose received by personnel, during the execution of working tasks in nuclear plants. The estimation will be based on their tracked positions and on dose rate mapping in a real nuclear plant at Instituto de Engenharia Nuclear, Argonauta nuclear research reactor. Cameras have been installed within Argonauta's room, supplying the data needed. Both video processing and statistical signal processing techniques may be used for detection, segmentation and tracking people in video. This first paper reports people segmentation in video using background subtraction, by two different approaches, namely frame differences, and blind signal separation based on the independent component analysis method. Results are commented, along with perspectives for further work. (author)

People detection in nuclear plants by video processing for safety purpose

International Nuclear Information System (INIS)

Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Seixas, Jose M.; Silva, Eduardo Antonio B.; Cota, Raphael E.; Ramos, Bruno L.

2011-01-01

This work describes the development of a surveillance system for safety purposes in nuclear plants. The final objective is to track people online in videos, in order to estimate the dose received by personnel, during the execution of working tasks in nuclear plants. The estimation will be based on their tracked positions and on dose rate mapping in a real nuclear plant at Instituto de Engenharia Nuclear, Argonauta nuclear research reactor. Cameras have been installed within Argonauta's room, supplying the data needed. Both video processing and statistical signal processing techniques may be used for detection, segmentation and tracking people in video. This first paper reports people segmentation in video using background subtraction, by two different approaches, namely frame differences, and blind signal separation based on the independent component analysis method. Results are commented, along with perspectives for further work. (author)

Adaptive testing for video quality assessment

NARCIS (Netherlands)

Menkovski, V.; Exarchakos, G.; Liotta, A.; Damásio, M.J.; Cardoso, G.; Quico, C.; Geerts, D.

2011-01-01

Optimizing the Quality of Experience and avoiding under or over provisioning in video delivery services requires understanding of how different resources affect the perceived quality. The utility of resources, such as bit-rate, is directly calculated by proportioningthe improvement in quality over

Prostate segmentation by feature enhancement using domain knowledge and adaptive region based operations

International Nuclear Information System (INIS)

Nanayakkara, Nuwan D; Samarabandu, Jagath; Fenster, Aaron

2006-01-01

Estimation of prostate location and volume is essential in determining a dose plan for ultrasound-guided brachytherapy, a common prostate cancer treatment. However, manual segmentation is difficult, time consuming and prone to variability. In this paper, we present a semi-automatic discrete dynamic contour (DDC) model based image segmentation algorithm, which effectively combines a multi-resolution model refinement procedure together with the domain knowledge of the image class. The segmentation begins on a low-resolution image by defining a closed DDC model by the user. This contour model is then deformed progressively towards higher resolution images. We use a combination of a domain knowledge based fuzzy inference system (FIS) and a set of adaptive region based operators to enhance the edges of interest and to govern the model refinement using a DDC model. The automatic vertex relocation process, embedded into the algorithm, relocates deviated contour points back onto the actual prostate boundary, eliminating the need of user interaction after initialization. The accuracy of the prostate boundary produced by the proposed algorithm was evaluated by comparing it with a manually outlined contour by an expert observer. We used this algorithm to segment the prostate boundary in 114 2D transrectal ultrasound (TRUS) images of six patients scheduled for brachytherapy. The mean distance between the contours produced by the proposed algorithm and the manual outlines was 2.70 ± 0.51 pixels (0.54 ± 0.10 mm). We also showed that the algorithm is insensitive to variations of the initial model and parameter values, thus increasing the accuracy and reproducibility of the resulting boundaries in the presence of noise and artefacts

VIDEO DENOISING USING SWITCHING ADAPTIVE DECISION BASED ALGORITHM WITH ROBUST MOTION ESTIMATION TECHNIQUE

Directory of Open Access Journals (Sweden)

V. Jayaraj

2010-08-01

Full Text Available A Non-linear adaptive decision based algorithm with robust motion estimation technique is proposed for removal of impulse noise, Gaussian noise and mixed noise (impulse and Gaussian with edge and fine detail preservation in images and videos. The algorithm includes detection of corrupted pixels and the estimation of values for replacing the corrupted pixels. The main advantage of the proposed algorithm is that an appropriate filter is used for replacing the corrupted pixel based on the estimation of the noise variance present in the filtering window. This leads to reduced blurring and better fine detail preservation even at the high mixed noise density. It performs both spatial and temporal filtering for removal of the noises in the filter window of the videos. The Improved Cross Diamond Search Motion Estimation technique uses Least Median Square as a cost function, which shows improved performance than other motion estimation techniques with existing cost functions. The results show that the proposed algorithm outperforms the other algorithms in the visual point of view and in Peak Signal to Noise Ratio, Mean Square Error and Image Enhancement Factor.

Research on Construction of Road Network Database Based on Video Retrieval Technology

Directory of Open Access Journals (Sweden)

Wang Fengling

2017-01-01

Full Text Available Based on the characteristics of the video database and the basic structure of the video database and several typical video data models, the segmentation-based multi-level data model is used to describe the landscape information video database, the network database model and the road network management database system. Landscape information management system detailed design and implementation of a detailed preparation.

SIRSALE: integrated video database management tools

Science.gov (United States)

Brunie, Lionel; Favory, Loic; Gelas, J. P.; Lefevre, Laurent; Mostefaoui, Ahmed; Nait-Abdesselam, F.

2002-07-01

Video databases became an active field of research during the last decade. The main objective in such systems is to provide users with capabilities to friendly search, access and playback distributed stored video data in the same way as they do for traditional distributed databases. Hence, such systems need to deal with hard issues : (a) video documents generate huge volumes of data and are time sensitive (streams must be delivered at a specific bitrate), (b) contents of video data are very hard to be automatically extracted and need to be humanly annotated. To cope with these issues, many approaches have been proposed in the literature including data models, query languages, video indexing etc. In this paper, we present SIRSALE : a set of video databases management tools that allow users to manipulate video documents and streams stored in large distributed repositories. All the proposed tools are based on generic models that can be customized for specific applications using ad-hoc adaptation modules. More precisely, SIRSALE allows users to : (a) browse video documents by structures (sequences, scenes, shots) and (b) query the video database content by using a graphical tool, adapted to the nature of the target video documents. This paper also presents an annotating interface which allows archivists to describe the content of video documents. All these tools are coupled to a video player integrating remote VCR functionalities and are based on active network technology. So, we present how dedicated active services allow an optimized video transport for video streams (with Tamanoir active nodes). We then describe experiments of using SIRSALE on an archive of news video and soccer matches. The system has been demonstrated to professionals with a positive feedback. Finally, we discuss open issues and present some perspectives.

Induced Recall of Jane Austen's Novels: Films, Television, Videos.

Science.gov (United States)

Diaz de Chumaceiro, Cora L.

2000-01-01

Notes that the popularity of Jane Austen adaptations in theaters, television, and videos increases the probability that patients and therapists may recall these movies in treatment. Underscores excerpts from a comparison of an Austen novel with the psychoanalytic process and highlights available film adaptations in video format. (SC)

Comparison of parameter-adapted segmentation methods for fluorescence micrographs.

Science.gov (United States)

Held, Christian; Palmisano, Ralf; Häberle, Lothar; Hensel, Michael; Wittenberg, Thomas

2011-11-01

Interpreting images from fluorescence microscopy is often a time-consuming task with poor reproducibility. Various image processing routines that can help investigators evaluate the images are therefore useful. The critical aspect for a reliable automatic image analysis system is a robust segmentation algorithm that can perform accurate segmentation for different cell types. In this study, several image segmentation methods were therefore compared and evaluated in order to identify the most appropriate segmentation schemes that are usable with little new parameterization and robustly with different types of fluorescence-stained cells for various biological and biomedical tasks. The study investigated, compared, and enhanced four different methods for segmentation of cultured epithelial cells. The maximum-intensity linking (MIL) method, an improved MIL, a watershed method, and an improved watershed method based on morphological reconstruction were used. Three manually annotated datasets consisting of 261, 817, and 1,333 HeLa or L929 cells were used to compare the different algorithms. The comparisons and evaluations showed that the segmentation performance of methods based on the watershed transform was significantly superior to the performance of the MIL method. The results also indicate that using morphological opening by reconstruction can improve the segmentation of cells stained with a marker that exhibits the dotted surface of cells. Copyright © 2011 International Society for Advancement of Cytometry.

Adaptive Distributed Video Coding with Correlation Estimation using Expectation Propagation.

Science.gov (United States)

Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel

2012-10-15

Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method.

Adaptive distributed video coding with correlation estimation using expectation propagation

Science.gov (United States)

Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel

2012-10-01

Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method.

Interaction between High-Level and Low-Level Image Analysis for Semantic Video Object Extraction

Directory of Open Access Journals (Sweden)

Andrea Cavallaro

2004-06-01

Full Text Available The task of extracting a semantic video object is split into two subproblems, namely, object segmentation and region segmentation. Object segmentation relies on a priori assumptions, whereas region segmentation is data-driven and can be solved in an automatic manner. These two subproblems are not mutually independent, and they can benefit from interactions with each other. In this paper, a framework for such interaction is formulated. This representation scheme based on region segmentation and semantic segmentation is compatible with the view that image analysis and scene understanding problems can be decomposed into low-level and high-level tasks. Low-level tasks pertain to region-oriented processing, whereas the high-level tasks are closely related to object-level processing. This approach emulates the human visual system: what one “sees” in a scene depends on the scene itself (region segmentation as well as on the cognitive task (semantic segmentation at hand. The higher-level segmentation results in a partition corresponding to semantic video objects. Semantic video objects do not usually have invariant physical properties and the definition depends on the application. Hence, the definition incorporates complex domain-specific knowledge and is not easy to generalize. For the specific implementation used in this paper, motion is used as a clue to semantic information. In this framework, an automatic algorithm is presented for computing the semantic partition based on color change detection. The change detection strategy is designed to be immune to the sensor noise and local illumination variations. The lower-level segmentation identifies the partition corresponding to perceptually uniform regions. These regions are derived by clustering in an N-dimensional feature space, composed of static as well as dynamic image attributes. We propose an interaction mechanism between the semantic and the region partitions which allows to

Robust video object cosegmentation.

Science.gov (United States)

Wang, Wenguan; Shen, Jianbing; Li, Xuelong; Porikli, Fatih

2015-10-01

With ever-increasing volumes of video data, automatic extraction of salient object regions became even more significant for visual analytic solutions. This surge has also opened up opportunities for taking advantage of collective cues encapsulated in multiple videos in a cooperative manner. However, it also brings up major challenges, such as handling of drastic appearance, motion pattern, and pose variations, of foreground objects as well as indiscriminate backgrounds. Here, we present a cosegmentation framework to discover and segment out common object regions across multiple frames and multiple videos in a joint fashion. We incorporate three types of cues, i.e., intraframe saliency, interframe consistency, and across-video similarity into an energy optimization framework that does not make restrictive assumptions on foreground appearance and motion model, and does not require objects to be visible in all frames. We also introduce a spatio-temporal scale-invariant feature transform (SIFT) flow descriptor to integrate across-video correspondence from the conventional SIFT-flow into interframe motion flow from optical flow. This novel spatio-temporal SIFT flow generates reliable estimations of common foregrounds over the entire video data set. Experimental results show that our method outperforms the state-of-the-art on a new extensive data set (ViCoSeg).

Adaptive thresholding algorithm based on SAR images and wind data to segment oil spills along the northwest coast of the Iberian Peninsula

International Nuclear Information System (INIS)

Mera, David; Cotos, José M.; Varela-Pet, José; Garcia-Pineda, Oscar

2012-01-01

Highlights: ► We present an adaptive thresholding algorithm to segment oil spills. ► The segmentation algorithm is based on SAR images and wind field estimations. ► A Database of oil spill confirmations was used for the development of the algorithm. ► Wind field estimations have demonstrated to be useful for filtering look-alikes. ► Parallel programming has been successfully used to minimize processing time. - Abstract: Satellite Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillage on the ocean’s surface. Several surveillance applications have been developed based on this technology. Environmental variables such as wind speed should be taken into account for better SAR image segmentation. This paper presents an adaptive thresholding algorithm for detecting oil spills based on SAR data and a wind field estimation as well as its implementation as a part of a functional prototype. The algorithm was adapted to an important shipping route off the Galician coast (northwest Iberian Peninsula) and was developed on the basis of confirmed oil spills. Image testing revealed 99.93% pixel labelling accuracy. By taking advantage of multi-core processor architecture, the prototype was optimized to get a nearly 30% improvement in processing time.

Video Film Piracy in Nigeria: Interfacing to Integrate the Pirate ...

African Journals Online (AJOL)

It recommends the adoption of market segmentation policy in integrating the pirate, emphasises the run of video films in cinemas, halls etc before they go into the market and calls for a better synergy between producers and marketers among others. Key words: Identification, Interface, Integration, Market Segmentation ...

Adventure Racing and Organizational Behavior: Using Eco Challenge Video Clips to Stimulate Learning

Science.gov (United States)

Kenworthy-U'Ren, Amy; Erickson, Anthony

2009-01-01

In this article, the Eco Challenge race video is presented as a teaching tool for facilitating theory-based discussion and application in organizational behavior (OB) courses. Before discussing the intricacies of the video series itself, the authors present a pedagogically based rationale for using reality TV-based video segments in a classroom…

Despeckle filtering for ultrasound imaging and video II selected applications

CERN Document Server

Loizou, Christos P

2015-01-01

In ultrasound imaging and video visual perception is hindered by speckle multiplicative noise that degrades the quality. Noise reduction is therefore essential for improving the visual observation quality or as a pre-processing step for further automated analysis, such as image/video segmentation, texture analysis and encoding in ultrasound imaging and video. The goal of the first book (book 1 of 2 books) was to introduce the problem of speckle in ultrasound image and video as well as the theoretical background, algorithmic steps, and the MatlabTM for the following group of despeckle filters:

A low false negative filter for detecting rare bird species from short video segments using a probable observation data set-based EKF method.

Science.gov (United States)

Song, Dezhen; Xu, Yiliang

2010-09-01

We report a new filter to assist the search for rare bird species. Since a rare bird only appears in front of a camera with very low occurrence (e.g., less than ten times per year) for very short duration (e.g., less than a fraction of a second), our algorithm must have a very low false negative rate. We verify the bird body axis information with the known bird flying dynamics from the short video segment. Since a regular extended Kalman filter (EKF) cannot converge due to high measurement error and limited data, we develop a novel probable observation data set (PODS)-based EKF method. The new PODS-EKF searches the measurement error range for all probable observation data that ensures the convergence of the corresponding EKF in short time frame. The algorithm has been extensively tested using both simulated inputs and real video data of four representative bird species. In the physical experiments, our algorithm has been tested on rock pigeons and red-tailed hawks with 119 motion sequences. The area under the ROC curve is 95.0%. During the one-year search of ivory-billed woodpeckers, the system reduces the raw video data of 29.41 TB to only 146.7 MB (reduction rate 99.9995%).

Video watermarking for mobile phone applications

Science.gov (United States)

Mitrea, M.; Duta, S.; Petrescu, M.; Preteux, F.

2005-08-01

Nowadays, alongside with the traditional voice signal, music, video, and 3D characters tend to become common data to be run, stored and/or processed on mobile phones. Hence, to protect their related intellectual property rights also becomes a crucial issue. The video sequences involved in such applications are generally coded at very low bit rates. The present paper starts by presenting an accurate statistical investigation on such a video as well as on a very dangerous attack (the StirMark attack). The obtained results are turned into practice when adapting a spread spectrum watermarking method to such applications. The informed watermarking approach was also considered: an outstanding method belonging to this paradigm has been adapted and re evaluated under the low rate video constraint. The experimental results were conducted in collaboration with the SFR mobile services provider in France. They also allow a comparison between the spread spectrum and informed embedding techniques.

Action recognition in depth video from RGB perspective: A knowledge transfer manner

Science.gov (United States)

Chen, Jun; Xiao, Yang; Cao, Zhiguo; Fang, Zhiwen

2018-03-01

Different video modal for human action recognition has becoming a highly promising trend in the video analysis. In this paper, we propose a method for human action recognition from RGB video to Depth video using domain adaptation, where we use learned feature from RGB videos to do action recognition for depth videos. More specifically, we make three steps for solving this problem in this paper. First, different from image, video is more complex as it has both spatial and temporal information, in order to better encode this information, dynamic image method is used to represent each RGB or Depth video to one image, based on this, most methods for extracting feature in image can be used in video. Secondly, as video can be represented as image, so standard CNN model can be used for training and testing for videos, beside, CNN model can be also used for feature extracting as its powerful feature expressing ability. Thirdly, as RGB videos and Depth videos are belong to two different domains, in order to make two different feature domains has more similarity, domain adaptation is firstly used for solving this problem between RGB and Depth video, based on this, the learned feature from RGB video model can be directly used for Depth video classification. We evaluate the proposed method on one complex RGB-D action dataset (NTU RGB-D), and our method can have more than 2% accuracy improvement using domain adaptation from RGB to Depth action recognition.

A Modification of the Fuzzy Logic Based DASH Adaptation Scheme for Performance Improvement

Directory of Open Access Journals (Sweden)

Hyun Jun Kim

2018-01-01

Full Text Available We propose a modification of the fuzzy logic based DASH adaptation scheme (FDASH for seamless media service in time-varying network conditions. The proposed scheme (mFDASH selects a more appropriate bit-rate for the next segment by modification of the Fuzzy Logic Controller (FLC and estimates more accurate available bandwidth than FDASH scheme by using History-Based TCP Throughput Estimation. Moreover, mFDASH reduces the number of video bit-rate changes by applying Segment Bit-Rate Filtering Module (SBFM and employs Start Mechanism for clients to provide high-quality videos in the very beginning stage of the streaming service. Lastly, Sleeping Mechanism is applied to avoid any expected buffer overflow. We then use NS-3 Network Simulator to verify the performance of mFDASH. Upon the experimental results, mFDASH shows no buffer overflow within the limited buffer size, which is not guaranteed in FDASH. Also, we confirm that mFDASH provides the highest QoE to DASH clients among the three schemes (mFDASH, FDASH, and SVAA in Point-to-Point networks, Wi-Fi networks, and LTE networks, respectively.

Automated music selection of video ads

Directory of Open Access Journals (Sweden)

Wiesener Oliver

2017-07-01

Full Text Available The importance of video ads on social media platforms can be measured by views. For instance, Samsung’s commercial ad for one of its new smartphones reached more than 46 million viewers at Youtube. A video ad addresses the visual as well as the auditive sense of users. Often the visual sense is busy in the sense that users focus other screens than the screen with the video ad. This is called the second screen syndrome. Therefore, the importance of the audio channel seems to grow. To get back the visual attention of users that are deflected from other visual impulses it appears reasonable to adapt the music to the target group. Additionally, it appears useful to adapt the music to content of the video. Thus, the overall success of a video ad could by increased by increasing the attention of the users. Humans typically make the decision about the music of a video ad. If there is a correlation between music, products and target groups, a digitization of the music selection process seems to be possible. Since the digitization progress in the music sector is mainly focused on music composing this article strives for making a first step towards the digitization of the music selection.

Polyp Detection and Segmentation from Video Capsule Endoscopy: A Review

Directory of Open Access Journals (Sweden)

V. B. Surya Prasath

2016-12-01

Full Text Available Video capsule endoscopy (VCE is used widely nowadays for visualizing the gastrointestinal (GI tract. Capsule endoscopy exams are prescribed usually as an additional monitoring mechanism and can help in identifying polyps, bleeding, etc. To analyze the large scale video data produced by VCE exams, automatic image processing, computer vision, and learning algorithms are required. Recently, automatic polyp detection algorithms have been proposed with various degrees of success. Though polyp detection in colonoscopy and other traditional endoscopy procedure based images is becoming a mature field, due to its unique imaging characteristics, detecting polyps automatically in VCE is a hard problem. We review different polyp detection approaches for VCE imagery and provide systematic analysis with challenges faced by standard image processing and computer vision methods.

Bayesian Modeling of Temporal Coherence in Videos for Entity Discovery and Summarization.

Science.gov (United States)

Mitra, Adway; Biswas, Soma; Bhattacharyya, Chiranjib

2017-03-01

A video is understood by users in terms of entities present in it. Entity Discovery is the task of building appearance model for each entity (e.g., a person), and finding all its occurrences in the video. We represent a video as a sequence of tracklets, each spanning 10-20 frames, and associated with one entity. We pose Entity Discovery as tracklet clustering, and approach it by leveraging Temporal Coherence (TC): the property that temporally neighboring tracklets are likely to be associated with the same entity. Our major contributions are the first Bayesian nonparametric models for TC at tracklet-level. We extend Chinese Restaurant Process (CRP) to TC-CRP, and further to Temporally Coherent Chinese Restaurant Franchise (TC-CRF) to jointly model entities and temporal segments using mixture components and sparse distributions. For discovering persons in TV serial videos without meta-data like scripts, these methods show considerable improvement over state-of-the-art approaches to tracklet clustering in terms of clustering accuracy, cluster purity and entity coverage. The proposed methods can perform online tracklet clustering on streaming videos unlike existing approaches, and can automatically reject false tracklets. Finally we discuss entity-driven video summarization- where temporal segments of the video are selected based on the discovered entities, to create a semantically meaningful summary.

Brain activity and desire for Internet video game play.

Science.gov (United States)

Han, Doug Hyun; Bolo, Nicolas; Daniels, Melissa A; Arenella, Lynn; Lyoo, In Kyoon; Renshaw, Perry F

2011-01-01

Recent studies have suggested that the brain circuitry mediating cue-induced desire for video games is similar to that elicited by cues related to drugs and alcohol. We hypothesized that desire for Internet video games during cue presentation would activate similar brain regions to those that have been linked with craving for drugs or pathologic gambling. This study involved the acquisition of diagnostic magnetic resonance imaging and functional magnetic resonance imaging data from 19 healthy male adults (age, 18-23 years) following training and a standardized 10-day period of game play with a specified novel Internet video game, "War Rock" (K2 Network, Irvine, CA). Using segments of videotape consisting of 5 contiguous 90-second segments of alternating resting, matched control, and video game-related scenes, desire to play the game was assessed using a 7-point visual analogue scale before and after presentation of the videotape. In responding to Internet video game stimuli, compared with neutral control stimuli, significantly greater activity was identified in left inferior frontal gyrus, left parahippocampal gyrus, right and left parietal lobe, right and left thalamus, and right cerebellum (false discovery rate Internet video game showed significantly greater activity in right medial frontal lobe, right and left frontal precentral gyrus, right parietal postcentral gyrus, right parahippocampal gyrus, and left parietal precuneus gyrus. Controlling for total game time, reported desire for the Internet video game in the subjects who played more Internet video game was positively correlated with activation in right medial frontal lobe and right parahippocampal gyrus. The present findings suggest that cue-induced activation to Internet video game stimuli may be similar to that observed during cue presentation in persons with substance dependence or pathologic gambling. In particular, cues appear to commonly elicit activity in the dorsolateral prefrontal, orbitofrontal

The Simple Video Coder: A free tool for efficiently coding social video data.

Science.gov (United States)

Barto, Daniel; Bird, Clark W; Hamilton, Derek A; Fink, Brandi C

2017-08-01

Videotaping of experimental sessions is a common practice across many disciplines of psychology, ranging from clinical therapy, to developmental science, to animal research. Audio-visual data are a rich source of information that can be easily recorded; however, analysis of the recordings presents a major obstacle to project completion. Coding behavior is time-consuming and often requires ad-hoc training of a student coder. In addition, existing software is either prohibitively expensive or cumbersome, which leaves researchers with inadequate tools to quickly process video data. We offer the Simple Video Coder-free, open-source software for behavior coding that is flexible in accommodating different experimental designs, is intuitive for students to use, and produces outcome measures of event timing, frequency, and duration. Finally, the software also offers extraction tools to splice video into coded segments suitable for training future human coders or for use as input for pattern classification algorithms.

Deep learning for quality assessment in live video streaming

NARCIS (Netherlands)

Torres Vega, M.; Mocanu, D.C.; Famaey, J.; Stavrou, S.; Liotta, A.

Video content providers put stringent requirements on the quality assessment methods realized on their services. They need to be accurate, real-time, adaptable to new content, and scalable as the video set grows. In this letter, we introduce a novel automated and computationally efficient video

Upper-Limb Rehabilitation With Adaptive Video Games for Preschool Children With Developmental Disabilities.

Science.gov (United States)

Hsieh, Hsieh-Chun; Lin, Hung-Yu; Chiu, Wen-Hsin; Meng, Ling Fu; Liu, Chun Kai

2015-01-01

This study used a novel device to make video games accessible to children with developmental disabilities (DD) by modifying the training software and interfaces to enhance motor training. In the pretest-posttest design, 20 children (13 boys, 7 girls; mean age=5.2 yr) with DD received adaptive upper-limb motor rehabilitation consisting of fifteen 30-min individual sessions 3 times per week for 5 wk. Improvement in Beery-Buktenica Developmental Test of Visual Motor Integration and Peabody Developmental Motor Scales, Second Edition, scores for children with DD indicated significant differences between pretest and posttest. The rehabilitation device modified for the needs of children with DD is effective in improving visual-motor performance of children with DD. Copyright © 2015 by the American Occupational Therapy Association, Inc.

Celiac Family Health Education Video Series

Medline Plus

Full Text Available ... Boston Children's Hospital will teach you and your family about a healthful celiac lifestyle. Education is key in making parents feel more at ease and allow children with celiac disease to live happy and productive lives. Each of our video segments ... I. Introduction : Experiencing ...

Motion based segmentation for robot vision using adapted EM algorithm

NARCIS (Netherlands)

Zhao, Wei; Roos, Nico

2016-01-01

Robots operate in a dynamic world in which objects are often moving. The movement of objects may help the robot to segment the objects from the background. The result of the segmentation can subsequently be used to identify the objects. This paper investigates the possibility of segmenting objects

Making Sense of Video Analytics: Lessons Learned from Clickstream Interactions, Attitudes, and Learning Outcome in a Video-Assisted Course

Directory of Open Access Journals (Sweden)

Michail N. Giannakos

2015-02-01

Full Text Available Online video lectures have been considered an instructional media for various pedagogic approaches, such as the flipped classroom and open online courses. In comparison to other instructional media, online video affords the opportunity for recording student clickstream patterns within a video lecture. Video analytics within lecture videos may provide insights into student learning performance and inform the improvement of video-assisted teaching tactics. Nevertheless, video analytics are not accessible to learning stakeholders, such as researchers and educators, mainly because online video platforms do not broadly share the interactions of the users with their systems. For this purpose, we have designed an open-access video analytics system for use in a video-assisted course. In this paper, we present a longitudinal study, which provides valuable insights through the lens of the collected video analytics. In particular, we found that there is a relationship between video navigation (repeated views and the level of cognition/thinking required for a specific video segment. Our results indicated that learning performance progress was slightly improved and stabilized after the third week of the video-assisted course. We also found that attitudes regarding easiness, usability, usefulness, and acceptance of this type of course remained at the same levels throughout the course. Finally, we triangulate analytics from diverse sources, discuss them, and provide the lessons learned for further development and refinement of video-assisted courses and practices.

Skype resilience to high motion videos

NARCIS (Netherlands)

Exarchakos, G.; Druda, L.; Menkovski, V.; Bellavista, P.; Liotta, A.

Skype is one of the most popular video call services in the current Internet world. One of its strengths is the use of an adaptive mechanism to match the constraints of the underlying network. This work is focused on how this mechanism can maximize the video quality as perceived by the viewers using

Comparison of the Effects of Video Modeling with Narration vs. Video Modeling on the Functional Skill Acquisition of Adolescents with Autism

Science.gov (United States)

Smith, Molly; Ayres, Kevin; Mechling, Linda; Smith, Katie

2013-01-01

The purpose of this study was to compare the effects of two forms of video modeling: video modeling that includes narration (VMN) and video models without narration (VM) on skill acquisition of four adolescent boys with a primary diagnosis of autism enrolled in an Extended School Year (ESY) summer program. An adapted alternating treatment design…

Adaptive modeling of sky for video processing and coding applications

NARCIS (Netherlands)

Zafarifar, B.; With, de P.H.N.; Lagendijk, R.L.; Weber, Jos H.; Berg, van den A.F.M.

2006-01-01

Video content analysis for still- and moving images can be used for various applications, such as high-level semantic-driven operations or pixel-level contentdependent image manipulation. Within video content analysis, sky regions of an image form visually important objects, for which interesting

Can Skype be used beyond video calling?

NARCIS (Netherlands)

Exarchakos, G.; Menkovski, V.; Liotta, A.

2011-01-01

Skype nodes generate a substantial part of real-time bi-directional video traffic nowadays. Employing a range of adaptive mechanisms, the application configures video streaming to meet the requirements of the communication and constraints of the underlying network. While other related works focus on

Rate control scheme for consistent video quality in scalable video codec.

Science.gov (United States)

Seo, Chan-Won; Han, Jong-Ki; Nguyen, Truong Q

2011-08-01

Multimedia data delivered to mobile devices over wireless channels or the Internet are complicated by bandwidth fluctuation and the variety of mobile devices. Scalable video coding has been developed as an extension of H.264/AVC to solve this problem. Since scalable video codec provides various scalabilities to adapt the bitstream for the channel conditions and terminal types, scalable codec is one of the useful codecs for wired or wireless multimedia communication systems, such as IPTV and streaming services. In such scalable multimedia communication systems, video quality fluctuation degrades the visual perception significantly. It is important to efficiently use the target bits in order to maintain a consistent video quality or achieve a small distortion variation throughout the whole video sequence. The scheme proposed in this paper provides a useful function to control video quality in applications supporting scalability, whereas conventional schemes have been proposed to control video quality in the H.264 and MPEG-4 systems. The proposed algorithm decides the quantization parameter of the enhancement layer to maintain a consistent video quality throughout the entire sequence. The video quality of the enhancement layer is controlled based on a closed-form formula which utilizes the residual data and quantization error of the base layer. The simulation results show that the proposed algorithm controls the frame quality of the enhancement layer in a simple operation, where the parameter decision algorithm is applied to each frame.

Coding Transparency in Object-Based Video

DEFF Research Database (Denmark)

Aghito, Shankar Manuel; Forchhammer, Søren

2006-01-01

A novel algorithm for coding gray level alpha planes in object-based video is presented. The scheme is based on segmentation in multiple layers. Different coders are specifically designed for each layer. In order to reduce the bit rate, cross-layer redundancies as well as temporal correlation are...

REAL TIME SPEED ESTIMATION FROM MONOCULAR VIDEO

Directory of Open Access Journals (Sweden)

M. S. Temiz

2012-07-01

Full Text Available In this paper, detailed studies have been performed for developing a real time system to be used for surveillance of the traffic flow by using monocular video cameras to find speeds of the vehicles for secure travelling are presented. We assume that the studied road segment is planar and straight, the camera is tilted downward a bridge and the length of one line segment in the image is known. In order to estimate the speed of a moving vehicle from a video camera, rectification of video images is performed to eliminate the perspective effects and then the interest region namely the ROI is determined for tracking the vehicles. Velocity vectors of a sufficient number of reference points are identified on the image of the vehicle from each video frame. For this purpose sufficient number of points from the vehicle is selected, and these points must be accurately tracked on at least two successive video frames. In the second step, by using the displacement vectors of the tracked points and passed time, the velocity vectors of those points are computed. Computed velocity vectors are defined in the video image coordinate system and displacement vectors are measured by the means of pixel units. Then the magnitudes of the computed vectors in the image space are transformed to the object space to find the absolute values of these magnitudes. The accuracy of the estimated speed is approximately ±1 – 2 km/h. In order to solve the real time speed estimation problem, the authors have written a software system in C++ programming language. This software system has been used for all of the computations and test applications.

Video repairing under variable illumination using cyclic motions.

Science.gov (United States)

Jia, Jiaya; Tai, Yu-Wing; Wu, Tai-Pang; Tang, Chi-Keung

2006-05-01

This paper presents a complete system capable of synthesizing a large number of pixels that are missing due to occlusion or damage in an uncalibrated input video. These missing pixels may correspond to the static background or cyclic motions of the captured scene. Our system employs user-assisted video layer segmentation, while the main processing in video repair is fully automatic. The input video is first decomposed into the color and illumination videos. The necessary temporal consistency is maintained by tensor voting in the spatio-temporal domain. Missing colors and illumination of the background are synthesized by applying image repairing. Finally, the occluded motions are inferred by spatio-temporal alignment of collected samples at multiple scales. We experimented on our system with some difficult examples with variable illumination, where the capturing camera can be stationary or in motion.

From Watching Newsreels to Making Videos

Science.gov (United States)

Hammond, Thomas C.; Lee, John

2009-01-01

From filmstrips to documentaries to Hollywood movies, social studies teachers have a long tradition of using video in the classroom. In fact, some of the earliest films made were purposefully adapted for social studies instruction as photoplays depicting pivotal events in U.S. history. A key difference between digital video and its predecessors is…

Brain activity and desire for internet video game play

Science.gov (United States)

Han, Doug Hyun; Bolo, Nicolas; Daniels, Melissa A.; Arenella, Lynn; Lyoo, In Kyoon; Renshaw, Perry F.

2010-01-01

Objective Recent studies have suggested that the brain circuitry mediating cue induced desire for video games is similar to that elicited by cues related to drugs and alcohol. We hypothesized that desire for internet video games during cue presentation would activate similar brain regions to those which have been linked with craving for drugs or pathological gambling. Methods This study involved the acquisition of diagnostic MRI and fMRI data from 19 healthy male adults (ages 18–23 years) following training and a standardized 10-day period of game play with a specified novel internet video game, “War Rock” (K-network®). Using segments of videotape consisting of five contiguous 90-second segments of alternating resting, matched control and video game-related scenes, desire to play the game was assessed using a seven point visual analogue scale before and after presentation of the videotape. Results In responding to internet video game stimuli, compared to neutral control stimuli, significantly greater activity was identified in left inferior frontal gyrus, left parahippocampal gyrus, right and left parietal lobe, right and left thalamus, and right cerebellum (FDR video game (MIGP) cohort showed significantly greater activity in right medial frontal lobe, right and left frontal pre-central gyrus, right parietal post-central gyrus, right parahippocampal gyrus, and left parietal precuneus gyrus. Controlling for total game time, reported desire for the internet video game in the MIGP cohort was positively correlated with activation in right medial frontal lobe and right parahippocampal gyrus. Discussion The present findings suggest that cue-induced activation to internet video game stimuli may be similar to that observed during cue presentation in persons with substance dependence or pathological gambling. In particular, cues appear to commonly elicit activity in the dorsolateral prefrontal, orbitofrontal cortex, parahippocampal gyrus, and thalamus. PMID:21220070

The Legal Nature of Video Games – Adapting Copyright Law to Multimedia

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Julian Simon Stein

2015-06-01

Full Text Available In Copyright Law, video games are still a contentious matter. The multimedia nature of games brings up the question on how to define their legal nature. While there are several original underlying works in video games such as computer programs, artistic works, musical works, dramatic works etc., video games enjoy protection as films or audiovisual works respectively in many jurisdictions, making video games an arrangement of a multiplicity of works. However, some have argued to define video games as a single 'multimedia work' rather than a product of many works of copyright.This article analyses the different types of original and derivative works contained in video games before evaluating the necessity and feasibility of a multimedia category of work, arguing in favour of the current system.

Motion video analysis using planar parallax

Science.gov (United States)

Sawhney, Harpreet S.

1994-04-01

Motion and structure analysis in video sequences can lead to efficient descriptions of objects and their motions. Interesting events in videos can be detected using such an analysis--for instance independent object motion when the camera itself is moving, figure-ground segregation based on the saliency of a structure compared to its surroundings. In this paper we present a method for 3D motion and structure analysis that uses a planar surface in the environment as a reference coordinate system to describe a video sequence. The motion in the video sequence is described as the motion of the reference plane, and the parallax motion of all the non-planar components of the scene. It is shown how this method simplifies the otherwise hard general 3D motion analysis problem. In addition, a natural coordinate system in the environment is used to describe the scene which can simplify motion based segmentation. This work is a part of an ongoing effort in our group towards video annotation and analysis for indexing and retrieval. Results from a demonstration system being developed are presented.

Content Adaptive Lagrange Multiplier Selection for Rate-Distortion Optimization in 3-D Wavelet-Based Scalable Video Coding

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Ying Chen

2018-03-01

Full Text Available Rate-distortion optimization (RDO plays an essential role in substantially enhancing the coding efficiency. Currently, rate-distortion optimized mode decision is widely used in scalable video coding (SVC. Among all the possible coding modes, it aims to select the one which has the best trade-off between bitrate and compression distortion. Specifically, this tradeoff is tuned through the choice of the Lagrange multiplier. Despite the prevalence of conventional method for Lagrange multiplier selection in hybrid video coding, the underlying formulation is not applicable to 3-D wavelet-based SVC where the explicit values of the quantization step are not available, with on consideration of the content features of input signal. In this paper, an efficient content adaptive Lagrange multiplier selection algorithm is proposed in the context of RDO for 3-D wavelet-based SVC targeting quality scalability. Our contributions are two-fold. First, we introduce a novel weighting method, which takes account of the mutual information, gradient per pixel, and texture homogeneity to measure the temporal subband characteristics after applying the motion-compensated temporal filtering (MCTF technique. Second, based on the proposed subband weighting factor model, we derive the optimal Lagrange multiplier. Experimental results demonstrate that the proposed algorithm enables more satisfactory video quality with negligible additional computational complexity.

Video Conferencing for a Virtual Seminar Room

DEFF Research Database (Denmark)

Forchhammer, Søren; Fosgerau, A.; Hansen, Peter Søren K.

2002-01-01

A PC-based video conferencing system for a virtual seminar room is presented. The platform is enhanced with DSPs for audio and video coding and processing. A microphone array is used to facilitate audio based speaker tracking, which is used for adaptive beam-forming and automatic camera...

Watch it! The Influence of Forced Pre-roll Video Ads on Consumer Perceptions

NARCIS (Netherlands)

Hegner, Sabrina; Hegner, Sabrina M.; Kusse, Daniel C.; Pruyn, Adriaan T.H.; Verlegh, Peeter; Voorveld, Hilde; Eisend, Martin

2016-01-01

The internet is the fastest growing advertising segment in the world (Gambaro and Puglisi, 2012). One specific online advertising format that is growing very rapidly is online video advertising. This advertising format owes its explosive growth to the rapid acceleration of online video viewing and

Viewer Discussion is Advised. Video Clubs Focus Teacher Discussion on Student Learning

Directory of Open Access Journals (Sweden)

Elizabeth A. van Es

2014-06-01

Full Text Available Video is being used widely in professional development. Yet, little is known about how to design video-based learning environments that are productive for teacher learning. One promising model is a video club (Sherin, 2000. Video clubs bring teachers together to view and analyze video segments from one another’s classrooms. The idea is that by watching and discussing video segments focused on student thinking, teachers will learn practices for identifying and analyzing noteworthy student thinking during instruction and can use what they learn to inform their instructional decisions. This paper addresses issues to consider when setting up a video club for teacher education, such as defining goals for using video, establishing norms for viewing and discussing one another’s teaching, selecting clips for analysis, and facilitating teacher discussions. Si consiglia la discussione tra osservatori. Nei Video Club gli insegnanti mettono a fuoco le modalità con cui gli studenti apprendono.Il video è stato ampiamente utilizzato per la formazione professionale. Tuttavia poche sono le conoscenze relative alla progettazione di ambienti di apprendimento basati su video che siano efficaci per la formazione degli insegnanti. Un modello promettente è il “video club” (Sherin, 2000. Video club uniscono insegnanti che guardano ed analizzano insieme segmenti video delle proprie rispettive classi. L'idea è che gli insegnanti, guardando e discutendo segmenti video centrati sul pensiero degli alunni, imparino ad adottare durante l’insegnamento pratiche d'identificazione e analisi di pensieri degli alunni degni di nota e possano poi utilizzare ciò che hanno imparato nelle decisioni didattiche. Questo articolo affronta le questioni da considerare quando si configura un video club per la formazione degli insegnanti, come ad esempio la definizione di obiettivi per l'utilizzo dei video, le norme per la visione e discussione dei rispettivi video, la selezione

Indexed Captioned Searchable Videos: A Learning Companion for STEM Coursework

Science.gov (United States)

Tuna, Tayfun; Subhlok, Jaspal; Barker, Lecia; Shah, Shishir; Johnson, Olin; Hovey, Christopher

2017-02-01

Videos of classroom lectures have proven to be a popular and versatile learning resource. A key shortcoming of the lecture video format is accessing the content of interest hidden in a video. This work meets this challenge with an advanced video framework featuring topical indexing, search, and captioning (ICS videos). Standard optical character recognition (OCR) technology was enhanced with image transformations for extraction of text from video frames to support indexing and search. The images and text on video frames is analyzed to divide lecture videos into topical segments. The ICS video player integrates indexing, search, and captioning in video playback providing instant access to the content of interest. This video framework has been used by more than 70 courses in a variety of STEM disciplines and assessed by more than 4000 students. Results presented from the surveys demonstrate the value of the videos as a learning resource and the role played by videos in a students learning process. Survey results also establish the value of indexing and search features in a video platform for education. This paper reports on the development and evaluation of ICS videos framework and over 5 years of usage experience in several STEM courses.

Strategic market segmentation

Directory of Open Access Journals (Sweden)

Maričić Branko R.

2015-01-01

Full Text Available Strategic planning of marketing activities is the basis of business success in modern business environment. Customers are not homogenous in their preferences and expectations. Formulating an adequate marketing strategy, focused on realization of company's strategic objectives, requires segmented approach to the market that appreciates differences in expectations and preferences of customers. One of significant activities in strategic planning of marketing activities is market segmentation. Strategic planning imposes a need to plan marketing activities according to strategically important segments on the long term basis. At the same time, there is a need to revise and adapt marketing activities on the short term basis. There are number of criteria based on which market segmentation is performed. The paper will consider effectiveness and efficiency of different market segmentation criteria based on empirical research of customer expectations and preferences. The analysis will include traditional criteria and criteria based on behavioral model. The research implications will be analyzed from the perspective of selection of the most adequate market segmentation criteria in strategic planning of marketing activities.

Error and Congestion Resilient Video Streaming over Broadband Wireless

Directory of Open Access Journals (Sweden)

Laith Al-Jobouri

2015-04-01

Full Text Available In this paper, error resilience is achieved by adaptive, application-layer rateless channel coding, which is used to protect H.264/Advanced Video Coding (AVC codec data-partitioned videos. A packetization strategy is an effective tool to control error rates and, in the paper, source-coded data partitioning serves to allocate smaller packets to more important compressed video data. The scheme for doing this is applied to real-time streaming across a broadband wireless link. The advantages of rateless code rate adaptivity are then demonstrated in the paper. Because the data partitions of a video slice are each assigned to different network packets, in congestion-prone wireless networks the increased number of packets per slice and their size disparity may increase the packet loss rate from buffer overflows. As a form of congestion resilience, this paper recommends packet-size dependent scheduling as a relatively simple way of alleviating the buffer-overflow problem arising from data-partitioned packets. The paper also contributes an analysis of data partitioning and packet sizes as a prelude to considering scheduling regimes. The combination of adaptive channel coding and prioritized packetization for error resilience with packet-size dependent packet scheduling results in a robust streaming scheme specialized for broadband wireless and real-time streaming applications such as video conferencing, video telephony, and telemedicine.

Activity-based exploitation of Full Motion Video (FMV)

Science.gov (United States)

Kant, Shashi

2012-06-01

Video has been a game-changer in how US forces are able to find, track and defeat its adversaries. With millions of minutes of video being generated from an increasing number of sensor platforms, the DOD has stated that the rapid increase in video is overwhelming their analysts. The manpower required to view and garner useable information from the flood of video is unaffordable, especially in light of current fiscal restraints. "Search" within full-motion video has traditionally relied on human tagging of content, and video metadata, to provision filtering and locate segments of interest, in the context of analyst query. Our approach utilizes a novel machine-vision based approach to index FMV, using object recognition & tracking, events and activities detection. This approach enables FMV exploitation in real-time, as well as a forensic look-back within archives. This approach can help get the most information out of video sensor collection, help focus the attention of overburdened analysts form connections in activity over time and conserve national fiscal resources in exploiting FMV.

Low latency adaptive streaming of HD H.264 video over 802.11 wireless networks with cross-layer feedback

Science.gov (United States)

Patti, Andrew; Tan, Wai-tian; Shen, Bo

2007-09-01

Streaming video in consumer homes over wireless IEEE 802.11 networks is becoming commonplace. Wireless 802.11 networks pose unique difficulties for streaming high definition (HD), low latency video due to their error-prone physical layer and media access procedures which were not designed for real-time traffic. HD video streaming, even with sophisticated H.264 encoding, is particularly challenging due to the large number of packet fragments per slice. Cross-layer design strategies have been proposed to address the issues of video streaming over 802.11. These designs increase streaming robustness by imposing some degree of monitoring and control over 802.11 parameters from application level, or by making the 802.11 layer media-aware. Important contributions are made, but none of the existing approaches directly take the 802.11 queuing into account. In this paper we take a different approach and propose a cross-layer design allowing direct, expedient control over the wireless packet queue, while obtaining timely feedback on transmission status for each packet in a media flow. This method can be fully implemented on a media sender with no explicit support or changes required to the media client. We assume that due to congestion or deteriorating signal-to-noise levels, the available throughput may drop substantially for extended periods of time, and thus propose video source adaptation methods that allow matching the bit-rate to available throughput. A particular H.264 slice encoding is presented to enable seamless stream switching between streams at multiple bit-rates, and we explore using new computationally efficient transcoding methods when only a high bit-rate stream is available.

Adaptive segmentation of nuclei in H&S stained tendon microscopy

Science.gov (United States)

Chuang, Bo-I.; Wu, Po-Ting; Hsu, Jian-Han; Jou, I.-Ming; Su, Fong-Chin; Sun, Yung-Nien

2015-12-01

Tendiopathy is a popular clinical issue in recent years. In most cases like trigger finger or tennis elbow, the pathology change can be observed under H and E stained tendon microscopy. However, the qualitative analysis is too subjective and thus the results heavily depend on the observers. We develop an automatic segmentation procedure which segments and counts the nuclei in H and E stained tendon microscopy fast and precisely. This procedure first determines the complexity of images and then segments the nuclei from the image. For the complex images, the proposed method adopts sampling-based thresholding to segment the nuclei. While for the simple images, the Laplacian-based thresholding is employed to re-segment the nuclei more accurately. In the experiments, the proposed method is compared with the experts outlined results. The nuclei number of proposed method is closed to the experts counted, and the processing time of proposed method is much faster than the experts'.

Classification and Weakly Supervised Pain Localization using Multiple Segment Representation.

Science.gov (United States)

Sikka, Karan; Dhall, Abhinav; Bartlett, Marian Stewart

2014-10-01

Automatic pain recognition from videos is a vital clinical application and, owing to its spontaneous nature, poses interesting challenges to automatic facial expression recognition (AFER) research. Previous pain vs no-pain systems have highlighted two major challenges: (1) ground truth is provided for the sequence, but the presence or absence of the target expression for a given frame is unknown, and (2) the time point and the duration of the pain expression event(s) in each video are unknown. To address these issues we propose a novel framework (referred to as MS-MIL) where each sequence is represented as a bag containing multiple segments, and multiple instance learning (MIL) is employed to handle this weakly labeled data in the form of sequence level ground-truth. These segments are generated via multiple clustering of a sequence or running a multi-scale temporal scanning window, and are represented using a state-of-the-art Bag of Words (BoW) representation. This work extends the idea of detecting facial expressions through 'concept frames' to 'concept segments' and argues through extensive experiments that algorithms such as MIL are needed to reap the benefits of such representation. The key advantages of our approach are: (1) joint detection and localization of painful frames using only sequence-level ground-truth, (2) incorporation of temporal dynamics by representing the data not as individual frames but as segments, and (3) extraction of multiple segments, which is well suited to signals with uncertain temporal location and duration in the video. Extensive experiments on UNBC-McMaster Shoulder Pain dataset highlight the effectiveness of the approach by achieving competitive results on both tasks of pain classification and localization in videos. We also empirically evaluate the contributions of different components of MS-MIL. The paper also includes the visualization of discriminative facial patches, important for pain detection, as discovered by our

Social Practices around Personal Videos using the Web

NARCIS (Netherlands)

R.L. Guimarães (Rodrigo); P.S. Cesar Garcia (Pablo Santiago); D.C.A. Bulterman (Dick); I. Kegel; P. Ljungstrand

2011-01-01

htmlabstractSocial multimedia is changing the way people interact with each other, transforming old practices on political activism, social participation and interpersonal relationships. Sharing dynamically created video segments is a prime example of this social transformation. This paper reports

BlobContours: adapting Blobworld for supervised color- and texture-based image segmentation

Science.gov (United States)

Vogel, Thomas; Nguyen, Dinh Quyen; Dittmann, Jana

2006-01-01

Extracting features is the first and one of the most crucial steps in recent image retrieval process. While the color features and the texture features of digital images can be extracted rather easily, the shape features and the layout features depend on reliable image segmentation. Unsupervised image segmentation, often used in image analysis, works on merely syntactical basis. That is, what an unsupervised segmentation algorithm can segment is only regions, but not objects. To obtain high-level objects, which is desirable in image retrieval, human assistance is needed. Supervised image segmentations schemes can improve the reliability of segmentation and segmentation refinement. In this paper we propose a novel interactive image segmentation technique that combines the reliability of a human expert with the precision of automated image segmentation. The iterative procedure can be considered a variation on the Blobworld algorithm introduced by Carson et al. from EECS Department, University of California, Berkeley. Starting with an initial segmentation as provided by the Blobworld framework, our algorithm, namely BlobContours, gradually updates it by recalculating every blob, based on the original features and the updated number of Gaussians. Since the original algorithm has hardly been designed for interactive processing we had to consider additional requirements for realizing a supervised segmentation scheme on the basis of Blobworld. Increasing transparency of the algorithm by applying usercontrolled iterative segmentation, providing different types of visualization for displaying the segmented image and decreasing computational time of segmentation are three major requirements which are discussed in detail.

KAMUTHE video microanalysis system for use in Brazil: translation, cross-cultural adaptation and evidence of validity and reliability

Directory of Open Access Journals (Sweden)

Gustavo Schulz Gattino

2016-11-01

Full Text Available Background KAMUTHE is a video microanalysis system which observes preverbal communication within the music therapy setting. This system is indicated for children with autism spectrum disorder (ASD or multiple disabilities. The purpose of this study was to translate, adapt to Brazilian Portuguese language and analyze some psychometric properties (reliability and validity evidence of KAMUTHE administration in Brazil for individuals with ASD. Participants and procedure Translation, back translation, analysis by judges, and pilot application were performed to obtain evidence of content and face validity. The second part of this study was to administer KAMUTHE in 39 consecutive children with ASD. An individual session of improvisational music therapy was applied to assess the different behaviors included in KAMUTHE. The intra-rater reliability, concurrent validity and convergent validity were analyzed. Results Translation and cross-cultural adaptation were followed and some cultural adaptations were needed. Inter-rater reliability was very good (ICCs 0.95-0.99 for the three child’s behaviors analyzed. Criteria validity with a moderate negative association was found (r = –.38, p = .017 comparing the behavior “Gazes at therapist” and the level of ASD along with the Childhood Autism Rating Scale (CARS. Convergent validity was established between the behavior “Gazes at therapist” and the two nonlinguistic communication scales (social interaction and interests of the Children’s Communication Checklist (CCC with a moderate correlation (r = –.43, p = .005. Conclusions The administration of the KAMUTHE video microanalysis system showed positive results in children with ASD. Further studies are needed to improve the reliability and validity of the instrument in Brazil.

Comparisons of adaptive TIN modelling filtering method and threshold segmentation filtering method of LiDAR point cloud

International Nuclear Information System (INIS)

Chen, Lin; Fan, Xiangtao; Du, Xiaoping

2014-01-01

Point cloud filtering is the basic and key step in LiDAR data processing. Adaptive Triangle Irregular Network Modelling (ATINM) algorithm and Threshold Segmentation on Elevation Statistics (TSES) algorithm are among the mature algorithms. However, few researches concentrate on the parameter selections of ATINM and the iteration condition of TSES, which can greatly affect the filtering results. First the paper presents these two key problems under two different terrain environments. For a flat area, small height parameter and angle parameter perform well and for areas with complex feature changes, large height parameter and angle parameter perform well. One-time segmentation is enough for flat areas, and repeated segmentations are essential for complex areas. Then the paper makes comparisons and analyses of the results by these two methods. ATINM has a larger I error in both two data sets as it sometimes removes excessive points. TSES has a larger II error in both two data sets as it ignores topological relations between points. ATINM performs well even with a large region and a dramatic topology while TSES is more suitable for small region with flat topology. Different parameters and iterations can cause relative large filtering differences

Gradual cut detection using low-level vision for digital video

Science.gov (United States)

Lee, Jae-Hyun; Choi, Yeun-Sung; Jang, Ok-bae

1996-09-01

Digital video computing and organization is one of the important issues in multimedia system, signal compression, or database. Video should be segmented into shots to be used for identification and indexing. This approach requires a suitable method to automatically locate cut points in order to separate shot in a video. Automatic cut detection to isolate shots in a video has received considerable attention due to many practical applications; our video database, browsing, authoring system, retrieval and movie. Previous studies are based on a set of difference mechanisms and they measured the content changes between video frames. But they could not detect more special effects which include dissolve, wipe, fade-in, fade-out, and structured flashing. In this paper, a new cut detection method for gradual transition based on computer vision techniques is proposed. And then, experimental results applied to commercial video are presented and evaluated.

Assessment of Active Video Gaming Using Adapted Controllers by Individuals With Physical Disabilities: A Protocol.

Science.gov (United States)

Malone, Laurie A; Padalabalanarayanan, Sangeetha; McCroskey, Justin; Thirumalai, Mohanraj

2017-06-16

Individuals with disabilities are typically more sedentary and less fit compared to their peers without disabilities. Furthermore, engaging in physical activity can be extremely challenging due to physical impairments associated with disability and fewer opportunities to participate. One option for increasing physical activity is playing active video games (AVG), a category of video games that requires much more body movement for successful play than conventional push-button or joystick actions. However, many current AVGs are inaccessible or offer limited play options for individuals who are unable to stand, have balance issues, poor motor control, or cannot use their lower body to perform game activities. Making AVGs accessible to people with disabilities offers an innovative approach to overcoming various barriers to participation in physical activity. Our aim was to compare the effect of off-the-shelf and adapted game controllers on quality of game play, enjoyment, and energy expenditure during active video gaming in persons with physical disabilities, specifically those with mobility impairments (ie, unable to stand, balance issues, poor motor control, unable to use lower extremity for gameplay). The gaming controllers to be evaluated include off-the-shelf and adapted versions of the Wii Fit balance board and gaming mat. Participants (10-60 years old) came to the laboratory a total of three times. During the first visit, participants completed a functional assessment and became familiar with the equipment and games to be played. For the functional assessment, participants performed 18 functional movement tasks from the International Classification of Functioning, Disability, and Health. They also answered a series of questions from the Patient Reported Outcomes Measurement Information System and Quality of Life in Neurological Conditions measurement tools, to provide a personal perspective regarding their own functional ability. For Visit 2, metabolic data were

On the definition of adapted audio/video profiles for high-quality video calling services over LTE/4G

Science.gov (United States)

Ndiaye, Maty; Quinquis, Catherine; Larabi, Mohamed Chaker; Le Lay, Gwenael; Saadane, Hakim; Perrine, Clency

2014-01-01

During the last decade, the important advances and widespread availability of mobile technology (operating systems, GPUs, terminal resolution and so on) have encouraged a fast development of voice and video services like video-calling. While multimedia services have largely grown on mobile devices, the generated increase of data consumption is leading to the saturation of mobile networks. In order to provide data with high bit-rates and maintain performance as close as possible to traditional networks, the 3GPP (The 3rd Generation Partnership Project) worked on a high performance standard for mobile called Long Term Evolution (LTE). In this paper, we aim at expressing recommendations related to audio and video media profiles (selection of audio and video codecs, bit-rates, frame-rates, audio and video formats) for a typical video-calling services held over LTE/4G mobile networks. These profiles are defined according to targeted devices (smartphones, tablets), so as to ensure the best possible quality of experience (QoE). Obtained results indicate that for a CIF format (352 x 288 pixels) which is usually used for smartphones, the VP8 codec provides a better image quality than the H.264 codec for low bitrates (from 128 to 384 kbps). However sequences with high motion, H.264 in slow mode is preferred. Regarding audio, better results are globally achieved using wideband codecs offering good quality except for opus codec (at 12.2 kbps).

Design Effectiveness Analysis of a Media Literacy Intervention to Reduce Violent Video Games Consumption Among Adolescents: The Relevance of Lifestyles Segmentation.

Science.gov (United States)

Rivera, Reynaldo; Santos, David; Brändle, Gaspar; Cárdaba, Miguel Ángel M

2016-04-01

Exposure to media violence might have detrimental effects on psychological adjustment and is associated with aggression-related attitudes and behaviors. As a result, many media literacy programs were implemented to tackle that major public health issue. However, there is little evidence about their effectiveness. Evaluating design effectiveness, particularly regarding targeting process, would prevent adverse effects and improve the evaluation of evidence-based media literacy programs. The present research examined whether or not different relational lifestyles may explain the different effects of an antiviolence intervention program. Based on relational and lifestyles theory, the authors designed a randomized controlled trial and applied an analysis of variance 2 (treatment: experimental vs. control) × 4 (lifestyle classes emerged from data using latent class analysis: communicative vs. autonomous vs. meta-reflexive vs. fractured). Seven hundred and thirty-five Italian students distributed in 47 classes participated anonymously in the research (51.3% females). Participants completed a lifestyle questionnaire as well as their attitudes and behavioral intentions as the dependent measures. The results indicated that the program was effective in changing adolescents' attitudes toward violence. However, behavioral intentions toward consumption of violent video games were moderated by lifestyles. Those with communicative relational lifestyles showed fewer intentions to consume violent video games, while a boomerang effect was found among participants with problematic lifestyles. Adolescents' lifestyles played an important role in influencing the effectiveness of an intervention aimed at changing behavioral intentions toward the consumption of violent video games. For that reason, audience lifestyle segmentation analysis should be considered an essential technique for designing, evaluating, and improving media literacy programs. © The Author(s) 2016.

ISOMER: Informative Segment Observations for Multimedia Event Recounting

NARCIS (Netherlands)

Sun, C.; Burns, B.; Nevatia, R.; Snoek, C.; Bolles, B.; Myers, G.; Wang, W.; Yeh, E.

2014-01-01

This paper describes a system for multimedia event detection and recounting. The goal is to detect a high level event class in unconstrained web videos and generate event oriented summarization for display to users. For this purpose, we detect informative segments and collect observations for them,

Adaptations in Play

DEFF Research Database (Denmark)

Jørgensen, Ida Kathrine Hammeleff

2017-01-01

2010). Such adaptations make use of different strategies for capturing the various aspects of their source. Talisman: Digital Edition (Nomad Games 2014) largely adopts the same primary mechanics of the board game Talisman (Fantasy Flight Games 2008) while StarCraft: The Board Game (Fantasy Flight Games...... from television or cinema (Woods 2012). Furthermore, since the early days of digital games, tabletop games have served as a source of inspiration for many video-game designers, and more recently we have seen the occurrence of tabletop game adaptations of popular video-games such as StarCraft (Blizzard...... similarities and differences equally and thus challenges the ‘ideology of fidelity’ that has long permeated the field of adaption studies. This presentation explores adaptations between digital and non-digital games. This analysis is inspired by intermedial studies (e.g. Elleström 2010) that distinguishes...

Self Occlusion and Disocclusion in Causal Video Object Segmentation

Science.gov (United States)

2015-12-18

22, 37, 13, 17], since an explicit 3D reconstruction of the scene produces as a side effect a partition of the video into regions. However, it...83.4 79.3 82.8 84.4 34.7 Soldier 84.0 81.1 83.8 66.6 66.5 Monkey 85.1 86.0 84.8 79.0 61.9 Bird of Paradise 96.1 93.0 94.0 92.2 86.8 BMXPerson 92.8 88.9

Assessing hippocampal development and language in early childhood: Evidence from a new application of the Automatic Segmentation Adapter Tool.

Science.gov (United States)

Lee, Joshua K; Nordahl, Christine W; Amaral, David G; Lee, Aaron; Solomon, Marjorie; Ghetti, Simona

2015-11-01

Volumetric assessments of the hippocampus and other brain structures during childhood provide useful indices of brain development and correlates of cognitive functioning in typically and atypically developing children. Automated methods such as FreeSurfer promise efficient and replicable segmentation, but may include errors which are avoided by trained manual tracers. A recently devised automated correction tool that uses a machine learning algorithm to remove systematic errors, the Automatic Segmentation Adapter Tool (ASAT), was capable of substantially improving the accuracy of FreeSurfer segmentations in an adult sample [Wang et al., 2011], but the utility of ASAT has not been examined in pediatric samples. In Study 1, the validity of FreeSurfer and ASAT corrected hippocampal segmentations were examined in 20 typically developing children and 20 children with autism spectrum disorder aged 2 and 3 years. We showed that while neither FreeSurfer nor ASAT accuracy differed by disorder or age, the accuracy of ASAT corrected segmentations were substantially better than FreeSurfer segmentations in every case, using as few as 10 training examples. In Study 2, we applied ASAT to 89 typically developing children aged 2 to 4 years to examine relations between hippocampal volume, age, sex, and expressive language. Girls had smaller hippocampi overall, and in left hippocampus this difference was larger in older than younger girls. Expressive language ability was greater in older children, and this difference was larger in those with larger hippocampi, bilaterally. Overall, this research shows that ASAT is highly reliable and useful to examinations relating behavior to hippocampal structure. © 2015 Wiley Periodicals, Inc.

SU-C-BRA-01: Interactive Auto-Segmentation for Bowel in Online Adaptive MRI-Guided Radiation Therapy by Using a Multi-Region Labeling Algorithm

International Nuclear Information System (INIS)

Lu, Y; Chen, I; Kashani, R; Wan, H; Maughan, N; Muccigrosso, D; Parikh, P

2016-01-01

Purpose: In MRI-guided online adaptive radiation therapy, re-contouring of bowel is time-consuming and can impact the overall time of patients on table. The study aims to auto-segment bowel on volumetric MR images by using an interactive multi-region labeling algorithm. Methods: 5 Patients with locally advanced pancreatic cancer underwent fractionated radiotherapy (18–25 fractions each, total 118 fractions) on an MRI-guided radiation therapy system with a 0.35 Tesla magnet and three Co-60 sources. At each fraction, a volumetric MR image of the patient was acquired when the patient was in the treatment position. An interactive two-dimensional multi-region labeling technique based on graph cut solver was applied on several typical MRI images to segment the large bowel and small bowel, followed by a shape based contour interpolation for generating entire bowel contours along all image slices. The resulted contours were compared with the physician’s manual contouring by using metrics of Dice coefficient and Hausdorff distance. Results: Image data sets from the first 5 fractions of each patient were selected (total of 25 image data sets) for the segmentation test. The algorithm segmented the large and small bowel effectively and efficiently. All bowel segments were successfully identified, auto-contoured and matched with manual contours. The time cost by the algorithm for each image slice was within 30 seconds. For large bowel, the calculated Dice coefficients and Hausdorff distances (mean±std) were 0.77±0.07 and 13.13±5.01mm, respectively; for small bowel, the corresponding metrics were 0.73±0.08and 14.15±4.72mm, respectively. Conclusion: The preliminary results demonstrated the potential of the proposed algorithm in auto-segmenting large and small bowel on low field MRI images in MRI-guided adaptive radiation therapy. Further work will be focused on improving its segmentation accuracy and lessening human interaction.

SU-C-BRA-01: Interactive Auto-Segmentation for Bowel in Online Adaptive MRI-Guided Radiation Therapy by Using a Multi-Region Labeling Algorithm

Energy Technology Data Exchange (ETDEWEB)

Lu, Y; Chen, I; Kashani, R; Wan, H; Maughan, N; Muccigrosso, D; Parikh, P [Washington University School of Medicine, Saint Louis, MO (United States)

2016-06-15

Purpose: In MRI-guided online adaptive radiation therapy, re-contouring of bowel is time-consuming and can impact the overall time of patients on table. The study aims to auto-segment bowel on volumetric MR images by using an interactive multi-region labeling algorithm. Methods: 5 Patients with locally advanced pancreatic cancer underwent fractionated radiotherapy (18–25 fractions each, total 118 fractions) on an MRI-guided radiation therapy system with a 0.35 Tesla magnet and three Co-60 sources. At each fraction, a volumetric MR image of the patient was acquired when the patient was in the treatment position. An interactive two-dimensional multi-region labeling technique based on graph cut solver was applied on several typical MRI images to segment the large bowel and small bowel, followed by a shape based contour interpolation for generating entire bowel contours along all image slices. The resulted contours were compared with the physician’s manual contouring by using metrics of Dice coefficient and Hausdorff distance. Results: Image data sets from the first 5 fractions of each patient were selected (total of 25 image data sets) for the segmentation test. The algorithm segmented the large and small bowel effectively and efficiently. All bowel segments were successfully identified, auto-contoured and matched with manual contours. The time cost by the algorithm for each image slice was within 30 seconds. For large bowel, the calculated Dice coefficients and Hausdorff distances (mean±std) were 0.77±0.07 and 13.13±5.01mm, respectively; for small bowel, the corresponding metrics were 0.73±0.08and 14.15±4.72mm, respectively. Conclusion: The preliminary results demonstrated the potential of the proposed algorithm in auto-segmenting large and small bowel on low field MRI images in MRI-guided adaptive radiation therapy. Further work will be focused on improving its segmentation accuracy and lessening human interaction.

Testing music selection automation possibilities for video ads

Directory of Open Access Journals (Sweden)

Wiesener Oliver

2017-09-01

Full Text Available The importance of video ads on social media platforms can be measured by the number of views. For instance, Samsung’s commercial ad for one of its new smartphones reached more than 46 million viewers at Youtube. Video ads address users both visually and aurally. Often, the visual sense is engaged by users focusing on other screens, rather than on the screen with the video ad, which is referred to as the second screen syndrome. Therefore, the importance of the audio channel seems to gain more importance. To get back the visual attention of users that are deflected from other visual impulses it appears reasonable to adapt the music to the target group. Additionally, it appears useful to adapt the music to the content of the video. Thus, the overall success of a video ad could be improved by increasing the attention of the users. Humans typically decide which music is to be used in a video ad. If there is a correlation between music, products and target groups, a digitization of the music selection process appears to be possible. Since the digitization progress in the music sector is currently mainly focused on music composing this article strives for taking a first step towards the digitization of the music selection.

Moving Shadow Detection in Video Using Cepstrum

Directory of Open Access Journals (Sweden)

Fuat Cogun

2013-01-01

Full Text Available Moving shadows constitute problems in various applications such as image segmentation and object tracking. The main cause of these problems is the misclassification of the shadow pixels as target pixels. Therefore, the use of an accurate and reliable shadow detection method is essential to realize intelligent video processing applications. In this paper, a cepstrum-based method for moving shadow detection is presented. The proposed method is tested on outdoor and indoor video sequences using well-known benchmark test sets. To show the improvements over previous approaches, quantitative metrics are introduced and comparisons based on these metrics are made.

Discovery and fusion of salient multimodal features toward news story segmentation

Science.gov (United States)

Hsu, Winston; Chang, Shih-Fu; Huang, Chih-Wei; Kennedy, Lyndon; Lin, Ching-Yung; Iyengar, Giridharan

2003-12-01

In this paper, we present our new results in news video story segmentation and classification in the context of TRECVID video retrieval benchmarking event 2003. We applied and extended the Maximum Entropy statistical model to effectively fuse diverse features from multiple levels and modalities, including visual, audio, and text. We have included various features such as motion, face, music/speech types, prosody, and high-level text segmentation information. The statistical fusion model is used to automatically discover relevant features contributing to the detection of story boundaries. One novel aspect of our method is the use of a feature wrapper to address different types of features -- asynchronous, discrete, continuous and delta ones. We also developed several novel features related to prosody. Using the large news video set from the TRECVID 2003 benchmark, we demonstrate satisfactory performance (F1 measures up to 0.76 in ABC news and 0.73 in CNN news), present how these multi-level multi-modal features construct the probabilistic framework, and more importantly observe an interesting opportunity for further improvement.

Communication with market segments - travel agencies' perspective

OpenAIRE

Lorena Bašan; Jasmina Dlačić; Željko Trezner

2013-01-01

Purpose – The purpose of this paper is to research the travel agencies’ communication with market segments. Communication with market segments takes into account marketing communication means as well as the implementation of different business orientations. Design – Special emphasis is placed on the use of different marketing communication means and their efficiency. Research also explores business orientation adaptation when approaching different market segments. Methodology – In explo...

Segmentation by Large Scale Hypothesis Testing - Segmentation as Outlier Detection

DEFF Research Database (Denmark)

Darkner, Sune; Dahl, Anders Lindbjerg; Larsen, Rasmus

2010-01-01

a microscope and we show how the method can handle transparent particles with significant glare point. The method generalizes to other problems. THis is illustrated by applying the method to camera calibration images and MRI of the midsagittal plane for gray and white matter separation and segmentation......We propose a novel and efficient way of performing local image segmentation. For many applications a threshold of pixel intensities is sufficient but determine the appropriate threshold value can be difficult. In cases with large global intensity variation the threshold value has to be adapted...... locally. We propose a method based on large scale hypothesis testing with a consistent method for selecting an appropriate threshold for the given data. By estimating the background distribution we characterize the segment of interest as a set of outliers with a certain probability based on the estimated...

Scalable and Media Aware Adaptive Video Streaming over Wireless Networks

Directory of Open Access Journals (Sweden)

Béatrice Pesquet-Popescu

2008-07-01

Full Text Available This paper proposes an advanced video streaming system based on scalable video coding in order to optimize resource utilization in wireless networks with retransmission mechanisms at radio protocol level. The key component of this system is a packet scheduling algorithm which operates on the different substreams of a main scalable video stream and which is implemented in a so-called media aware network element. The concerned type of transport channel is a dedicated channel subject to parameters (bitrate, loss rate variations on the long run. Moreover, we propose a combined scalability approach in which common temporal and SNR scalability features can be used jointly with a partitioning of the image into regions of interest. Simulation results show that our approach provides substantial quality gain compared to classical packet transmission methods and they demonstrate how ROI coding combined with SNR scalability allows to improve again the visual quality.

Geographic Video 3d Data Model And Retrieval

Science.gov (United States)

Han, Z.; Cui, C.; Kong, Y.; Wu, H.

2014-04-01

Geographic video includes both spatial and temporal geographic features acquired through ground-based or non-ground-based cameras. With the popularity of video capture devices such as smartphones, the volume of user-generated geographic video clips has grown significantly and the trend of this growth is quickly accelerating. Such a massive and increasing volume poses a major challenge to efficient video management and query. Most of the today's video management and query techniques are based on signal level content extraction. They are not able to fully utilize the geographic information of the videos. This paper aimed to introduce a geographic video 3D data model based on spatial information. The main idea of the model is to utilize the location, trajectory and azimuth information acquired by sensors such as GPS receivers and 3D electronic compasses in conjunction with video contents. The raw spatial information is synthesized to point, line, polygon and solid according to the camcorder parameters such as focal length and angle of view. With the video segment and video frame, we defined the three categories geometry object using the geometry model of OGC Simple Features Specification for SQL. We can query video through computing the spatial relation between query objects and three categories geometry object such as VFLocation, VSTrajectory, VSFOView and VFFovCone etc. We designed the query methods using the structured query language (SQL) in detail. The experiment indicate that the model is a multiple objective, integration, loosely coupled, flexible and extensible data model for the management of geographic stereo video.

Performance evaluation software moving object detection and tracking in videos

CERN Document Server

Karasulu, Bahadir

2013-01-01

Performance Evaluation Software: Moving Object Detection and Tracking in Videos introduces a software approach for the real-time evaluation and performance comparison of the methods specializing in moving object detection and/or tracking (D&T) in video processing. Digital video content analysis is an important item for multimedia content-based indexing (MCBI), content-based video retrieval (CBVR) and visual surveillance systems. There are some frequently-used generic algorithms for video object D&T in the literature, such as Background Subtraction (BS), Continuously Adaptive Mean-shift (CMS),

Content-based retrieval in videos from laparoscopic surgery

Science.gov (United States)

Schoeffmann, Klaus; Beecks, Christian; Lux, Mathias; Uysal, Merih Seran; Seidl, Thomas

2016-03-01

In the field of medical endoscopy more and more surgeons are changing over to record and store videos of their endoscopic procedures for long-term archival. These endoscopic videos are a good source of information for explanations to patients and follow-up operations. As the endoscope is the "eye of the surgeon", the video shows the same information the surgeon has seen during the operation, and can describe the situation inside the patient much more precisely than an operation report would do. Recorded endoscopic videos can also be used for training young surgeons and in some countries the long-term archival of video recordings from endoscopic procedures is even enforced by law. A major challenge, however, is to efficiently access these very large video archives for later purposes. One problem, for example, is to locate specific images in the videos that show important situations, which are additionally captured as static images during the procedure. This work addresses this problem and focuses on contentbased video retrieval in data from laparoscopic surgery. We propose to use feature signatures, which can appropriately and concisely describe the content of laparoscopic images, and show that by using this content descriptor with an appropriate metric, we are able to efficiently perform content-based retrieval in laparoscopic videos. In a dataset with 600 captured static images from 33 hours recordings, we are able to find the correct video segment for more than 88% of these images.

Combination of Accumulated Motion and Color Segmentation for Human Activity Analysis

Directory of Open Access Journals (Sweden)

Briassouli Alexia

2008-01-01

Full Text Available Abstract The automated analysis of activity in digital multimedia, and especially video, is gaining more and more importance due to the evolution of higher-level video processing systems and the development of relevant applications such as surveillance and sports. This paper presents a novel algorithm for the recognition and classification of human activities, which employs motion and color characteristics in a complementary manner, so as to extract the most information from both sources, and overcome their individual limitations. The proposed method accumulates the flow estimates in a video, and extracts "regions of activity" by processing their higher-order statistics. The shape of these activity areas can be used for the classification of the human activities and events taking place in a video and the subsequent extraction of higher-level semantics. Color segmentation of the active and static areas of each video frame is performed to complement this information. The color layers in the activity and background areas are compared using the earth mover's distance, in order to achieve accurate object segmentation. Thus, unlike much existing work on human activity analysis, the proposed approach is based on general color and motion processing methods, and not on specific models of the human body and its kinematics. The combined use of color and motion information increases the method robustness to illumination variations and measurement noise. Consequently, the proposed approach can lead to higher-level information about human activities, but its applicability is not limited to specific human actions. We present experiments with various real video sequences, from sports and surveillance domains, to demonstrate the effectiveness of our approach.

Combination of Accumulated Motion and Color Segmentation for Human Activity Analysis

Directory of Open Access Journals (Sweden)

Ioannis Kompatsiaris

2008-03-01

Full Text Available The automated analysis of activity in digital multimedia, and especially video, is gaining more and more importance due to the evolution of higher-level video processing systems and the development of relevant applications such as surveillance and sports. This paper presents a novel algorithm for the recognition and classification of human activities, which employs motion and color characteristics in a complementary manner, so as to extract the most information from both sources, and overcome their individual limitations. The proposed method accumulates the flow estimates in a video, and extracts “regions of activity” by processing their higher-order statistics. The shape of these activity areas can be used for the classification of the human activities and events taking place in a video and the subsequent extraction of higher-level semantics. Color segmentation of the active and static areas of each video frame is performed to complement this information. The color layers in the activity and background areas are compared using the earth mover's distance, in order to achieve accurate object segmentation. Thus, unlike much existing work on human activity analysis, the proposed approach is based on general color and motion processing methods, and not on specific models of the human body and its kinematics. The combined use of color and motion information increases the method robustness to illumination variations and measurement noise. Consequently, the proposed approach can lead to higher-level information about human activities, but its applicability is not limited to specific human actions. We present experiments with various real video sequences, from sports and surveillance domains, to demonstrate the effectiveness of our approach.

Unsupervised Object Modeling and Segmentation with Symmetry Detection for Human Activity Recognition

Directory of Open Access Journals (Sweden)

Jui-Yuan Su

2015-04-01

Full Text Available In this paper we present a novel unsupervised approach to detecting and segmenting objects as well as their constituent symmetric parts in an image. Traditional unsupervised image segmentation is limited by two obvious deficiencies: the object detection accuracy degrades with the misaligned boundaries between the segmented regions and the target, and pre-learned models are required to group regions into meaningful objects. To tackle these difficulties, the proposed approach aims at incorporating the pair-wise detection of symmetric patches to achieve the goal of segmenting images into symmetric parts. The skeletons of these symmetric parts then provide estimates of the bounding boxes to locate the target objects. Finally, for each detected object, the graphcut-based segmentation algorithm is applied to find its contour. The proposed approach has significant advantages: no a priori object models are used, and multiple objects are detected. To verify the effectiveness of the approach based on the cues that a face part contains an oval shape and skin colors, human objects are extracted from among the detected objects. The detected human objects and their parts are finally tracked across video frames to capture the object part movements for learning the human activity models from video clips. Experimental results show that the proposed method gives good performance on publicly available datasets.

Fine-Grained Rate Shaping for Video Streaming over Wireless Networks

Directory of Open Access Journals (Sweden)

Chen Tsuhan

2004-01-01

Full Text Available Video streaming over wireless networks faces challenges of time-varying packet loss rate and fluctuating bandwidth. In this paper, we focus on streaming precoded video that is both source and channel coded. Dynamic rate shaping has been proposed to “shape” the precompressed video to adapt to the fluctuating bandwidth. In our earlier work, rate shaping was extended to shape the channel coded precompressed video, and to take into account the time-varying packet loss rate as well as the fluctuating bandwidth of the wireless networks. However, prior work on rate shaping can only adjust the rate oarsely. In this paper, we propose “fine-grained rate shaping (FGRS” to allow for bandwidth adaptation over a wide range of bandwidth and packet loss rate in fine granularities. The video is precoded with fine granularity scalability (FGS followed by channel coding. Utilizing the fine granularity property of FGS and channel coding, FGRS selectively drops part of the precoded video and still yields decodable bit-stream at the decoder. Moreover, FGRS optimizes video streaming rather than achieves heuristic objectives as conventional methods. A two-stage rate-distortion (RD optimization algorithm is proposed for FGRS. Promising results of FGRS are shown.

Design and implementation of a non-linear symphonic soundtrack of a video game

Science.gov (United States)

Sporka, Adam J.; Valta, Jan

2017-10-01

The music in the contemporary video games is often interactive. The music playback is based on transitions between pieces of available music material. These transitions happen in response to evolving gameplay. This paradigm is referred to as the adaptive music. Our challenge was to design, create, and implement the soundtrack of the upcoming video game Kingdom Come: Deliverance. Our soundtrack is a collection of compositions with symphonic orchestration. Per our design decision, our intention was to implement the adaptive music in a way which respected the nature of the orchestral film score. We created our own adaptive music middleware, called Sequence Music Engine, implementing a high-level music logic as well as the low-level playback infrastructure. Our system can handle hours of video game music, helps maintain the relevance of the music throughout the video game, and minimises the repetitiveness of the individual pieces.

An EM based approach for motion segmentation of video sequence

NARCIS (Netherlands)

Zhao, Wei; Roos, Nico; Pan, Zhigeng; Skala, Vaclav

2016-01-01

Motions are important features for robot vision as we live in a dynamic world. Detecting moving objects is crucial for mobile robots and computer vision systems. This paper investigates an architecture for the segmentation of moving objects from image sequences. Objects are represented as groups of

Video interactivo en realidad virtual inmersiva

OpenAIRE

Gordo Ara, Juan

2016-01-01

Currently, developers are creating new virtual reality applications related to the field of video games or graphics environments created by computers. This is due largely to the arrival to the consumer market of new technologies to experience these virtual reality environments. This has provoked a wide adoption of 360º videos, which can be viewed directly from smartphones. In addition, cheap adapters allow converting the phone into a virtual reality display. In this project we investigated me...

Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

Science.gov (United States)

Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

2014-05-01

In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

Hierarchical vs non-hierarchical audio indexation and classification for video genres

Science.gov (United States)

Dammak, Nouha; BenAyed, Yassine

2018-04-01

In this paper, Support Vector Machines (SVMs) are used for segmenting and indexing video genres based on only audio features extracted at block level, which has a prominent asset by capturing local temporal information. The main contribution of our study is to show the wide effect on the classification accuracies while using an hierarchical categorization structure based on Mel Frequency Cepstral Coefficients (MFCC) audio descriptor. In fact, the classification consists in three common video genres: sports videos, music clips and news scenes. The sub-classification may divide each genre into several multi-speaker and multi-dialect sub-genres. The validation of this approach was carried out on over 360 minutes of video span yielding a classification accuracy of over 99%.

Video sensor architecture for surveillance applications.

Science.gov (United States)

Sánchez, Jordi; Benet, Ginés; Simó, José E

2012-01-01

This paper introduces a flexible hardware and software architecture for a smart video sensor. This sensor has been applied in a video surveillance application where some of these video sensors are deployed, constituting the sensory nodes of a distributed surveillance system. In this system, a video sensor node processes images locally in order to extract objects of interest, and classify them. The sensor node reports the processing results to other nodes in the cloud (a user or higher level software) in the form of an XML description. The hardware architecture of each sensor node has been developed using two DSP processors and an FPGA that controls, in a flexible way, the interconnection among processors and the image data flow. The developed node software is based on pluggable components and runs on a provided execution run-time. Some basic and application-specific software components have been developed, in particular: acquisition, segmentation, labeling, tracking, classification and feature extraction. Preliminary results demonstrate that the system can achieve up to 7.5 frames per second in the worst case, and the true positive rates in the classification of objects are better than 80%.

Video Sensor Architecture for Surveillance Applications

Directory of Open Access Journals (Sweden)

José E. Simó

2012-02-01

Full Text Available This paper introduces a flexible hardware and software architecture for a smart video sensor. This sensor has been applied in a video surveillance application where some of these video sensors are deployed, constituting the sensory nodes of a distributed surveillance system. In this system, a video sensor node processes images locally in order to extract objects of interest, and classify them. The sensor node reports the processing results to other nodes in the cloud (a user or higher level software in the form of an XML description. The hardware architecture of each sensor node has been developed using two DSP processors and an FPGA that controls, in a flexible way, the interconnection among processors and the image data flow. The developed node software is based on pluggable components and runs on a provided execution run-time. Some basic and application-specific software components have been developed, in particular: acquisition, segmentation, labeling, tracking, classification and feature extraction. Preliminary results demonstrate that the system can achieve up to 7.5 frames per second in the worst case, and the true positive rates in the classification of objects are better than 80%.

Unfolding Implementation in Industrial Market Segmentation

DEFF Research Database (Denmark)

Bøjgaard, John; Ellegaard, Chris

2011-01-01

to pave the way towards closing this gap. The extent of implementation coverage is assessed and various notions of implementation are identified. Implementation as the task of converting segmentation plans into action (referred to as execution) is identified as a particularly beneficial focus area...... for marketing management. Three key elements and challenges connected to execution of market segmentation are identified — organization, motivation, and adaptation....

Motion Segments Decomposition of RGB-D Sequences for Human Behavior Understanding

OpenAIRE

Devanne , Maxime; Berretti , Stefano; Pala , Pietro; Wannous , Hazem; Daoudi , Mohamed; Bimbo , Alberto ,

2017-01-01

International audience; In this paper, we propose a framework for analyzing and understanding human behavior from depth videos. The proposed solution first employs shape analysis of the human pose across time to decompose the full motion into short temporal segments representing elementary motions. Then, each segment is characterized by human motion and depth appearance around hand joints to describe the change in pose of the body and the interaction with objects. Finally , the sequence of te...

Kalman Filter Based Tracking in an Video Surveillance System

Directory of Open Access Journals (Sweden)

SULIMAN, C.

2010-05-01

Full Text Available In this paper we have developed a Matlab/Simulink based model for monitoring a contact in a video surveillance sequence. For the segmentation process and corect identification of a contact in a surveillance video, we have used the Horn-Schunk optical flow algorithm. The position and the behavior of the correctly detected contact were monitored with the help of the traditional Kalman filter. After that we have compared the results obtained from the optical flow method with the ones obtained from the Kalman filter, and we show the correct functionality of the Kalman filter based tracking. The tests were performed using video data taken with the help of a fix camera. The tested algorithm has shown promising results.

Surgical gesture classification from video and kinematic data.

Science.gov (United States)

Zappella, Luca; Béjar, Benjamín; Hager, Gregory; Vidal, René

2013-10-01

Much of the existing work on automatic classification of gestures and skill in robotic surgery is based on dynamic cues (e.g., time to completion, speed, forces, torque) or kinematic data (e.g., robot trajectories and velocities). While videos could be equally or more discriminative (e.g., videos contain semantic information not present in kinematic data), they are typically not used because of the difficulties associated with automatic video interpretation. In this paper, we propose several methods for automatic surgical gesture classification from video data. We assume that the video of a surgical task (e.g., suturing) has been segmented into video clips corresponding to a single gesture (e.g., grabbing the needle, passing the needle) and propose three methods to classify the gesture of each video clip. In the first one, we model each video clip as the output of a linear dynamical system (LDS) and use metrics in the space of LDSs to classify new video clips. In the second one, we use spatio-temporal features extracted from each video clip to learn a dictionary of spatio-temporal words, and use a bag-of-features (BoF) approach to classify new video clips. In the third one, we use multiple kernel learning (MKL) to combine the LDS and BoF approaches. Since the LDS approach is also applicable to kinematic data, we also use MKL to combine both types of data in order to exploit their complementarity. Our experiments on a typical surgical training setup show that methods based on video data perform equally well, if not better, than state-of-the-art approaches based on kinematic data. In turn, the combination of both kinematic and video data outperforms any other algorithm based on one type of data alone. Copyright © 2013 Elsevier B.V. All rights reserved.

VLSI-based video event triggering for image data compression

Science.gov (United States)

Williams, Glenn L.

1994-02-01

Long-duration, on-orbit microgravity experiments require a combination of high resolution and high frame rate video data acquisition. The digitized high-rate video stream presents a difficult data storage problem. Data produced at rates of several hundred million bytes per second may require a total mission video data storage requirement exceeding one terabyte. A NASA-designed, VLSI-based, highly parallel digital state machine generates a digital trigger signal at the onset of a video event. High capacity random access memory storage coupled with newly available fuzzy logic devices permits the monitoring of a video image stream for long term (DC-like) or short term (AC-like) changes caused by spatial translation, dilation, appearance, disappearance, or color change in a video object. Pre-trigger and post-trigger storage techniques are then adaptable to archiving only the significant video images.

Using multimodal information for the segmentation of fluorescent micrographs with application to virology and microbiology.

Science.gov (United States)

Held, Christian; Wenzel, Jens; Webel, Rike; Marschall, Manfred; Lang, Roland; Palmisano, Ralf; Wittenberg, Thomas

2011-01-01

In order to improve reproducibility and objectivity of fluorescence microscopy based experiments and to enable the evaluation of large datasets, flexible segmentation methods are required which are able to adapt to different stainings and cell types. This adaption is usually achieved by the manual adjustment of the segmentation methods parameters, which is time consuming and challenging for biologists with no knowledge on image processing. To avoid this, parameters of the presented methods automatically adapt to user generated ground truth to determine the best method and the optimal parameter setup. These settings can then be used for segmentation of the remaining images. As robust segmentation methods form the core of such a system, the currently used watershed transform based segmentation routine is replaced by a fast marching level set based segmentation routine which incorporates knowledge on the cell nuclei. Our evaluations reveal that incorporation of multimodal information improves segmentation quality for the presented fluorescent datasets.

Distributed Video Coding: Iterative Improvements

DEFF Research Database (Denmark)

Luong, Huynh Van

Nowadays, emerging applications such as wireless visual sensor networks and wireless video surveillance are requiring lightweight video encoding with high coding efficiency and error-resilience. Distributed Video Coding (DVC) is a new coding paradigm which exploits the source statistics...... and noise modeling and also learn from the previous decoded Wyner-Ziv (WZ) frames, side information and noise learning (SING) is proposed. The SING scheme introduces an optical flow technique to compensate the weaknesses of the block based SI generation and also utilizes clustering of DCT blocks to capture...... cross band correlation and increase local adaptivity in noise modeling. During decoding, the updated information is used to iteratively reestimate the motion and reconstruction in the proposed motion and reconstruction reestimation (MORE) scheme. The MORE scheme not only reestimates the motion vectors...

ESVD: An Integrated Energy Scalable Framework for Low-Power Video Decoding Systems

Directory of Open Access Journals (Sweden)

Wen Ji

2010-01-01

Full Text Available Video applications using mobile wireless devices are a challenging task due to the limited capacity of batteries. The higher complex functionality of video decoding needs high resource requirements. Thus, power efficient control has become more critical design with devices integrating complex video processing techniques. Previous works on power efficient control in video decoding systems often aim at the low complexity design and not explicitly consider the scalable impact of subfunctions in decoding process, and seldom consider the relationship with the features of compressed video date. This paper is dedicated to developing an energy-scalable video decoding (ESVD strategy for energy-limited mobile terminals. First, ESVE can dynamically adapt the variable energy resources due to the device aware technique. Second, ESVD combines the decoder control with decoded data, through classifying the data into different partition profiles according to its characteristics. Third, it introduces utility theoretical analysis during the resource allocation process, so as to maximize the resource utilization. Finally, it adapts the energy resource as different energy budget and generates the scalable video decoding output under energy-limited systems. Experimental results demonstrate the efficiency of the proposed approach.

Perioperative outcomes of video- and robot-assisted segmentectomies.

Science.gov (United States)

Rinieri, Philippe; Peillon, Christophe; Salaün, Mathieu; Mahieu, Julien; Bubenheim, Michael; Baste, Jean-Marc

2016-02-01

Video-assisted thoracic surgery appears to be technically difficult for segmentectomy. Conversely, robotic surgery could facilitate the performance of segmentectomy. The aim of this study was to compare the early results of video- and robot-assisted segmentectomies. Data were collected prospectively on videothoracoscopy from 2010 and on robotic procedures from 2013. Fifty-one patients who were candidates for minimally invasive segmentectomy were included in the study. Perioperative outcomes of video-assisted and robotic segmentectomies were compared. The minimally invasive segmentectomies included 32 video- and 16 robot-assisted procedures; 3 segmentectomies (2 video-assisted and 1 robot-assisted) were converted to lobectomies. Four conversions to thoracotomy were necessary for anatomical reason or arterial injury, with no uncontrolled bleeding in the robotic arm. There were 7 benign or infectious lesions, 9 pre-invasive lesions, 25 lung cancers, and 10 metastatic diseases. Patient characteristics, type of segment, conversion to thoracotomy, conversion to lobectomy, operative time, postoperative complications, chest tube duration, postoperative stay, and histology were similar in the video and robot groups. Estimated blood loss was significantly higher in the video group (100 vs. 50 mL, p = 0.028). The morbidity rate of minimally invasive segmentectomy was low. The short-term results of video-assisted and robot-assisted segmentectomies were similar, and more data are required to show any advantages between the two techniques. Long-term oncologic outcomes are necessary to evaluate these new surgical practices. © The Author(s) 2016.

The Effects of Video Self-Modeling on the Decoding Skills of Children At Risk for Reading Disabilities

OpenAIRE

Ayala, Sandra M

2010-01-01

Ten first grade students, participating in a Tier II response to intervention (RTI) reading program received an intervention of video self modeling to improve decoding skills and sight word recognition. The students were video recorded blending and segmenting decodable words, and reading sight words taken directly from their curriculum instruction. Individual videos were recorded and edited to show students successfully and accurately decoding words and practicing sight word recognition. Each...

A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images.

Science.gov (United States)

Janowczyk, Andrew; Doyle, Scott; Gilmore, Hannah; Madabhushi, Anant

2018-01-01

Deep learning (DL) has recently been successfully applied to a number of image analysis problems. However, DL approaches tend to be inefficient for segmentation on large image data, such as high-resolution digital pathology slide images. For example, typical breast biopsy images scanned at 40× magnification contain billions of pixels, of which usually only a small percentage belong to the class of interest. For a typical naïve deep learning scheme, parsing through and interrogating all the image pixels would represent hundreds if not thousands of hours of compute time using high performance computing environments. In this paper, we present a resolution adaptive deep hierarchical (RADHicaL) learning scheme wherein DL networks at lower resolutions are leveraged to determine if higher levels of magnification, and thus computation, are necessary to provide precise results. We evaluate our approach on a nuclear segmentation task with a cohort of 141 ER+ breast cancer images and show we can reduce computation time on average by about 85%. Expert annotations of 12,000 nuclei across these 141 images were employed for quantitative evaluation of RADHicaL. A head-to-head comparison with a naïve DL approach, operating solely at the highest magnification, yielded the following performance metrics: .9407 vs .9854 Detection Rate, .8218 vs .8489 F -score, .8061 vs .8364 true positive rate and .8822 vs 0.8932 positive predictive value. Our performance indices compare favourably with state of the art nuclear segmentation approaches for digital pathology images.

The impact of video technology on learning: A cooking skills experiment.

Science.gov (United States)

Surgenor, Dawn; Hollywood, Lynsey; Furey, Sinéad; Lavelle, Fiona; McGowan, Laura; Spence, Michelle; Raats, Monique; McCloat, Amanda; Mooney, Elaine; Caraher, Martin; Dean, Moira

2017-07-01

This study examines the role of video technology in the development of cooking skills. The study explored the views of 141 female participants on whether video technology can promote confidence in learning new cooking skills to assist in meal preparation. Prior to each focus group participants took part in a cooking experiment to assess the most effective method of learning for low-skilled cooks across four experimental conditions (recipe card only; recipe card plus video demonstration; recipe card plus video demonstration conducted in segmented stages; and recipe card plus video demonstration whereby participants freely accessed video demonstrations as and when needed). Focus group findings revealed that video technology was perceived to assist learning in the cooking process in the following ways: (1) improved comprehension of the cooking process; (2) real-time reassurance in the cooking process; (3) assisting the acquisition of new cooking skills; and (4) enhancing the enjoyment of the cooking process. These findings display the potential for video technology to promote motivation and confidence as well as enhancing cooking skills among low-skilled individuals wishing to cook from scratch using fresh ingredients. Copyright © 2017 Elsevier Ltd. All rights reserved.

Two-Level Evaluation on Sensor Interoperability of Features in Fingerprint Image Segmentation

Directory of Open Access Journals (Sweden)

Ya-Shuo Li

2012-03-01

Full Text Available Features used in fingerprint segmentation significantly affect the segmentation performance. Various features exhibit different discriminating abilities on fingerprint images derived from different sensors. One feature which has better discriminating ability on images derived from a certain sensor may not adapt to segment images derived from other sensors. This degrades the segmentation performance. This paper empirically analyzes the sensor interoperability problem of segmentation feature, which refers to the feature’s ability to adapt to the raw fingerprints captured by different sensors. To address this issue, this paper presents a two-level feature evaluation method, including the first level feature evaluation based on segmentation error rate and the second level feature evaluation based on decision tree. The proposed method is performed on a number of fingerprint databases which are obtained from various sensors. Experimental results show that the proposed method can effectively evaluate the sensor interoperability of features, and the features with good evaluation results acquire better segmentation accuracies of images originating from different sensors.

Practical and Scalable Transmission of Segmented Video Sequences to Multiple Players Using H.264

Science.gov (United States)

Quax, Peter; di Fiore, Fabian; Issaris, Panagiotis; Lamotte, Wim; van Reeth, Frank

We present a practical way to distribute viewports on the same video sequence to large amounts of players. Each of them has personal preferences to be met or is limited by the physical properties of his/her device (e.g., screen size of a PDA or processing power of a mobile phone). Instead of taking the naïve approach, in which sections of the video sequence are decoded and re-encoded for each of the clients, we have exploited advanced features offered by the H.264 codec to enable selection of parts of the video sequence by directly manipulating the encoder-generated bitstream. At the same time, we have overcome several practical issues presented by the fact that support for these features is sadly lacking from the state-of-the-art encoders available on the market. Two alternative solutions are discussed and have been implemented, enabling the generation of measurement results and comparison to alternative approaches.

A Secure and Robust Object-Based Video Authentication System

Directory of Open Access Journals (Sweden)

He Dajun

2004-01-01

Full Text Available An object-based video authentication system, which combines watermarking, error correction coding (ECC, and digital signature techniques, is presented for protecting the authenticity between video objects and their associated backgrounds. In this system, a set of angular radial transformation (ART coefficients is selected as the feature to represent the video object and the background, respectively. ECC and cryptographic hashing are applied to those selected coefficients to generate the robust authentication watermark. This content-based, semifragile watermark is then embedded into the objects frame by frame before MPEG4 coding. In watermark embedding and extraction, groups of discrete Fourier transform (DFT coefficients are randomly selected, and their energy relationships are employed to hide and extract the watermark. The experimental results demonstrate that our system is robust to MPEG4 compression, object segmentation errors, and some common object-based video processing such as object translation, rotation, and scaling while securely preventing malicious object modifications. The proposed solution can be further incorporated into public key infrastructure (PKI.

SU-C-BRA-03: An Automated and Quick Contour Errordetection for Auto Segmentation in Online Adaptive Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Zhang, J; Ates, O; Li, X [Medical College of Wisconsin, Milwaukee, WI (United States)

2016-06-15

Purpose: To develop a tool that can quickly and automatically assess contour quality generated from auto segmentation during online adaptive replanning. Methods: Due to the strict time requirement of online replanning and lack of ‘ground truth’ contours in daily images, our method starts with assessing image registration accuracy focusing on the surface of the organ in question. Several metrics tightly related to registration accuracy including Jacobian maps, contours shell deformation, and voxel-based root mean square (RMS) analysis were computed. To identify correct contours, additional metrics and an adaptive decision tree are introduced. To approve in principle, tests were performed with CT sets, planned and daily CTs acquired using a CT-on-rails during routine CT-guided RT delivery for 20 prostate cancer patients. The contours generated on daily CTs using an auto-segmentation tool (ADMIRE, Elekta, MIM) based on deformable image registration of the planning CT and daily CT were tested. Results: The deformed contours of 20 patients with total of 60 structures were manually checked as baselines. The incorrect rate of total contours is 49%. To evaluate the quality of local deformation, the Jacobian determinant (1.047±0.045) on contours has been analyzed. In an analysis of rectum contour shell deformed, the higher rate (0.41) of error contours detection was obtained compared to 0.32 with manual check. All automated detections took less than 5 seconds. Conclusion: The proposed method can effectively detect contour errors in micro and macro scope by evaluating multiple deformable registration metrics in a parallel computing process. Future work will focus on improving practicability and optimizing calculation algorithms and metric selection.

SU-C-BRA-03: An Automated and Quick Contour Errordetection for Auto Segmentation in Online Adaptive Radiotherapy

International Nuclear Information System (INIS)

Zhang, J; Ates, O; Li, X

2016-01-01

Purpose: To develop a tool that can quickly and automatically assess contour quality generated from auto segmentation during online adaptive replanning. Methods: Due to the strict time requirement of online replanning and lack of ‘ground truth’ contours in daily images, our method starts with assessing image registration accuracy focusing on the surface of the organ in question. Several metrics tightly related to registration accuracy including Jacobian maps, contours shell deformation, and voxel-based root mean square (RMS) analysis were computed. To identify correct contours, additional metrics and an adaptive decision tree are introduced. To approve in principle, tests were performed with CT sets, planned and daily CTs acquired using a CT-on-rails during routine CT-guided RT delivery for 20 prostate cancer patients. The contours generated on daily CTs using an auto-segmentation tool (ADMIRE, Elekta, MIM) based on deformable image registration of the planning CT and daily CT were tested. Results: The deformed contours of 20 patients with total of 60 structures were manually checked as baselines. The incorrect rate of total contours is 49%. To evaluate the quality of local deformation, the Jacobian determinant (1.047±0.045) on contours has been analyzed. In an analysis of rectum contour shell deformed, the higher rate (0.41) of error contours detection was obtained compared to 0.32 with manual check. All automated detections took less than 5 seconds. Conclusion: The proposed method can effectively detect contour errors in micro and macro scope by evaluating multiple deformable registration metrics in a parallel computing process. Future work will focus on improving practicability and optimizing calculation algorithms and metric selection.

COMPARISON OF DIFFERENT SEGMENTATION ALGORITHMS FOR DERMOSCOPIC IMAGES

Directory of Open Access Journals (Sweden)

A.A. Haseena Thasneem

2015-05-01

Full Text Available This paper compares different algorithms for the segmentation of skin lesions in dermoscopic images. The basic segmentation algorithms compared are Thresholding techniques (Global and Adaptive, Region based techniques (K-means, Fuzzy C means, Expectation Maximization and Statistical Region Merging, Contour models (Active Contour Model and Chan - Vese Model and Spectral Clustering. Accuracy, sensitivity, specificity, Border error, Hammoude distance, Hausdorff distance, MSE, PSNR and elapsed time metrices were used to evaluate various segmentation techniques.

A Super-resolution Reconstruction Algorithm for Surveillance Video

Directory of Open Access Journals (Sweden)

Jian Shao

2017-01-01

Full Text Available Recent technological developments have resulted in surveillance video becoming a primary method of preserving public security. Many city crimes are observed in surveillance video. The most abundant evidence collected by the police is also acquired through surveillance video sources. Surveillance video footage offers very strong support for solving criminal cases, therefore, creating an effective policy, and applying useful methods to the retrieval of additional evidence is becoming increasingly important. However, surveillance video has had its failings, namely, video footage being captured in low resolution (LR and bad visual quality. In this paper, we discuss the characteristics of surveillance video and describe the manual feature registration – maximum a posteriori – projection onto convex sets to develop a super-resolution reconstruction method, which improves the quality of surveillance video. From this method, we can make optimal use of information contained in the LR video image, but we can also control the image edge clearly as well as the convergence of the algorithm. Finally, we make a suggestion on how to adjust the algorithm adaptability by analyzing the prior information of target image.

Multi-focus Image Fusion Using Epifluorescence Microscopy for Robust Vascular Segmentation

OpenAIRE

Pelapur, Rengarajan; Prasath, Surya; Palaniappan, Kannappan

2014-01-01

We are building a computerized image analysis system for Dura Mater vascular network from fluorescence microscopy images. We propose a system that couples a multi-focus image fusion module with a robust adaptive filtering based segmentation. The robust adaptive filtering scheme handles noise without destroying small structures, and the multi focal image fusion considerably improves the overall segmentation quality by integrating information from multiple images. Based on the segmenta...

Effects of micro transactions on video games industry

Directory of Open Access Journals (Sweden)

Tomić Nenad

2017-01-01

Full Text Available During the twentieth century, the entertainment industry recorded a steady revenue growth. The progress of information and communication technology (ICT influenced the creation of a new segment in the industry at the beginning of the 80s, known as the video game industry. During the first two decades, the dominant model of earning for video games publishers was sale of a full game, which means that users were obliged to pay in order to play the game (pay-to-play concept. In the past ten years, publishers have developed a new approach, which instead of selling entire game content at once tends to decompose the sale into several smaller transactions. The prices of these supplements are often calculated in the virtual currency that is considered to be the currency of video game, and not in one of convertible currencies, which creates additional confusion. The subject of the paper is to explain the essence of microtransactions as type of electronic payments created in the video games industry and to observe their role in the process of industry transformation.

Remote control video cameras on a suborbital rocket

International Nuclear Information System (INIS)

Wessling, Francis C.

1997-01-01

Three video cameras were controlled in real time from the ground to a sub-orbital rocket during a fifteen minute flight from White Sands Missile Range in New Mexico. Telemetry communications with the rocket allowed the control of the cameras. The pan, tilt, zoom, focus, and iris of two of the camera lenses, the power and record functions of the three cameras, and also the analog video signal that would be sent to the ground was controlled by separate microprocessors. A microprocessor was used to record data from three miniature accelerometers, temperature sensors and a differential pressure sensor. In addition to the selected video signal sent to the ground and recorded there, the video signals from the three cameras also were recorded on board the rocket. These recorders were mounted inside the pressurized segment of the rocket payload. The lenses, lens control mechanisms, and the three small television cameras were located in a portion of the rocket payload that was exposed to the vacuum of space. The accelerometers were also exposed to the vacuum of space

Deriving video content type from HEVC bitstream semantics

Science.gov (United States)

Nightingale, James; Wang, Qi; Grecos, Christos; Goma, Sergio R.

2014-05-01

As network service providers seek to improve customer satisfaction and retention levels, they are increasingly moving from traditional quality of service (QoS) driven delivery models to customer-centred quality of experience (QoE) delivery models. QoS models only consider metrics derived from the network however, QoE models also consider metrics derived from within the video sequence itself. Various spatial and temporal characteristics of a video sequence have been proposed, both individually and in combination, to derive methods of classifying video content either on a continuous scale or as a set of discrete classes. QoE models can be divided into three broad categories, full reference, reduced reference and no-reference models. Due to the need to have the original video available at the client for comparison, full reference metrics are of limited practical value in adaptive real-time video applications. Reduced reference metrics often require metadata to be transmitted with the bitstream, while no-reference metrics typically operate in the decompressed domain at the client side and require significant processing to extract spatial and temporal features. This paper proposes a heuristic, no-reference approach to video content classification which is specific to HEVC encoded bitstreams. The HEVC encoder already makes use of spatial characteristics to determine partitioning of coding units and temporal characteristics to determine the splitting of prediction units. We derive a function which approximates the spatio-temporal characteristics of the video sequence by using the weighted averages of the depth at which the coding unit quadtree is split and the prediction mode decision made by the encoder to estimate spatial and temporal characteristics respectively. Since the video content type of a sequence is determined by using high level information parsed from the video stream, spatio-temporal characteristics are identified without the need for full decoding and can

Effectiveness of instruction and video feedback on staff's use of prompts and children's adaptive responses during one-to-one training in children with severe to profound intellectual disability

NARCIS (Netherlands)

Vonderen, A.M.H. van; Swart, C.C.W. de; Didden, H.C.M.

2010-01-01

Although relatively many studies have addressed staff training and its effect on trainer behavior, the effects of staff training on trainee's adaptive behaviors have seldomly been examined. We therefore assessed effectiveness of staff training, consisting of instruction and video feedback, on (a)

Cochlea Segmentation using Iterated Random Walks with Shape Prior

DEFF Research Database (Denmark)

Ruiz Pujadas, Esmeralda; Kjer, Hans Martin; Vera, Sergio

2016-01-01

Cochlear implants can restore hearing to deaf or partially deaf patients. In order to plan the intervention, a model from high resolution μCT images is to be built from accurate cochlea segmentations and then, adapted to a patient-specific model. Thus, a precise segmentation is required to build...

Privacy enabling technology for video surveillance

Science.gov (United States)

Dufaux, Frédéric; Ouaret, Mourad; Abdeljaoued, Yousri; Navarro, Alfonso; Vergnenègre, Fabrice; Ebrahimi, Touradj

2006-05-01

In this paper, we address the problem privacy in video surveillance. We propose an efficient solution based on transformdomain scrambling of regions of interest in a video sequence. More specifically, the sign of selected transform coefficients is flipped during encoding. We address more specifically the case of Motion JPEG 2000. Simulation results show that the technique can be successfully applied to conceal information in regions of interest in the scene while providing with a good level of security. Furthermore, the scrambling is flexible and allows adjusting the amount of distortion introduced. This is achieved with a small impact on coding performance and negligible computational complexity increase. In the proposed video surveillance system, heterogeneous clients can remotely access the system through the Internet or 2G/3G mobile phone network. Thanks to the inherently scalable Motion JPEG 2000 codestream, the server is able to adapt the resolution and bandwidth of the delivered video depending on the usage environment of the client.

Data Partitioning Technique for Improved Video Prioritization

Directory of Open Access Journals (Sweden)

Ismail Amin Ali

2017-07-01

Full Text Available A compressed video bitstream can be partitioned according to the coding priority of the data, allowing prioritized wireless communication or selective dropping in a congested channel. Known as data partitioning in the H.264/Advanced Video Coding (AVC codec, this paper introduces a further sub-partition of one of the H.264/AVC codec’s three data-partitions. Results show a 5 dB improvement in Peak Signal-to-Noise Ratio (PSNR through this innovation. In particular, the data partition containing intra-coded residuals is sub-divided into data from: those macroblocks (MBs naturally intra-coded, and those MBs forcibly inserted for non-periodic intra-refresh. Interactive user-to-user video streaming can benefit, as then HTTP adaptive streaming is inappropriate and the High Efficiency Video Coding (HEVC codec is too energy demanding.

A Video Game-Based Framework for Analyzing Human-Robot Interaction: Characterizing Interface Design in Real-Time Interactive Multimedia Applications

Science.gov (United States)

2006-01-01

segments video game interaction into domain-independent components which together form a framework that can be used to characterize real-time interactive...multimedia applications in general and HRI in particular. We provide examples of using the components in both the video game and the Unmanned Aerial

Real-time skin feature identification in a time-sequential video stream

Science.gov (United States)

Kramberger, Iztok

2005-04-01

Skin color can be an important feature when tracking skin-colored objects. Particularly this is the case for computer-vision-based human-computer interfaces (HCI). Humans have a highly developed feeling of space and, therefore, it is reasonable to support this within intelligent HCI, where the importance of augmented reality can be foreseen. Joining human-like interaction techniques within multimodal HCI could, or will, gain a feature for modern mobile telecommunication devices. On the other hand, real-time processing plays an important role in achieving more natural and physically intuitive ways of human-machine interaction. The main scope of this work is the development of a stereoscopic computer-vision hardware-accelerated framework for real-time skin feature identification in the sense of a single-pass image segmentation process. The hardware-accelerated preprocessing stage is presented with the purpose of color and spatial filtering, where the skin color model within the hue-saturation-value (HSV) color space is given with a polyhedron of threshold values representing the basis of the filter model. An adaptive filter management unit is suggested to achieve better segmentation results. This enables the adoption of filter parameters to the current scene conditions in an adaptive way. Implementation of the suggested hardware structure is given at the level of filed programmable system level integrated circuit (FPSLIC) devices using an embedded microcontroller as their main feature. A stereoscopic clue is achieved using a time-sequential video stream, but this shows no difference for real-time processing requirements in terms of hardware complexity. The experimental results for the hardware-accelerated preprocessing stage are given by efficiency estimation of the presented hardware structure using a simple motion-detection algorithm based on a binary function.

Segmenting Trajectories by Movement States

NARCIS (Netherlands)

Buchin, M.; Kruckenberg, H.; Kölzsch, A.; Timpf, S.; Laube, P.

2013-01-01

Dividing movement trajectories according to different movement states of animals has become a challenge in movement ecology, as well as in algorithm development. In this study, we revisit and extend a framework for trajectory segmentation based on spatio-temporal criteria for this purpose. We adapt

The effects of video self-modeling on the decoding skills of children at risk for reading disabilities

OpenAIRE

Ayala, SM; O'Connor, R

2013-01-01

Ten first grade students who had responded poorly to a Tier 2 reading intervention in a response to intervention (RTI) model received an intervention of video self-modeling to improve decoding skills and sight word recognition. Students were video recorded blending and segmenting decodable words and reading sight words. Videos were edited and viewed a minimum of four times per week. Data were collected twice per week using curriculum-based measures. A single subject multiple baseline across p...

Automatic 2D segmentation of airways in thorax computed tomography images

International Nuclear Information System (INIS)

Cavalcante, Tarique da Silveira; Cortez, Paulo Cesar; Almeida, Thomaz Maia de; Felix, John Hebert da Silva; Holanda, Marcelo Alcantara

2013-01-01

Introduction: much of the world population is affected by pulmonary diseases, such as the bronchial asthma, bronchitis and bronchiectasis. The bronchial diagnosis is based on the airways state. In this sense, the automatic segmentation of the airways in Computed Tomography (CT) scans is a critical step in the aid to diagnosis of these diseases. Methods: this paper evaluates algorithms for airway automatic segmentation, using Neural Network Multilayer Perceptron (MLP) and Lung Densities Analysis (LDA) for detecting airways, along with Region Growing (RG), Active Contour Method (ACM) Balloon and Topology Adaptive to segment them. Results: we obtained results in three stages: comparative analysis of the detection algorithms MLP and LDA, with a gold standard acquired by three physicians with expertise in CT imaging of the chest; comparative analysis of segmentation algorithms ACM Balloon, ACM Topology Adaptive, MLP and RG; and evaluation of possible combinations between segmentation and detection algorithms, resulting in the complete method for automatic segmentation of the airways in 2D. Conclusion: the low incidence of false negative and the significant reduction of false positive, results in similarity coefficient and sensitivity exceeding 91% and 87% respectively, for a combination of algorithms with satisfactory segmentation quality. (author)

Spatially adapted augmentation of age-specific atlas-based segmentation using patch-based priors

Science.gov (United States)

Liu, Mengyuan; Seshamani, Sharmishtaa; Harrylock, Lisa; Kitsch, Averi; Miller, Steven; Chau, Van; Poskitt, Kenneth; Rousseau, Francois; Studholme, Colin

2014-03-01

One of the most common approaches to MRI brain tissue segmentation is to employ an atlas prior to initialize an Expectation- Maximization (EM) image labeling scheme using a statistical model of MRI intensities. This prior is commonly derived from a set of manually segmented training data from the population of interest. However, in cases where subject anatomy varies significantly from the prior anatomical average model (for example in the case where extreme developmental abnormalities or brain injuries occur), the prior tissue map does not provide adequate information about the observed MRI intensities to ensure the EM algorithm converges to an anatomically accurate labeling of the MRI. In this paper, we present a novel approach for automatic segmentation of such cases. This approach augments the atlas-based EM segmentation by exploring methods to build a hybrid tissue segmentation scheme that seeks to learn where an atlas prior fails (due to inadequate representation of anatomical variation in the statistical atlas) and utilize an alternative prior derived from a patch driven search of the atlas data. We describe a framework for incorporating this patch-based augmentation of EM (PBAEM) into a 4D age-specific atlas-based segmentation of developing brain anatomy. The proposed approach was evaluated on a set of MRI brain scans of premature neonates with ages ranging from 27.29 to 46.43 gestational weeks (GWs). Results indicated superior performance compared to the conventional atlas-based segmentation method, providing improved segmentation accuracy for gray matter, white matter, ventricles and sulcal CSF regions.

Deformable segmentation via sparse shape representation.

Science.gov (United States)

Zhang, Shaoting; Zhan, Yiqiang; Dewan, Maneesh; Huang, Junzhou; Metaxas, Dimitris N; Zhou, Xiang Sean

2011-01-01

Appearance and shape are two key elements exploited in medical image segmentation. However, in some medical image analysis tasks, appearance cues are weak/misleading due to disease/artifacts and often lead to erroneous segmentation. In this paper, a novel deformable model is proposed for robust segmentation in the presence of weak/misleading appearance cues. Owing to the less trustable appearance information, this method focuses on the effective shape modeling with two contributions. First, a shape composition method is designed to incorporate shape prior on-the-fly. Based on two sparsity observations, this method is robust to false appearance information and adaptive to statistically insignificant shape modes. Second, shape priors are modeled and used in a hierarchical fashion. More specifically, by using affinity propagation method, our deformable surface is divided into multiple partitions, on which local shape models are built independently. This scheme facilitates a more compact shape prior modeling and hence a more robust and efficient segmentation. Our deformable model is applied on two very diverse segmentation problems, liver segmentation in PET-CT images and rodent brain segmentation in MR images. Compared to state-of-art methods, our method achieves better performance in both studies.

Soft segmented inchworm robot with dielectric elastomer muscles

Science.gov (United States)

Conn, Andrew T.; Hinitt, Andrew D.; Wang, Pengchuan

2014-03-01

Robotic devices typically utilize rigid components in order to produce precise and robust operation. Rigidity becomes a significant impediment, however, when navigating confined or constricted environments e.g. search-and-rescue, industrial pipe inspection. In such cases adaptively conformable soft structures become optimal. Dielectric elastomers (DEs) are well suited for developing such soft robots since they are inherently compliant and can produce large musclelike actuation strains. In this paper, a soft segmented inchworm robot is presented that utilizes pneumatically-coupled DE membranes to produce inchworm-like locomotion. The robot is constructed from repeated body segments, each with a simple control architecture, so that the total length can be readily adapted by adding or removing segments. Each segment consists of a soft inflatable shell (internal pressure in range of 1.0-15.9 mBar) and a pair of antagonistic DE membranes (VHB 4905). Experimental testing of a single body segment is presented and the relationship between drive voltage, pneumatic pressure and active displacement is characterized. This demonstrates that pneumatic coupling of DE membranes induces complex non-linear electro-mechanical behaviour as drive voltage and pneumatic pressure are altered. Locomotion of a two-segment inchworm robot prototype with a passive length of 80 mm is presented. Artificial setae are included on the body shell to generate anisotropic friction for locomotion. A maximum locomotion speed of 4.1 mm/s was recorded at a drive frequency of 1.5 Hz, which compares favourably to biological counterparts. Future development of the soft inchworm robot are discussed including reflexive low-level control of individual segments.

Self-Occlusions and Disocclusions in Causal Video Object Segmentation

KAUST Repository

Yang, Yanchao

2016-02-19

We propose a method to detect disocclusion in video sequences of three-dimensional scenes and to partition the disoccluded regions into objects, defined by coherent deformation corresponding to surfaces in the scene. Our method infers deformation fields that are piecewise smooth by construction without the need for an explicit regularizer and the associated choice of weight. It then partitions the disoccluded region and groups its components with objects by leveraging on the complementarity of motion and appearance cues: Where appearance changes within an object, motion can usually be reliably inferred and used for grouping. Where appearance is close to constant, it can be used for grouping directly. We integrate both cues in an energy minimization framework, incorporate prior assumptions explicitly into the energy, and propose a numerical scheme. © 2015 IEEE.

SuBSENSE: a universal change detection method with local adaptive sensitivity.

Science.gov (United States)

St-Charles, Pierre-Luc; Bilodeau, Guillaume-Alexandre; Bergevin, Robert

2015-01-01

Foreground/background segmentation via change detection in video sequences is often used as a stepping stone in high-level analytics and applications. Despite the wide variety of methods that have been proposed for this problem, none has been able to fully address the complex nature of dynamic scenes in real surveillance tasks. In this paper, we present a universal pixel-level segmentation method that relies on spatiotemporal binary features as well as color information to detect changes. This allows camouflaged foreground objects to be detected more easily while most illumination variations are ignored. Besides, instead of using manually set, frame-wide constants to dictate model sensitivity and adaptation speed, we use pixel-level feedback loops to dynamically adjust our method's internal parameters without user intervention. These adjustments are based on the continuous monitoring of model fidelity and local segmentation noise levels. This new approach enables us to outperform all 32 previously tested state-of-the-art methods on the 2012 and 2014 versions of the ChangeDetection.net dataset in terms of overall F-Measure. The use of local binary image descriptors for pixel-level modeling also facilitates high-speed parallel implementations: our own version, which used no low-level or architecture-specific instruction, reached real-time processing speed on a midlevel desktop CPU. A complete C++ implementation based on OpenCV is available online.

Skin Segmentation Based on Graph Cuts

Institute of Scientific and Technical Information of China (English)

HU Zhilan; WANG Guijin; LIN Xinggang; YAN Hong

2009-01-01

Skin segmentation is widely used in many computer vision tasks to improve automated visualiza-tion. This paper presents a graph cuts algorithm to segment arbitrary skin regions from images. The detected face is used to determine the foreground skin seeds and the background non-skin seeds with the color probability distributions for the foreground represented by a single Gaussian model and for the background by a Gaussian mixture model. The probability distribution of the image is used for noise suppression to alle-viate the influence of the background regions having skin-like colors. Finally, the skin is segmented by graph cuts, with the regional parameter y optimally selected to adapt to different images. Tests of the algorithm on many real wodd photographs show that the scheme accurately segments skin regions and is robust against illumination variations, individual skin variations, and cluttered backgrounds.

Rate-distortion optimization for compressive video sampling

Science.gov (United States)

Liu, Ying; Vijayanagar, Krishna R.; Kim, Joohee

2014-05-01

The recently introduced compressed sensing (CS) framework enables low complexity video acquisition via sub- Nyquist rate sampling. In practice, the resulting CS samples are quantized and indexed by finitely many bits (bit-depth) for transmission. In applications where the bit-budget for video transmission is constrained, rate- distortion optimization (RDO) is essential for quality video reconstruction. In this work, we develop a double-level RDO scheme for compressive video sampling, where frame-level RDO is performed by adaptively allocating the fixed bit-budget per frame to each video block based on block-sparsity, and block-level RDO is performed by modelling the block reconstruction peak-signal-to-noise ratio (PSNR) as a quadratic function of quantization bit-depth. The optimal bit-depth and the number of CS samples are then obtained by setting the first derivative of the function to zero. In the experimental studies the model parameters are initialized with a small set of training data, which are then updated with local information in the model testing stage. Simulation results presented herein show that the proposed double-level RDO significantly enhances the reconstruction quality for a bit-budget constrained CS video transmission system.

A model for evaluating sharing policies for network-assisted HTTP adaptive streaming

NARCIS (Netherlands)

J.W.M. Kleinrouweler (Jan Willem); S. Cabrero Barros (Sergio); R.D. van der Mei (Rob); P.S. Cesar Garcia (Pablo Santiago)

2016-01-01

textabstractHTTP adaptive streaming (HAS) has become the dominant technology for streaming video over the Internet. It gained popularity because of its ability to adapt the video quality to the current network conditions and other appealing properties such as usage of off-the-shelf HTTP servers and

Boundary error analysis and categorization in the TRECVID news story segmentation task

NARCIS (Netherlands)

Arlandis, J.; Over, P.; Kraaij, W.

2005-01-01

In this paper, an error analysis based on boundary error popularity (frequency) including semantic boundary categorization is applied in the context of the news story segmentation task from TRECVTD1. Clusters of systems were defined based on the input resources they used including video, audio and

Effectiveness of Instruction and Video Feedback on Staff's Use of Prompts and Children's Adaptive Responses during One-to-One Training in Children with Severe to Profound Intellectual Disability

Science.gov (United States)

van Vonderen, Annemarie; de Swart, Charlotte; Didden, Robert

2010-01-01

Although relatively many studies have addressed staff training and its effect on trainer behavior, the effects of staff training on trainee's adaptive behaviors have seldomly been examined. We therefore assessed effectiveness of staff training, consisting of instruction and video feedback, on (a) staff's response prompting, and (b) staff's trainer…

Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem.

Science.gov (United States)

Wang, Jun Yi; Ngo, Michael M; Hessl, David; Hagerman, Randi J; Rivera, Susan M

2016-01-01

Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer's segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation) to 0.978 (for SegAdapter-corrected segmentation) for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large-scale neuroimaging studies, and potentially for segmenting other neural regions as

Delivering stable high-quality video: an SDN architecture with DASH assisting network elements

NARCIS (Netherlands)

J.W.M. Kleinrouweler (Jan Willem); S. Cabrero Barros (Sergio); P.S. Cesar Garcia (Pablo Santiago)

2016-01-01

textabstractDynamic adaptive streaming over HTTP (DASH) is a simple, but effective, technology for video streaming over the Internet. It provides adaptive streaming while being highly scalable at the side of the content providers. However, the mismatch between TCP and the adaptive bursty nature of

A model for evaluating sharing policies for network-assisted HTTP adaptive streaming

NARCIS (Netherlands)

Kleinrouweler, Jan Willem; Cabrero, Sergio; van der Mei, Rob; Cesar Garcia, P.S.

2016-01-01

HTTP adaptive streaming (HAS) has become the dominant technology for streaming video over the Internet. It gained popularity because of its ability to adapt the video quality to the current network conditions and other appealing properties such as usage of off-the-shelf HTTP servers and easy

Adaptive Content Management for UGC Video Delivery in Mobile Internet Era

Directory of Open Access Journals (Sweden)

Qilin Fan

2016-01-01

Full Text Available The demand of storing and transferring user generated content (UGC has been rapidly growing with the popularization of mobile devices equipped with video recording and playback capabilities. As a typical application of software-defined networks/network functions virtualization-based pervasive communications infrastructure, content delivery networks (CDNs have been widely leveraged to distribute contents across different geographical locations. Nevertheless, the content delivery for UGC is inefficient with the existing “pull-based” caching mechanism in traditional CDNs, because there exists a huge volume of lukewarm or cold UGC which results in a low cache hit ratio. In this paper, we propose a “push-based” caching mechanism to efficiently and economically deliver UGC videos. Different from traditional CDNs which separate the original content storage and caching, we directly store UGC videos into selective servers which serve as both reliable storages and user-facing uploading servers. By carefully and dynamically selecting the storage locations of each UGC object based on its popularity and locality, we not only guarantee the data availability but also remarkably improve the content distribution performance and reduce the distribution cost.

Infertilitas feminis caused by salpingemphraxis: therapeutic alliances of oviduct recanalization and video-laparoscope

International Nuclear Information System (INIS)

Din Xinxue; Fan Xuemei; Chen Tianwu; Ren Chaofeng; Zhou Dan; You Haiyan

2010-01-01

Objective: To explore the clinical value of therapeutic alliances of oviduct recanalization and video-laparoscope in the treatment of infertilitas feminis caused by multiple salpingemphraxis. Methods: Sixty-seven patients with salpingemphraxis in 127 oviducts complicated with adhesions in fimbriated extremities were enrolled into our study. All the patients underwent separation of adherences in fimbriated extremities and neostomy using a video-laparoscope 2 to 3 days after selective oviduct recanalization. The therapeutic effects were retrospectively reviewed focusing on recanalization rate of proximal three segments, complete recanalization rate, and pregnancy rate and relevant complications during the follow-up period were analyzed. And patients with infertilitas feminis in the follow-up period underwent repeated salpingography to determine whether oviduct was repeatebly obstructed. Results: The therapeutic alliance of oviduct recanalization and video-laparoscope were performed successfully in this cohort. Owing to the treatment of oviduct recanalization, recanalization rate of proximal three segments was 97.6% oviducts (124/127). Due to the alliance of oviduct recanalization and video-laparoscope, complete rate of oviduct were 98.4%(122/124). One year after operation, the pregnancy rate, ectopic pregnancy rate, and non pregnancy rate were 58.2% (39/67), 4.5% (3/67), and 37.3% (25/67), respectively. The patients with non pregnancy were composed by repeated oviduct obstruction in 25.4% (17/67) and non obstruction in 11.9% (8/67). Conclusion: Therapeutic alliances of oviduct recanalization and video-laparoscope could be an effective method for the treatment of infertilitas feminis caused by mulitiple salpingemphraxis, and be helpful for the enhancement of pregnancy rate. (authors)

Adaptive striping watershed segmentation method for processing microscopic images of overlapping irregular-shaped and multicentre particles.

Science.gov (United States)

Xiao, X; Bai, B; Xu, N; Wu, K

2015-04-01

Oversegmentation is a major drawback of the morphological watershed algorithm. Here, we study and reveal that the oversegmentation is not only because of the irregular shapes of the particle images, which people are familiar with, but also because of some particles, such as ellipses, with more than one centre. A new parameter, the striping level, is introduced and the criterion for striping parameter is built to help find the right markers prior to segmentation. An adaptive striping watershed algorithm is established by applying a procedure, called the marker searching algorithm, to find the markers, which can effectively suppress the oversegmentation. The effectiveness of the proposed method is validated by analysing some typical particle images including the images of gold nanorod ensembles. © 2014 The Authors Journal of Microscopy © 2014 Royal Microscopical Society.

Motion estimation for video coding efficient algorithms and architectures

CERN Document Server

Chakrabarti, Indrajit; Chatterjee, Sumit Kumar

2015-01-01

The need of video compression in the modern age of visual communication cannot be over-emphasized. This monograph will provide useful information to the postgraduate students and researchers who wish to work in the domain of VLSI design for video processing applications. In this book, one can find an in-depth discussion of several motion estimation algorithms and their VLSI implementation as conceived and developed by the authors. It records an account of research done involving fast three step search, successive elimination, one-bit transformation and its effective combination with diamond search and dynamic pixel truncation techniques. Two appendices provide a number of instances of proof of concept through Matlab and Verilog program segments. In this aspect, the book can be considered as first of its kind. The architectures have been developed with an eye to their applicability in everyday low-power handheld appliances including video camcorders and smartphones.

Research of Block-Based Motion Estimation Methods for Video Compression

Directory of Open Access Journals (Sweden)

Tropchenko Andrey

2016-08-01

Full Text Available This work is a review of the block-based algorithms used for motion estimation in video compression. It researches different types of block-based algorithms that range from the simplest named Full Search to the fast adaptive algorithms like Hierarchical Search. The algorithms evaluated in this paper are widely accepted by the video compressing community and have been used in implementing various standards, such as MPEG-4 Visual and H.264. The work also presents a very brief introduction to the entire flow of video compression.

Robust Video Stabilization Using Particle Keypoint Update and l1-Optimized Camera Path

Directory of Open Access Journals (Sweden)

Semi Jeon

2017-02-01

Full Text Available Acquisition of stabilized video is an important issue for various type of digital cameras. This paper presents an adaptive camera path estimation method using robust feature detection to remove shaky artifacts in a video. The proposed algorithm consists of three steps: (i robust feature detection using particle keypoints between adjacent frames; (ii camera path estimation and smoothing; and (iii rendering to reconstruct a stabilized video. As a result, the proposed algorithm can estimate the optimal homography by redefining important feature points in the flat region using particle keypoints. In addition, stabilized frames with less holes can be generated from the optimal, adaptive camera path that minimizes a temporal total variation (TV. The proposed video stabilization method is suitable for enhancing the visual quality for various portable cameras and can be applied to robot vision, driving assistant systems, and visual surveillance systems.

Hierarchical video surveillance architecture: a chassis for video big data analytics and exploration

Science.gov (United States)

Ajiboye, Sola O.; Birch, Philip; Chatwin, Christopher; Young, Rupert

2015-03-01

There is increasing reliance on video surveillance systems for systematic derivation, analysis and interpretation of the data needed for predicting, planning, evaluating and implementing public safety. This is evident from the massive number of surveillance cameras deployed across public locations. For example, in July 2013, the British Security Industry Association (BSIA) reported that over 4 million CCTV cameras had been installed in Britain alone. The BSIA also reveal that only 1.5% of these are state owned. In this paper, we propose a framework that allows access to data from privately owned cameras, with the aim of increasing the efficiency and accuracy of public safety planning, security activities, and decision support systems that are based on video integrated surveillance systems. The accuracy of results obtained from government-owned public safety infrastructure would improve greatly if privately owned surveillance systems `expose' relevant video-generated metadata events, such as triggered alerts and also permit query of a metadata repository. Subsequently, a police officer, for example, with an appropriate level of system permission can query unified video systems across a large geographical area such as a city or a country to predict the location of an interesting entity, such as a pedestrian or a vehicle. This becomes possible with our proposed novel hierarchical architecture, the Fused Video Surveillance Architecture (FVSA). At the high level, FVSA comprises of a hardware framework that is supported by a multi-layer abstraction software interface. It presents video surveillance systems as an adapted computational grid of intelligent services, which is integration-enabled to communicate with other compatible systems in the Internet of Things (IoT).

Video game characteristics, happiness and flow as predictors of addiction among video game players: A pilot study.

Science.gov (United States)

Hull, Damien C; Williams, Glenn A; Griffiths, Mark D

2013-09-01

Video games provide opportunities for positive psychological experiences such as flow-like phenomena during play and general happiness that could be associated with gaming achievements. However, research has shown that specific features of game play may be associated with problematic behaviour associated with addiction-like experiences. The study was aimed at analysing whether certain structural characteristics of video games, flow, and global happiness could be predictive of video game addiction. A total of 110 video game players were surveyed about a game they had recently played by using a 24-item checklist of structural characteristics, an adapted Flow State Scale, the Oxford Happiness Questionnaire, and the Game Addiction Scale. The study revealed decreases in general happiness had the strongest role in predicting increases in gaming addiction. One of the nine factors of the flow experience was a significant predictor of gaming addiction - perceptions of time being altered during play. The structural characteristic that significantly predicted addiction was its social element with increased sociability being associated with higher levels of addictive-like experiences. Overall, the structural characteristics of video games, elements of the flow experience, and general happiness accounted for 49.2% of the total variance in Game Addiction Scale levels. Implications for interventions are discussed, particularly with regard to making players more aware of time passing and in capitalising on benefits of social features of video game play to guard against addictive-like tendencies among video game players.

Video game characteristics, happiness and flow as predictors of addiction among video game players: A pilot study

Science.gov (United States)

Hull, Damien C.; Williams, Glenn A.; Griffiths, Mark D.

2013-01-01

Aims: Video games provide opportunities for positive psychological experiences such as flow-like phenomena during play and general happiness that could be associated with gaming achievements. However, research has shown that specific features of game play may be associated with problematic behaviour associated with addiction-like experiences. The study was aimed at analysing whether certain structural characteristics of video games, flow, and global happiness could be predictive of video game addiction. Method: A total of 110 video game players were surveyed about a game they had recently played by using a 24-item checklist of structural characteristics, an adapted Flow State Scale, the Oxford Happiness Questionnaire, and the Game Addiction Scale. Results: The study revealed decreases in general happiness had the strongest role in predicting increases in gaming addiction. One of the nine factors of the flow experience was a significant predictor of gaming addiction – perceptions of time being altered during play. The structural characteristic that significantly predicted addiction was its social element with increased sociability being associated with higher levels of addictive-like experiences. Overall, the structural characteristics of video games, elements of the flow experience, and general happiness accounted for 49.2% of the total variance in Game Addiction Scale levels. Conclusions: Implications for interventions are discussed, particularly with regard to making players more aware of time passing and in capitalising on benefits of social features of video game play to guard against addictive-like tendencies among video game players. PMID:25215196

Simultaneous Whole-Brain Segmentation and White Matter Lesion Detection Using Contrast-Adaptive Probabilistic Models

DEFF Research Database (Denmark)

Puonti, Oula; Van Leemput, Koen

2016-01-01

In this paper we propose a new generative model for simultaneous brain parcellation and white matter lesion segmentation from multi-contrast magnetic resonance images. The method combines an existing whole-brain segmentation technique with a novel spatial lesion model based on a convolutional...... restricted Boltzmann machine. Unlike current state-of-the-art lesion detection techniques based on discriminative modeling, the proposed method is not tuned to one specific scanner or imaging protocol, and simultaneously segments dozens of neuroanatomical structures. Experiments on a public benchmark dataset...... in multiple sclerosis indicate that the method’s lesion segmentation accuracy compares well to that of the current state-of-the-art in the field, while additionally providing robust whole-brain segmentations....

Query by example video based on fuzzy c-means initialized by fixed clustering center

Science.gov (United States)

Hou, Sujuan; Zhou, Shangbo; Siddique, Muhammad Abubakar

2012-04-01

Currently, the high complexity of video contents has posed the following major challenges for fast retrieval: (1) efficient similarity measurements, and (2) efficient indexing on the compact representations. A video-retrieval strategy based on fuzzy c-means (FCM) is presented for querying by example. Initially, the query video is segmented and represented by a set of shots, each shot can be represented by a key frame, and then we used video processing techniques to find visual cues to represent the key frame. Next, because the FCM algorithm is sensitive to the initializations, here we initialized the cluster center by the shots of query video so that users could achieve appropriate convergence. After an FCM cluster was initialized by the query video, each shot of query video was considered a benchmark point in the aforesaid cluster, and each shot in the database possessed a class label. The similarity between the shots in the database with the same class label and benchmark point can be transformed into the distance between them. Finally, the similarity between the query video and the video in database was transformed into the number of similar shots. Our experimental results demonstrated the performance of this proposed approach.

Quality-Based Backlight Optimization for Video Playback on Handheld Devices

Directory of Open Access Journals (Sweden)

Liang Cheng

2007-01-01

Full Text Available For a typical handheld device, the backlight accounts for a significant percentage of the total energy consumption (e.g., around 30% for a Compaq iPAQ 3650. Substantial energy savings can be achieved by dynamically adapting backlight intensity levels on such low-power portable devices. In this paper, we analyze the characteristics of video streaming services and propose a cross-layer optimization scheme called quality adapted backlight scaling (QABS to achieve backlight energy savings for video playback applications on handheld devices. Specifically, we present a fast algorithm to optimize backlight dimming while keeping the degradation in image quality to a minimum so that the overall service quality is close to a specified threshold. Additionally, we propose two effective techniques to prevent frequent backlight switching, which negatively affects user perception of video. Our initial experimental results indicate that the energy used for backlight is significantly reduced, while the desired quality is satisfied. The proposed algorithms can be realized in real time.

Using learning analytics to evaluate a video-based lecture series.

Science.gov (United States)

Lau, K H Vincent; Farooque, Pue; Leydon, Gary; Schwartz, Michael L; Sadler, R Mark; Moeller, Jeremy J

2018-01-01

The video-based lecture (VBL), an important component of the flipped classroom (FC) and massive open online course (MOOC) approaches to medical education, has primarily been evaluated through direct learner feedback. Evaluation may be enhanced through learner analytics (LA) - analysis of quantitative audience usage data generated by video-sharing platforms. We applied LA to an experimental series of ten VBLs on electroencephalography (EEG) interpretation, uploaded to YouTube in the model of a publicly accessible MOOC. Trends in view count; total percentage of video viewed and audience retention (AR) (percentage of viewers watching at a time point compared to the initial total) were examined. The pattern of average AR decline was characterized using regression analysis, revealing a uniform linear decline in viewership for each video, with no evidence of an optimal VBL length. Segments with transient increases in AR corresponded to those focused on core concepts, indicative of content requiring more detailed evaluation. We propose a model for applying LA at four levels: global, series, video, and feedback. LA may be a useful tool in evaluating a VBL series. Our proposed model combines analytics data and learner self-report for comprehensive evaluation.

Boundary segmentation for fluorescence microscopy using steerable filters

Science.gov (United States)

Ho, David Joon; Salama, Paul; Dunn, Kenneth W.; Delp, Edward J.

2017-02-01

Fluorescence microscopy is used to image multiple subcellular structures in living cells which are not readily observed using conventional optical microscopy. Moreover, two-photon microscopy is widely used to image structures deeper in tissue. Recent advancement in fluorescence microscopy has enabled the generation of large data sets of images at different depths, times, and spectral channels. Thus, automatic object segmentation is necessary since manual segmentation would be inefficient and biased. However, automatic segmentation is still a challenging problem as regions of interest may not have well defined boundaries as well as non-uniform pixel intensities. This paper describes a method for segmenting tubular structures in fluorescence microscopy images of rat kidney and liver samples using adaptive histogram equalization, foreground/background segmentation, steerable filters to capture directional tendencies, and connected-component analysis. The results from several data sets demonstrate that our method can segment tubular boundaries successfully. Moreover, our method has better performance when compared to other popular image segmentation methods when using ground truth data obtained via manual segmentation.

Low Cost Skin Segmentation Scheme in Videos Using Two Alternative Methods for Dynamic Hand Gesture Detection Method

Directory of Open Access Journals (Sweden)

Eman Thabet

2017-01-01

Full Text Available Recent years have witnessed renewed interest in developing skin segmentation approaches. Skin feature segmentation has been widely employed in different aspects of computer vision applications including face detection and hand gestures recognition systems. This is mostly due to the attractive characteristics of skin colour and its effectiveness to object segmentation. On the contrary, there are certain challenges in using human skin colour as a feature to segment dynamic hand gesture, due to various illumination conditions, complicated environment, and computation time or real-time method. These challenges have led to the insufficiency of many of the skin color segmentation approaches. Therefore, to produce simple, effective, and cost efficient skin segmentation, this paper has proposed a skin segmentation scheme. This scheme includes two procedures for calculating generic threshold ranges in Cb-Cr colour space. The first procedure uses threshold values trained online from nose pixels of the face region. Meanwhile, the second procedure known as the offline training procedure uses thresholds trained out of skin samples and weighted equation. The experimental results showed that the proposed scheme achieved good performance in terms of efficiency and computation time.

For Video Streaming/Delivery: Is HTML5 the Real Fix?

Directory of Open Access Journals (Sweden)

John Millard

2013-10-01

Full Text Available The general movement towards streaming or playing videos on the web has grown exponentially in the last decade. The combination of new streaming technologies and faster Internet connections continue to provide enhanced and robust user experience for video content. For many organizations, adding videos on their websites has transitioned from a “cool” feature to a mission critical service. Some of the benefits in putting videos online include: to engage and convert visitors, to raise awareness or drive interest, to share inspirational stories or recent unique events, etc. Along with the growth in the use and need for video content on the web; delivering videos online also remains a messy activity for developers and web teams. Examples of existing challenges include creating more accessible videos with captions and delivering content (using adaptive streaming for the diverse range of mobile and tablet devices. In this article, we report on the decision-making and early results in using the Kaltura video platform in two popular library platforms: CONTENTdm and DSpace.

Robust and efficient fiducial tracking for augmented reality in HD-laparoscopic video streams

Science.gov (United States)

Mueller, M.; Groch, A.; Baumhauer, M.; Maier-Hein, L.; Teber, D.; Rassweiler, J.; Meinzer, H.-P.; Wegner, In.

2012-02-01

Augmented Reality (AR) is a convenient way of porting information from medical images into the surgical field of view and can deliver valuable assistance to the surgeon, especially in laparoscopic procedures. In addition, high definition (HD) laparoscopic video devices are a great improvement over the previously used low resolution equipment. However, in AR applications that rely on real-time detection of fiducials from video streams, the demand for efficient image processing has increased due to the introduction of HD devices. We present an algorithm based on the well-known Conditional Density Propagation (CONDENSATION) algorithm which can satisfy these new demands. By incorporating a prediction around an already existing and robust segmentation algorithm, we can speed up the whole procedure while leaving the robustness of the fiducial segmentation untouched. For evaluation purposes we tested the algorithm on recordings from real interventions, allowing for a meaningful interpretation of the results. Our results show that we can accelerate the segmentation by a factor of 3.5 on average. Moreover, the prediction information can be used to compensate for fiducials that are temporarily occluded or out of scope, providing greater stability.

Adaptive intrusion data system

International Nuclear Information System (INIS)

Johnson, C.S.

1976-01-01

An Adaptive Intrusion Data System (AIDS) was developed to collect data from intrusion alarm sensors as part of an evaluation system to improve sensor performance. AIDS is a unique digital data compression, storage, and formatting system. It also incorporates capability for video selection and recording for assessment of the sensors monitored by the system. The system is software reprogrammable to numerous configurations that may be utilized for the collection of environmental, bi-level, analog and video data. The output of the system is digital tapes formatted for direct data reduction on a CDC 6400 computer, and video tapes containing timed tagged information that can be correlated with the digital data

Remote Video Monitor of Vehicles in Cooperative Information Platform

Science.gov (United States)

Qin, Guofeng; Wang, Xiaoguo; Wang, Li; Li, Yang; Li, Qiyan

Detection of vehicles plays an important role in the area of the modern intelligent traffic management. And the pattern recognition is a hot issue in the area of computer vision. An auto- recognition system in cooperative information platform is studied. In the cooperative platform, 3G wireless network, including GPS, GPRS (CDMA), Internet (Intranet), remote video monitor and M-DMB networks are integrated. The remote video information can be taken from the terminals and sent to the cooperative platform, then detected by the auto-recognition system. The images are pretreated and segmented, including feature extraction, template matching and pattern recognition. The system identifies different models and gets vehicular traffic statistics. Finally, the implementation of the system is introduced.

Efficient Coding of Shape and Transparency for Video Objects

DEFF Research Database (Denmark)

Aghito, Shankar Manuel; Forchhammer, Søren

2007-01-01

A novel scheme for coding gray-level alpha planes in object-based video is presented. Gray-level alpha planes convey the shape and the transparency information, which are required for smooth composition of video objects. The algorithm proposed is based on the segmentation of the alpha plane...... in three layers: binary shape layer, opaque layer, and intermediate layer. Thus, the latter two layers replace the single transparency layer of MPEG-4 Part 2. Different encoding schemes are specifically designed for each layer, utilizing cross-layer correlations to reduce the bit rate. First, the binary...... demonstrating that the proposed techniques provide substantial bit rate savings coding shape and transparency when compared to the tools adopted in MPEG-4 Part 2....

A clinical pilot study of a modular video-CT augmentation system for image-guided skull base surgery

Science.gov (United States)

Liu, Wen P.; Mirota, Daniel J.; Uneri, Ali; Otake, Yoshito; Hager, Gregory; Reh, Douglas D.; Ishii, Masaru; Gallia, Gary L.; Siewerdsen, Jeffrey H.

2012-02-01

Augmentation of endoscopic video with preoperative or intraoperative image data [e.g., planning data and/or anatomical segmentations defined in computed tomography (CT) and magnetic resonance (MR)], can improve navigation, spatial orientation, confidence, and tissue resection in skull base surgery, especially with respect to critical neurovascular structures that may be difficult to visualize in the video scene. This paper presents the engineering and evaluation of a video augmentation system for endoscopic skull base surgery translated to use in a clinical study. Extension of previous research yielded a practical system with a modular design that can be applied to other endoscopic surgeries, including orthopedic, abdominal, and thoracic procedures. A clinical pilot study is underway to assess feasibility and benefit to surgical performance by overlaying CT or MR planning data in realtime, high-definition endoscopic video. Preoperative planning included segmentation of the carotid arteries, optic nerves, and surgical target volume (e.g., tumor). An automated camera calibration process was developed that demonstrates mean re-projection accuracy (0.7+/-0.3) pixels and mean target registration error of (2.3+/-1.5) mm. An IRB-approved clinical study involving fifteen patients undergoing skull base tumor surgery is underway in which each surgery includes the experimental video-CT system deployed in parallel to the standard-of-care (unaugmented) video display. Questionnaires distributed to one neurosurgeon and two otolaryngologists are used to assess primary outcome measures regarding the benefit to surgical confidence in localizing critical structures and targets by means of video overlay during surgical approach, resection, and reconstruction.

Video Bioinformatics Analysis of Human Embryonic Stem Cell Colony Growth

Science.gov (United States)

Lin, Sabrina; Fonteno, Shawn; Satish, Shruthi; Bhanu, Bir; Talbot, Prue

2010-01-01

Because video data are complex and are comprised of many images, mining information from video material is difficult to do without the aid of computer software. Video bioinformatics is a powerful quantitative approach for extracting spatio-temporal data from video images using computer software to perform dating mining and analysis. In this article, we introduce a video bioinformatics method for quantifying the growth of human embryonic stem cells (hESC) by analyzing time-lapse videos collected in a Nikon BioStation CT incubator equipped with a camera for video imaging. In our experiments, hESC colonies that were attached to Matrigel were filmed for 48 hours in the BioStation CT. To determine the rate of growth of these colonies, recipes were developed using CL-Quant software which enables users to extract various types of data from video images. To accurately evaluate colony growth, three recipes were created. The first segmented the image into the colony and background, the second enhanced the image to define colonies throughout the video sequence accurately, and the third measured the number of pixels in the colony over time. The three recipes were run in sequence on video data collected in a BioStation CT to analyze the rate of growth of individual hESC colonies over 48 hours. To verify the truthfulness of the CL-Quant recipes, the same data were analyzed manually using Adobe Photoshop software. When the data obtained using the CL-Quant recipes and Photoshop were compared, results were virtually identical, indicating the CL-Quant recipes were truthful. The method described here could be applied to any video data to measure growth rates of hESC or other cells that grow in colonies. In addition, other video bioinformatics recipes can be developed in the future for other cell processes such as migration, apoptosis, and cell adhesion. PMID:20495527

Efficient depth intraprediction method for H.264/AVC-based three-dimensional video coding

Science.gov (United States)

Oh, Kwan-Jung; Oh, Byung Tae

2015-04-01

We present an intracoding method that is applicable to depth map coding in multiview plus depth systems. Our approach combines skip prediction and plane segmentation-based prediction. The proposed depth intraskip prediction uses the estimated direction at both the encoder and decoder, and does not need to encode residual data. Our plane segmentation-based intraprediction divides the current block into biregions, and applies a different prediction scheme for each segmented region. This method avoids incorrect estimations across different regions, resulting in higher prediction accuracy. Simulation results demonstrate that the proposed scheme is superior to H.264/advanced video coding intraprediction and has the ability to improve the subjective rendering quality.

Automatic Video-based Analysis of Human Motion

DEFF Research Database (Denmark)

Fihl, Preben

The human motion contains valuable information in many situations and people frequently perform an unconscious analysis of the motion of other people to understand their actions, intentions, and state of mind. An automatic analysis of human motion will facilitate many applications and thus has...... received great interest from both industry and research communities. The focus of this thesis is on video-based analysis of human motion and the thesis presents work within three overall topics, namely foreground segmentation, action recognition, and human pose estimation. Foreground segmentation is often...... the first important step in the analysis of human motion. By separating foreground from background the subsequent analysis can be focused and efficient. This thesis presents a robust background subtraction method that can be initialized with foreground objects in the scene and is capable of handling...

Physical activity patterns across time-segmented youth sport flag football practice.

Science.gov (United States)

Schlechter, Chelsey R; Guagliano, Justin M; Rosenkranz, Richard R; Milliken, George A; Dzewaltowski, David A

2018-02-08

Youth sport (YS) reaches a large number of children world-wide and contributes substantially to children's daily physical activity (PA), yet less than half of YS time has been shown to be spent in moderate-to-vigorous physical activity (MVPA). Physical activity during practice is likely to vary depending on practice structure that changes across YS time, therefore the purpose of this study was 1) to describe the type and frequency of segments of time, defined by contextual characteristics of practice structure, during YS practices and 2) determine the influence of these segments on PA. Research assistants video-recorded the full duration of 28 practices from 14 boys' flag football teams (2 practices/team) while children concurrently (N = 111, aged 5-11 years, mean 7.9 ± 1.2 years) wore ActiGraph GT1M accelerometers to measure PA. Observers divided videos of each practice into continuous context time segments (N = 204; mean-segments-per-practice = 7.3, SD = 2.5) using start/stop points defined by change in context characteristics, and assigned a value for task (e.g., management, gameplay, etc.), member arrangement (e.g., small group, whole group, etc.), and setting demand (i.e., fosters participation, fosters exclusion). Segments were then paired with accelerometer data. Data were analyzed using a multilevel model with segment as unit of analysis. Whole practices averaged 34 ± 2.4% of time spent in MVPA. Free-play (51.5 ± 5.5%), gameplay (53.6 ± 3.7%), and warm-up (53.9 ± 3.6%) segments had greater percentage of time (%time) in MVPA compared to fitness (36.8 ± 4.4%) segments (p ≤ .01). Greater %time was spent in MVPA during free-play segments compared to scrimmage (30.2 ± 4.6%), strategy (30.6 ± 3.2%), and sport-skill (31.6 ± 3.1%) segments (p ≤ .01), and in segments that fostered participation (36.1 ± 2.7%) than segments that fostered exclusion (29.1 ± 3.0%; p ≤ .01

Fast Temporal Activity Proposals for Efficient Detection of Human Actions in Untrimmed Videos

KAUST Repository

Heilbron, Fabian Caba; Niebles, Juan Carlos; Ghanem, Bernard

2016-01-01

In many large-scale video analysis scenarios, one is interested in localizing and recognizing human activities that occur in short temporal intervals within long untrimmed videos. Current approaches for activity detection still struggle to handle large-scale video collections and the task remains relatively unexplored. This is in part due to the computational complexity of current action recognition approaches and the lack of a method that proposes fewer intervals in the video, where activity processing can be focused. In this paper, we introduce a proposal method that aims to recover temporal segments containing actions in untrimmed videos. Building on techniques for learning sparse dictionaries, we introduce a learning framework to represent and retrieve activity proposals. We demonstrate the capabilities of our method in not only producing high quality proposals but also in its efficiency. Finally, we show the positive impact our method has on recognition performance when it is used for action detection, while running at 10FPS.

Fast Temporal Activity Proposals for Efficient Detection of Human Actions in Untrimmed Videos

KAUST Repository

Heilbron, Fabian Caba

2016-12-13

In many large-scale video analysis scenarios, one is interested in localizing and recognizing human activities that occur in short temporal intervals within long untrimmed videos. Current approaches for activity detection still struggle to handle large-scale video collections and the task remains relatively unexplored. This is in part due to the computational complexity of current action recognition approaches and the lack of a method that proposes fewer intervals in the video, where activity processing can be focused. In this paper, we introduce a proposal method that aims to recover temporal segments containing actions in untrimmed videos. Building on techniques for learning sparse dictionaries, we introduce a learning framework to represent and retrieve activity proposals. We demonstrate the capabilities of our method in not only producing high quality proposals but also in its efficiency. Finally, we show the positive impact our method has on recognition performance when it is used for action detection, while running at 10FPS.

An openstack-based flexible video transcoding framework in live

Science.gov (United States)

Shi, Qisen; Song, Jianxin

2017-08-01

With the rapid development of mobile live business, transcoding HD video is often a challenge for mobile devices due to their limited processing capability and bandwidth-constrained network connection. For live service providers, it's wasteful for resources to delay lots of transcoding server because some of them are free to work sometimes. To deal with this issue, this paper proposed an Openstack-based flexible transcoding framework to achieve real-time video adaption for mobile device and make computing resources used efficiently. To this end, we introduced a special method of video stream splitting and VMs resource scheduling based on access pressure prediction,which is forecasted by an AR model.

Efficient Delivery of Scalable Video Using a Streaming Class Model

Directory of Open Access Journals (Sweden)

Jason J. Quinlan

2018-03-01

Full Text Available When we couple the rise in video streaming with the growing number of portable devices (smart phones, tablets, laptops, we see an ever-increasing demand for high-definition video online while on the move. Wireless networks are inherently characterised by restricted shared bandwidth and relatively high error loss rates, thus presenting a challenge for the efficient delivery of high quality video. Additionally, mobile devices can support/demand a range of video resolutions and qualities. This demand for mobile streaming highlights the need for adaptive video streaming schemes that can adjust to available bandwidth and heterogeneity, and can provide a graceful changes in video quality, all while respecting viewing satisfaction. In this context, the use of well-known scalable/layered media streaming techniques, commonly known as scalable video coding (SVC, is an attractive solution. SVC encodes a number of video quality levels within a single media stream. This has been shown to be an especially effective and efficient solution, but it fares badly in the presence of datagram losses. While multiple description coding (MDC can reduce the effects of packet loss on scalable video delivery, the increased delivery cost is counterproductive for constrained networks. This situation is accentuated in cases where only the lower quality level is required. In this paper, we assess these issues and propose a new approach called Streaming Classes (SC through which we can define a key set of quality levels, each of which can be delivered in a self-contained manner. This facilitates efficient delivery, yielding reduced transmission byte-cost for devices requiring lower quality, relative to MDC and Adaptive Layer Distribution (ALD (42% and 76% respective reduction for layer 2, while also maintaining high levels of consistent quality. We also illustrate how selective packetisation technique can further reduce the effects of packet loss on viewable quality by

Predictive no-reference assessment of video quality

NARCIS (Netherlands)

Torres Vega, M.; Mocanu, D.C.; Stavrou, S.; Liotta, A.

2017-01-01

Among the various means to evaluate the quality of video streams, light-weight No-Reference (NR) methods have low computation and may be executed on thin clients. Thus, these methods would be perfect candidates in cases of real-time quality assessment, automated quality control and in adaptive

Random Linear Network Coding for 5G Mobile Video Delivery

Directory of Open Access Journals (Sweden)

Dejan Vukobratovic

2018-03-01

Full Text Available An exponential increase in mobile video delivery will continue with the demand for higher resolution, multi-view and large-scale multicast video services. Novel fifth generation (5G 3GPP New Radio (NR standard will bring a number of new opportunities for optimizing video delivery across both 5G core and radio access networks. One of the promising approaches for video quality adaptation, throughput enhancement and erasure protection is the use of packet-level random linear network coding (RLNC. In this review paper, we discuss the integration of RLNC into the 5G NR standard, building upon the ideas and opportunities identified in 4G LTE. We explicitly identify and discuss in detail novel 5G NR features that provide support for RLNC-based video delivery in 5G, thus pointing out to the promising avenues for future research.

Generic method for automatic bladder segmentation on cone beam CT using a patient-specific bladder shape model

International Nuclear Information System (INIS)

Schoot, A. J. A. J. van de; Schooneveldt, G.; Wognum, S.; Stalpers, L. J. A.; Rasch, C. R. N.; Bel, A.; Hoogeman, M. S.; Chai, X.

2014-01-01

Purpose: The aim of this study is to develop and validate a generic method for automatic bladder segmentation on cone beam computed tomography (CBCT), independent of gender and treatment position (prone or supine), using only pretreatment imaging data. Methods: Data of 20 patients, treated for tumors in the pelvic region with the entire bladder visible on CT and CBCT, were divided into four equally sized groups based on gender and treatment position. The full and empty bladder contour, that can be acquired with pretreatment CT imaging, were used to generate a patient-specific bladder shape model. This model was used to guide the segmentation process on CBCT. To obtain the bladder segmentation, the reference bladder contour was deformed iteratively by maximizing the cross-correlation between directional grey value gradients over the reference and CBCT bladder edge. To overcome incorrect segmentations caused by CBCT image artifacts, automatic adaptations were implemented. Moreover, locally incorrect segmentations could be adapted manually. After each adapted segmentation, the bladder shape model was expanded and new shape patterns were calculated for following segmentations. All available CBCTs were used to validate the segmentation algorithm. The bladder segmentations were validated by comparison with the manual delineations and the segmentation performance was quantified using the Dice similarity coefficient (DSC), surface distance error (SDE) and SD of contour-to-contour distances. Also, bladder volumes obtained by manual delineations and segmentations were compared using a Bland-Altman error analysis. Results: The mean DSC, mean SDE, and mean SD of contour-to-contour distances between segmentations and manual delineations were 0.87, 0.27 cm and 0.22 cm (female, prone), 0.85, 0.28 cm and 0.22 cm (female, supine), 0.89, 0.21 cm and 0.17 cm (male, supine) and 0.88, 0.23 cm and 0.17 cm (male, prone), respectively. Manual local adaptations improved the segmentation

Scalable Video Streaming Relay for Smart Mobile Devices in Wireless Networks.

Science.gov (United States)

Kwon, Dongwoo; Je, Huigwang; Kim, Hyeonwoo; Ju, Hongtaek; An, Donghyeok

2016-01-01

Recently, smart mobile devices and wireless communication technologies such as WiFi, third generation (3G), and long-term evolution (LTE) have been rapidly deployed. Many smart mobile device users can access the Internet wirelessly, which has increased mobile traffic. In 2014, more than half of the mobile traffic around the world was devoted to satisfying the increased demand for the video streaming. In this paper, we propose a scalable video streaming relay scheme. Because many collisions degrade the scalability of video streaming, we first separate networks to prevent excessive contention between devices. In addition, the member device controls the video download rate in order to adapt to video playback. If the data are sufficiently buffered, the member device stops the download. If not, it requests additional video data. We implemented apps to evaluate the proposed scheme and conducted experiments with smart mobile devices. The results showed that our scheme improves the scalability of video streaming in a wireless local area network (WLAN).

Scalable Video Streaming Relay for Smart Mobile Devices in Wireless Networks

Science.gov (United States)

Kwon, Dongwoo; Je, Huigwang; Kim, Hyeonwoo; Ju, Hongtaek; An, Donghyeok

2016-01-01

Recently, smart mobile devices and wireless communication technologies such as WiFi, third generation (3G), and long-term evolution (LTE) have been rapidly deployed. Many smart mobile device users can access the Internet wirelessly, which has increased mobile traffic. In 2014, more than half of the mobile traffic around the world was devoted to satisfying the increased demand for the video streaming. In this paper, we propose a scalable video streaming relay scheme. Because many collisions degrade the scalability of video streaming, we first separate networks to prevent excessive contention between devices. In addition, the member device controls the video download rate in order to adapt to video playback. If the data are sufficiently buffered, the member device stops the download. If not, it requests additional video data. We implemented apps to evaluate the proposed scheme and conducted experiments with smart mobile devices. The results showed that our scheme improves the scalability of video streaming in a wireless local area network (WLAN). PMID:27907113

Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem.

Directory of Open Access Journals (Sweden)

Jun Yi Wang

Full Text Available Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer's segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation to 0.978 (for SegAdapter-corrected segmentation for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by <0.01. These results suggest that the combination of automated segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large

Comparison of Video Steganography Methods for Watermark Embedding

Directory of Open Access Journals (Sweden)

Griberman David

2016-05-01

Full Text Available The paper focuses on the comparison of video steganography methods for the purpose of digital watermarking in the context of copyright protection. Four embedding methods that use Discrete Cosine and Discrete Wavelet Transforms have been researched and compared based on their embedding efficiency and fidelity. A video steganography program has been developed in the Java programming language with all of the researched methods implemented for experiments. The experiments used 3 video containers with different amounts of movement. The impact of the movement has been addressed in the paper as well as the ways of potential improvement of embedding efficiency using adaptive embedding based on the movement amount. Results of the research have been verified using a survey with 17 participants.

Daily Digest Generation of Kindergartner from Surveillance Video

Science.gov (United States)

Ishikawa, Tomoya; Wang, Yu; Kato, Jien

Nowadays, children spend most of their time in kindergarten as well as nursery schools. This directly brings a requirement to the parents: they want to see how everyday goes with their kids. To meet this requirement, in this paper, we propose a method to automatically generate video digest that records kids' daily life in kindergarten. Our method involves two steps. The first is to efficiently narrow down the searching space by analyzing the noisy RFID tag log which records kids' temporal location, while the second is to use visual features and time constrains to recognize events and pick out video segments for each individual event. The accuracy of our method was evaluated with quantitative experiment and the superior of the digest that generated by our method was confirmed via questionnaire survey.

SU-E-J-220: Evaluation of Atlas-Based Auto-Segmentation (ABAS) in Head-And-Neck Adaptive Radiotherapy

International Nuclear Information System (INIS)

Liu, Q; Yan, D

2014-01-01

Purpose: Evaluate the accuracy of atlas-based auto segmentation of organs at risk (OARs) on both helical CT (HCT) and cone beam CT (CBCT) images in head and neck (HN) cancer adaptive radiotherapy (ART). Methods: Six HN patients treated in the ART process were included in this study. For each patient, three images were selected: pretreatment planning CT (PreTx-HCT), in treatment CT for replanning (InTx-HCT) and a CBCT acquired in the same day of the InTx-HCT. Three clinical procedures of auto segmentation and deformable registration performed in the ART process were evaluated: a) auto segmentation on PreTx-HCT using multi-subject atlases, b) intra-patient propagation of OARs from PreTx-HCT to InTx-HCT using deformable HCT-to-HCT image registration, and c) intra-patient propagation of OARs from PreTx-HCT to CBCT using deformable CBCT-to-HCT image registration. Seven OARs (brainstem, cord, L/R parotid, L/R submandibular gland and mandible) were manually contoured on PreTx-HCT and InTx-HCT for comparison. In addition, manual contours on InTx-CT were copied on the same day CBCT, and a local region rigid body registration was performed accordingly for each individual OAR. For procedures a) and b), auto contours were compared to manual contours, and for c) auto contours were compared to those rigidly transferred contours on CBCT. Dice similarity coefficients (DSC) and mean surface distances of agreement (MSDA) were calculated for evaluation. Results: For procedure a), the mean DSC/MSDA of most OARs are >80%/±2mm. For intra-patient HCT-to-HCT propagation, the Resultimproved to >85%/±1.5mm. Compared to HCT-to-HCT, the mean DSC for HCT-to-CBCT propagation drops ∼2–3% and MSDA increases ∼0.2mm. This Resultindicates that the inferior imaging quality of CBCT seems only degrade auto propagation performance slightly. Conclusion: Auto segmentation and deformable propagation can generate OAR structures on HCT and CBCT images with clinically acceptable accuracy. Therefore

The IXV Ground Segment design, implementation and operations

Science.gov (United States)

Martucci di Scarfizzi, Giovanni; Bellomo, Alessandro; Musso, Ivano; Bussi, Diego; Rabaioli, Massimo; Santoro, Gianfranco; Billig, Gerhard; Gallego Sanz, José María

2016-07-01

The Intermediate eXperimental Vehicle (IXV) is an ESA re-entry demonstrator that performed, on the 11th February of 2015, a successful re-entry demonstration mission. The project objectives were the design, development, manufacturing and on ground and in flight verification of an autonomous European lifting and aerodynamically controlled re-entry system. For the IXV mission a dedicated Ground Segment was provided. The main subsystems of the IXV Ground Segment were: IXV Mission Control Center (MCC), from where monitoring of the vehicle was performed, as well as support during pre-launch and recovery phases; IXV Ground Stations, used to cover IXV mission by receiving spacecraft telemetry and forwarding it toward the MCC; the IXV Communication Network, deployed to support the operations of the IXV mission by interconnecting all remote sites with MCC, supporting data, voice and video exchange. This paper describes the concept, architecture, development, implementation and operations of the ESA Intermediate Experimental Vehicle (IXV) Ground Segment and outlines the main operations and lessons learned during the preparation and successful execution of the IXV Mission.

A System to Generate SignWriting for Video Tracks Enhancing Accessibility of Deaf People

Directory of Open Access Journals (Sweden)

Elena Verdú

2017-12-01

Full Text Available Video content has increased much on the Internet during last years. In spite of the efforts of different organizations and governments to increase the accessibility of websites, most multimedia content on the Internet is not accessible. This paper describes a system that contributes to make multimedia content more accessible on the Web, by automatically translating subtitles in oral language to SignWriting, a way of writing Sign Language. This system extends the functionality of a general web platform that can provide accessible web content for different needs. This platform has a core component that automatically converts any web page to a web page compliant with level AA of WAI guidelines. Around this core component, different adapters complete the conversion according to the needs of specific users. One adapter is the Deaf People Accessibility Adapter, which provides accessible web content for the Deaf, based on SignWritting. Functionality of this adapter has been extended with the video subtitle translator system. A first prototype of this system has been tested through different methods including usability and accessibility tests and results show that this tool can enhance the accessibility of video content available on the Web for Deaf people.

Acute Zonal Cone Photoreceptor Outer Segment Loss.

Science.gov (United States)

Aleman, Tomas S; Sandhu, Harpal S; Serrano, Leona W; Traband, Anastasia; Lau, Marisa K; Adamus, Grazyna; Avery, Robert A

2017-05-01

The diagnostic path presented narrows down the cause of acute vision loss to the cone photoreceptor outer segment and will refocus the search for the cause of similar currently idiopathic conditions. To describe the structural and functional associations found in a patient with acute zonal occult photoreceptor loss. A case report of an adolescent boy with acute visual field loss despite a normal fundus examination performed at a university teaching hospital. Results of a complete ophthalmic examination, full-field flash electroretinography (ERG) and multifocal ERG, light-adapted achromatic and 2-color dark-adapted perimetry, and microperimetry. Imaging was performed with spectral-domain optical coherence tomography (SD-OCT), near-infrared (NIR) and short-wavelength (SW) fundus autofluorescence (FAF), and NIR reflectance (REF). The patient was evaluated within a week of the onset of a scotoma in the nasal field of his left eye. Visual acuity was 20/20 OU, and color vision was normal in both eyes. Results of the fundus examination and of SW-FAF and NIR-FAF imaging were normal in both eyes, whereas NIR-REF imaging showed a region of hyporeflectance temporal to the fovea that corresponded with a dense relative scotoma noted on light-adapted static perimetry in the left eye. Loss in the photoreceptor outer segment detected by SD-OCT co-localized with an area of dense cone dysfunction detected on light-adapted perimetry and multifocal ERG but with near-normal rod-mediated vision according to results of 2-color dark-adapted perimetry. Full-field flash ERG findings were normal in both eyes. The outer nuclear layer and inner retinal thicknesses were normal. Localized, isolated cone dysfunction may represent the earliest photoreceptor abnormality or a distinct entity within the acute zonal occult outer retinopathy complex. Acute zonal occult outer retinopathy should be considered in patients with acute vision loss and abnormalities on NIR-REF imaging, especially if

Joint Optimization in UMTS-Based Video Transmission

Directory of Open Access Journals (Sweden)

Attila Zsiros

2007-01-01

Full Text Available A software platform is exposed, which was developed to enable demonstration and capacity testing. The platform simulates a joint optimized wireless video transmission. The development succeeded within the frame of the IST-PHOENIX project and is based on the system optimization model of the project. One of the constitutive parts of the model, the wireless network segment, is changed to a detailed, standard UTRA network simulation module. This paper consists of (1 a brief description of the projects simulation chain, (2 brief description of the UTRAN system, and (3 the integration of the two segments. The role of the UTRAN part in the joint optimization is described, with the configuration and control of this element. Finally, some simulation results are shown. In the conclusion, we show how our simulation results translate into real-world performance gains.

Segmentation and packaging reactor vessels internals

International Nuclear Information System (INIS)

Boucau, Joseph

2014-01-01

Document available in abstract form only, full text follows: With more than 25 years of experience in the development of reactor vessel internals and reactor vessel segmentation and packaging technology, Westinghouse has accumulated significant know-how in the reactor dismantling market. The primary challenges of a segmentation and packaging project are to separate the highly activated materials from the less-activated materials and package them into appropriate containers for disposal. Since disposal cost is a key factor, it is important to plan and optimize waste segmentation and packaging. The choice of the optimum cutting technology is also important for a successful project implementation and depends on some specific constraints. Detailed 3-D modeling is the basis for tooling design and provides invaluable support in determining the optimum strategy for component cutting and disposal in waste containers, taking account of the radiological and packaging constraints. The usual method is to start at the end of the process, by evaluating handling of the containers, the waste disposal requirements, what type and size of containers are available for the different disposal options, and working backwards to select a cutting method and finally the cut geometry required. The 3-D models can include intelligent data such as weight, center of gravity, curie content, etc, for each segmented piece, which is very useful when comparing various cutting, handling and packaging options. The detailed 3-D analyses and thorough characterization assessment can draw the attention to material potentially subject to clearance, either directly or after certain period of decay, to allow recycling and further disposal cost reduction. Westinghouse has developed a variety of special cutting and handling tools, support fixtures, service bridges, water filtration systems, video-monitoring systems and customized rigging, all of which are required for a successful reactor vessel internals

Video-feedback Intervention to promote Positive Parenting adapted to Autism (VIPP-AUTI): A randomized controlled trial.

Science.gov (United States)

Poslawsky, Irina E; Naber, Fabiënne Ba; Bakermans-Kranenburg, Marian J; van Daalen, Emma; van Engeland, Herman; van IJzendoorn, Marinus H

2015-07-01

In a randomized controlled trial, we evaluated the early intervention program Video-feedback Intervention to promote Positive Parenting adapted to Autism (VIPP-AUTI) with 78 primary caregivers and their child (16-61 months) with Autism Spectrum Disorder. VIPP-AUTI is a brief attachment-based intervention program, focusing on improving parent-child interaction and reducing the child's individual Autism Spectrum Disorder-related symptomatology in five home visits. VIPP-AUTI, as compared with usual care, demonstrated efficacy in reducing parental intrusiveness. Moreover, parents who received VIPP-AUTI showed increased feelings of self-efficacy in child rearing. No significant group differences were found on other aspects of parent-child interaction or on child play behavior. At 3-months follow-up, intervention effects were found on child-initiated joint attention skills, not mediated by intervention effects on parenting. Implementation of VIPP-AUTI in clinical practice is facilitated by the use of a detailed manual and a relatively brief training of interveners. © The Author(s) 2014.

Shot Boundary Detection in Soccer Video using Twin-comparison Algorithm and Dominant Color Region

Directory of Open Access Journals (Sweden)

Matko Šarić

2008-06-01

Full Text Available The first step in generic video processing is temporal segmentation, i.e. shot boundary detection. Camera shot transitions can be either abrupt (e.g. cuts or gradual (e.g. fades, dissolves, wipes. Sports video is one of the most challenging domains for robust shot boundary detection. We proposed a shot boundary detection algorithm for soccer video based on the twin-comparison method and the absolute difference between frames in their ratios of dominant colored pixels to total number of pixels. With this approach the detection of gradual transitions is improved by decreasing the number of false positives caused by some camera operations. We also compared performances of our algorithm and the standard twin-comparison method.

Mediastinoscopic Bilateral Bronchial Release for Long Segmental Resection and Anastomosis of the Trachea

OpenAIRE

Kang, Jeong-Han; Park, In Kyu; Bae, Mi-Kyung; Hwang, Yoohwa

2011-01-01

The extent of resection and release of the trachea is important for successful anastomosis. Bilateral bronchial dissection is one of the release techniques for resection of the lower trachea. We present the experience of cervical video-assisted mediastinoscopic bilateral bronchial release for long segmental resection and anastomosis of the lower trachea.

Improved people detection in nuclear plants by video processing for safety purpose

Energy Technology Data Exchange (ETDEWEB)

Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Carvalho, Paulo Victor R., E-mail: calexandre@ien.gov.br, E-mail: mol@ien.gov.br, E-mail: paulov@ien.gov.br [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil); Seixas, Jose M.; Silva, Eduardo Antonio B., E-mail: seixas@lps.ufrj.br, E-mail: eduardo@smt.ufrj.br [Coordenacao dos Programas de Pos-Graduacao em Engenharia (COPPE/UFRJ), RJ (Brazil). Programa de Engenharia Eletrica; Waintraub, Fabio, E-mail: fabiowaintraub@hotmail.com [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Escola Politecnica. Departamento de Engenharia Eletronica e de Computacao

2013-07-01

This work describes improvements in a surveillance system for safety purposes in nuclear plants. The objective is to track people online in video, in order to estimate the dose received by personnel, during working tasks executed in nuclear plants. The estimation will be based on their tracked positions and on dose rate mapping in a nuclear research reactor, Argonauta. Cameras have been installed within Argonauta room, supplying the data needed. Video processing methods were combined for detecting and tracking people in video. More specifically, segmentation, performed by background subtraction, was combined with a tracking method based on color distribution. The use of both methods improved the overall results. An alternative approach was also evaluated, by means of blind source signal separation. Results are commented, along with perspectives. (author)

Improved people detection in nuclear plants by video processing for safety purpose

International Nuclear Information System (INIS)

Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Carvalho, Paulo Victor R.; Seixas, Jose M.; Silva, Eduardo Antonio B.; Waintraub, Fabio

2013-01-01

This work describes improvements in a surveillance system for safety purposes in nuclear plants. The objective is to track people online in video, in order to estimate the dose received by personnel, during working tasks executed in nuclear plants. The estimation will be based on their tracked positions and on dose rate mapping in a nuclear research reactor, Argonauta. Cameras have been installed within Argonauta room, supplying the data needed. Video processing methods were combined for detecting and tracking people in video. More specifically, segmentation, performed by background subtraction, was combined with a tracking method based on color distribution. The use of both methods improved the overall results. An alternative approach was also evaluated, by means of blind source signal separation. Results are commented, along with perspectives. (author)

Multi-Class Simultaneous Adaptive Segmentation and Quality Control of Point Cloud Data

Directory of Open Access Journals (Sweden)

Ayman Habib

2016-01-01

Full Text Available 3D modeling of a given site is an important activity for a wide range of applications including urban planning, as-built mapping of industrial sites, heritage documentation, military simulation, and outdoor/indoor analysis of airflow. Point clouds, which could be either derived from passive or active imaging systems, are an important source for 3D modeling. Such point clouds need to undergo a sequence of data processing steps to derive the necessary information for the 3D modeling process. Segmentation is usually the first step in the data processing chain. This paper presents a region-growing multi-class simultaneous segmentation procedure, where planar, pole-like, and rough regions are identified while considering the internal characteristics (i.e., local point density/spacing and noise level of the point cloud in question. The segmentation starts with point cloud organization into a kd-tree data structure and characterization process to estimate the local point density/spacing. Then, proceeding from randomly-distributed seed points, a set of seed regions is derived through distance-based region growing, which is followed by modeling of such seed regions into planar and pole-like features. Starting from optimally-selected seed regions, planar and pole-like features are then segmented. The paper also introduces a list of hypothesized artifacts/problems that might take place during the region-growing process. Finally, a quality control process is devised to detect, quantify, and mitigate instances of partially/fully misclassified planar and pole-like features. Experimental results from airborne and terrestrial laser scanning as well as image-based point clouds are presented to illustrate the performance of the proposed segmentation and quality control framework.

Multi-Model Estimation Based Moving Object Detection for Aerial Video

Directory of Open Access Journals (Sweden)

Yanning Zhang

2015-04-01

Full Text Available With the wide development of UAV (Unmanned Aerial Vehicle technology, moving target detection for aerial video has become a popular research topic in the computer field. Most of the existing methods are under the registration-detection framework and can only deal with simple background scenes. They tend to go wrong in the complex multi background scenarios, such as viaducts, buildings and trees. In this paper, we break through the single background constraint and perceive the complex scene accurately by automatic estimation of multiple background models. First, we segment the scene into several color blocks and estimate the dense optical flow. Then, we calculate an affine transformation model for each block with large area and merge the consistent models. Finally, we calculate subordinate degree to multi-background models pixel to pixel for all small area blocks. Moving objects are segmented by means of energy optimization method solved via Graph Cuts. The extensive experimental results on public aerial videos show that, due to multi background models estimation, analyzing each pixel’s subordinate relationship to multi models by energy minimization, our method can effectively remove buildings, trees and other false alarms and detect moving objects correctly.

3D video coding: an overview of present and upcoming standards

Science.gov (United States)

Merkle, Philipp; Müller, Karsten; Wiegand, Thomas

2010-07-01

An overview of existing and upcoming 3D video coding standards is given. Various different 3D video formats are available, each with individual pros and cons. The 3D video formats can be separated into two classes: video-only formats (such as stereo and multiview video) and depth-enhanced formats (such as video plus depth and multiview video plus depth). Since all these formats exist of at least two video sequences and possibly additional depth data, efficient compression is essential for the success of 3D video applications and technologies. For the video-only formats the H.264 family of coding standards already provides efficient and widely established compression algorithms: H.264/AVC simulcast, H.264/AVC stereo SEI message, and H.264/MVC. For the depth-enhanced formats standardized coding algorithms are currently being developed. New and specially adapted coding approaches are necessary, as the depth or disparity information included in these formats has significantly different characteristics than video and is not displayed directly, but used for rendering. Motivated by evolving market needs, MPEG has started an activity to develop a generic 3D video standard within the 3DVC ad-hoc group. Key features of the standard are efficient and flexible compression of depth-enhanced 3D video representations and decoupling of content creation and display requirements.

Adaptive Motor Resistance Video Game Exercise Apparatus and Method of Use Thereof

Science.gov (United States)

Reich, Alton (Inventor); Shaw, James (Inventor)

2015-01-01

The invention comprises a method and/or an apparatus using computer configured exercise equipment and an electric motor provided physical resistance in conjunction with a game system, such as a video game system, where the exercise system provides real physical resistance to a user interface. Results of user interaction with the user interface are integrated into a video game, such as running on a game console. The resistance system comprises: a subject interface, software control, a controller, an electric servo assist/resist motor, an actuator, and/or a subject sensor. The system provides actual physical interaction with a resistance device as input to the game console and game run thereon.

Adaptive Stress Response in Segmental Progeria Resembles Long-Lived Dwarfism and Calorie Restriction in Mice

Science.gov (United States)

Holcomb, Valerie B; von Lindern, Marieke; Jong, Willeke M. C; Zeeuw, Chris I. De; Suh, Yousin; Hasty, Paul; Hoeijmakers, Jan H. J; van der Horst, Gijsbertus T. J; Mitchell, James R

2006-01-01

How congenital defects causing genome instability can result in the pleiotropic symptoms reminiscent of aging but in a segmental and accelerated fashion remains largely unknown. Most segmental progerias are associated with accelerated fibroblast senescence, suggesting that cellular senescence is a likely contributing mechanism. Contrary to expectations, neither accelerated senescence nor acute oxidative stress hypersensitivity was detected in primary fibroblast or erythroblast cultures from multiple progeroid mouse models for defects in the nucleotide excision DNA repair pathway, which share premature aging features including postnatal growth retardation, cerebellar ataxia, and death before weaning. Instead, we report a prominent phenotypic overlap with long-lived dwarfism and calorie restriction during postnatal development (2 wk of age), including reduced size, reduced body temperature, hypoglycemia, and perturbation of the growth hormone/insulin-like growth factor 1 neuroendocrine axis. These symptoms were also present at 2 wk of age in a novel progeroid nucleotide excision repair-deficient mouse model (XPDG602D/R722W/XPA−/−) that survived weaning with high penetrance. However, despite persistent cachectic dwarfism, blood glucose and serum insulin-like growth factor 1 levels returned to normal by 10 wk, with hypoglycemia reappearing near premature death at 5 mo of age. These data strongly suggest changes in energy metabolism as part of an adaptive response during the stressful period of postnatal growth. Interestingly, a similar perturbation of the postnatal growth axis was not detected in another progeroid mouse model, the double-strand DNA break repair deficient Ku80 −/− mouse. Specific (but not all) types of genome instability may thus engage a conserved response to stress that evolved to cope with environmental pressures such as food shortage. PMID:17173483

Adaptive stress response in segmental progeria resembles long-lived dwarfism and calorie restriction in mice.

Science.gov (United States)

van de Ven, Marieke; Andressoo, Jaan-Olle; Holcomb, Valerie B; von Lindern, Marieke; Jong, Willeke M C; De Zeeuw, Chris I; Suh, Yousin; Hasty, Paul; Hoeijmakers, Jan H J; van der Horst, Gijsbertus T J; Mitchell, James R

2006-12-15

How congenital defects causing genome instability can result in the pleiotropic symptoms reminiscent of aging but in a segmental and accelerated fashion remains largely unknown. Most segmental progerias are associated with accelerated fibroblast senescence, suggesting that cellular senescence is a likely contributing mechanism. Contrary to expectations, neither accelerated senescence nor acute oxidative stress hypersensitivity was detected in primary fibroblast or erythroblast cultures from multiple progeroid mouse models for defects in the nucleotide excision DNA repair pathway, which share premature aging features including postnatal growth retardation, cerebellar ataxia, and death before weaning. Instead, we report a prominent phenotypic overlap with long-lived dwarfism and calorie restriction during postnatal development (2 wk of age), including reduced size, reduced body temperature, hypoglycemia, and perturbation of the growth hormone/insulin-like growth factor 1 neuroendocrine axis. These symptoms were also present at 2 wk of age in a novel progeroid nucleotide excision repair-deficient mouse model (XPD(G602D/R722W)/XPA(-/-)) that survived weaning with high penetrance. However, despite persistent cachectic dwarfism, blood glucose and serum insulin-like growth factor 1 levels returned to normal by 10 wk, with hypoglycemia reappearing near premature death at 5 mo of age. These data strongly suggest changes in energy metabolism as part of an adaptive response during the stressful period of postnatal growth. Interestingly, a similar perturbation of the postnatal growth axis was not detected in another progeroid mouse model, the double-strand DNA break repair deficient Ku80(-/-) mouse. Specific (but not all) types of genome instability may thus engage a conserved response to stress that evolved to cope with environmental pressures such as food shortage.

Adaptive stress response in segmental progeria resembles long-lived dwarfism and calorie restriction in mice.

Directory of Open Access Journals (Sweden)

Marieke van de Ven

2006-12-01

Full Text Available How congenital defects causing genome instability can result in the pleiotropic symptoms reminiscent of aging but in a segmental and accelerated fashion remains largely unknown. Most segmental progerias are associated with accelerated fibroblast senescence, suggesting that cellular senescence is a likely contributing mechanism. Contrary to expectations, neither accelerated senescence nor acute oxidative stress hypersensitivity was detected in primary fibroblast or erythroblast cultures from multiple progeroid mouse models for defects in the nucleotide excision DNA repair pathway, which share premature aging features including postnatal growth retardation, cerebellar ataxia, and death before weaning. Instead, we report a prominent phenotypic overlap with long-lived dwarfism and calorie restriction during postnatal development (2 wk of age, including reduced size, reduced body temperature, hypoglycemia, and perturbation of the growth hormone/insulin-like growth factor 1 neuroendocrine axis. These symptoms were also present at 2 wk of age in a novel progeroid nucleotide excision repair-deficient mouse model (XPD(G602D/R722W/XPA(-/- that survived weaning with high penetrance. However, despite persistent cachectic dwarfism, blood glucose and serum insulin-like growth factor 1 levels returned to normal by 10 wk, with hypoglycemia reappearing near premature death at 5 mo of age. These data strongly suggest changes in energy metabolism as part of an adaptive response during the stressful period of postnatal growth. Interestingly, a similar perturbation of the postnatal growth axis was not detected in another progeroid mouse model, the double-strand DNA break repair deficient Ku80(-/- mouse. Specific (but not all types of genome instability may thus engage a conserved response to stress that evolved to cope with environmental pressures such as food shortage.

Two Variations of Video Modeling Interventions for Teaching Play Skills to Children with Autism

Science.gov (United States)

Sancho, Kimberly; Sidener, Tina M.; Reeve, Sharon A.; Sidener, David W.

2010-01-01

The current study employed an adapted alternating treatments design with reversal and multiple probe across participants components to compare the effects of traditional video priming and simultaneous video modeling on the acquisition of play skills in two children diagnosed with autism. Generalization was programmed across play sets, instructors,…

Distributed coding/decoding complexity in video sensor networks.

Science.gov (United States)

Cordeiro, Paulo J; Assunção, Pedro

2012-01-01

Video Sensor Networks (VSNs) are recent communication infrastructures used to capture and transmit dense visual information from an application context. In such large scale environments which include video coding, transmission and display/storage, there are several open problems to overcome in practical implementations. This paper addresses the most relevant challenges posed by VSNs, namely stringent bandwidth usage and processing time/power constraints. In particular, the paper proposes a novel VSN architecture where large sets of visual sensors with embedded processors are used for compression and transmission of coded streams to gateways, which in turn transrate the incoming streams and adapt them to the variable complexity requirements of both the sensor encoders and end-user decoder terminals. Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate. Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted. The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality.

Multidimensional Brain MRI segmentation using graph cuts

International Nuclear Information System (INIS)

Lecoeur, Jeremy

2010-01-01

This thesis deals with the segmentation of multimodal brain MRIs by graph cuts method. First, we propose a method that utilizes three MRI modalities by merging them. The border information given by the spectral gradient is then challenged by a region information, given by the seeds selected by the user, using a graph cut algorithm. Then, we propose three enhancements of this method. The first consists in finding an optimal spectral space because the spectral gradient is based on natural images and then inadequate for multimodal medical images. This results in a learning based segmentation method. We then explore the automation of the graph cut method. Here, the various pieces of information usually given by the user are inferred from a robust expectation-maximization algorithm. We show the performance of these two enhanced versions on multiple sclerosis lesions. Finally, we integrate atlases for the automatic segmentation of deep brain structures. These three new techniques show the adaptability of our method to various problems. Our different segmentation methods are better than most of nowadays techniques, speaking of computation time or segmentation accuracy. (authors)

A Video Game-Based Framework for Analyzing Human-Robot Interaction: Characterizing Interface Design in Real-Time Interactive Multimedia Applications

National Research Council Canada - National Science Library

Richer, Justin; Drury, Jill L

2006-01-01

.... This paper segments video game interaction into domain-independent components which together form a framework that can be used to characterize real-time interactive multimedia applications in general...

Energy intake adaptations to acute isoenergetic active video games and exercise are similar in obese adolescents.

Science.gov (United States)

Chaput, J P; Schwartz, C; Boirie, Y; Duclos, M; Tremblay, A; Thivel, D

2015-11-01

Although the impact of passive video games (PVGs) on energy intake has been previously explored in lean adolescents, data are missing on the nutritional adaptations to passive and active video games (AVGs) in obese adolescents. It is also unknown whether isoenergetic AVGs and exercise (EX) differently affect food consumption in youth. Nineteen obese adolescent boys (12-15 years old) had to complete four 1-hour sessions in a crossover manner: control (CON; sitting on a chair), PVG (boxing game on Xbox 360), AVG (boxing game on Xbox Kinect 360) and EX (cycling). The EX was calibrated to generate the same energy expenditure as the AVG session. Energy expenditure was measured using a K4b2 portable indirect calorimeter. Ad libitum food intake (buffet-style meal) and appetite sensations (visual analogue scales) were assessed after the sessions. As expected, mean energy expenditure was similar between AVG (370±4 kcal) and EX (358±3 kcal), both of which were significantly higher than PVG (125±7 kcal) and CON (98±5 kcal) (P<0.001). However, ad libitum food intake after the sessions was not significantly different between CON (1174±282 kcal), PVG (1124±281 kcal), AVG (1098±265 kcal) and EX (1091±290 kcal). Likewise, the energy derived from fat, carbohydrate and protein was not significantly different between sessions, and appetite sensations were not affected. Energy intake and food preferences after an hour of AVG or PVG playing remain unchanged, and isoenergetic sessions of AVG and EX at moderate intensity induce similar nutritional responses in obese adolescent boys.

Energy Adaption for Multimedia Information Kiosks

DEFF Research Database (Denmark)

Urunuela, Richard; Muller, Gilles; Lawall, Julia Laetitia

2006-01-01

Video kiosks increasingly contain powerful PC-like embedded processors, allowing them to display video at a high level of quality. Such video display, however, entails significant energy consumption.This paper presents an approach to reducing energy consumption by adapting the CPU clock frequency....... In contrast to previous approaches, we exploit the specific behavior of a video kiosk. Because a kiosk plays the same set of movies over and over, we choose a CPU frequency for a given frame based on the computational requirements of the frame that were observed on earlier iterations. We have implemented our...... approach in the legacy video player MPlayer. On a PC like those that can be found in kiosks, we observe increases in battery lifetime of up to 2 times as compared to running at the maximum CPU frequency on a set of high resolution divx movies....

Potential for La Crosse virus segment reassortment in nature

Directory of Open Access Journals (Sweden)

Geske Dave

2008-12-01

Full Text Available Abstract The evolutionary success of La Crosse virus (LACV, family Bunyaviridae is due to its ability to adapt to changing conditions through intramolecular genetic changes and segment reassortment. Vertical transmission of LACV in mosquitoes increases the potential for segment reassortment. Studies were conducted to determine if segment reassortment was occurring in naturally infected Aedes triseriatus from Wisconsin and Minnesota in 2000, 2004, 2006 and 2007. Mosquito eggs were collected from various sites in Wisconsin and Minnesota. They were reared in the laboratory and adults were tested for LACV antigen by immunofluorescence assay. RNA was isolated from the abdomen of infected mosquitoes and portions of the small (S, medium (M and large (L viral genome segments were amplified by RT-PCR and sequenced. Overall, the viral sequences from 40 infected mosquitoes and 5 virus isolates were analyzed. Phylogenetic and linkage disequilibrium analyses revealed that approximately 25% of infected mosquitoes and viruses contained reassorted genome segments, suggesting that LACV segment reassortment is frequent in nature.

Learning a Continuous-Time Streaming Video QoE Model.

Science.gov (United States)

Ghadiyaram, Deepti; Pan, Janice; Bovik, Alan C

2018-05-01

Over-the-top adaptive video streaming services are frequently impacted by fluctuating network conditions that can lead to rebuffering events (stalling events) and sudden bitrate changes. These events visually impact video consumers' quality of experience (QoE) and can lead to consumer churn. The development of models that can accurately predict viewers' instantaneous subjective QoE under such volatile network conditions could potentially enable the more efficient design of quality-control protocols for media-driven services, such as YouTube, Amazon, Netflix, and so on. However, most existing models only predict a single overall QoE score on a given video and are based on simple global video features, without accounting for relevant aspects of human perception and behavior. We have created a QoE evaluator, called the time-varying QoE Indexer, that accounts for interactions between stalling events, analyzes the spatial and temporal content of a video, predicts the perceptual video quality, models the state of the client-side data buffer, and consequently predicts continuous-time quality scores that agree quite well with human opinion scores. The new QoE predictor also embeds the impact of relevant human cognitive factors, such as memory and recency, and their complex interactions with the video content being viewed. We evaluated the proposed model on three different video databases and attained standout QoE prediction performance.

Inference of segmented color and texture description by tensor voting.

Science.gov (United States)

Jia, Jiaya; Tang, Chi-Keung

2004-06-01

A robust synthesis method is proposed to automatically infer missing color and texture information from a damaged 2D image by (N)D tensor voting (N > 3). The same approach is generalized to range and 3D data in the presence of occlusion, missing data and noise. Our method translates texture information into an adaptive (N)D tensor, followed by a voting process that infers noniteratively the optimal color values in the (N)D texture space. A two-step method is proposed. First, we perform segmentation based on insufficient geometry, color, and texture information in the input, and extrapolate partitioning boundaries by either 2D or 3D tensor voting to generate a complete segmentation for the input. Missing colors are synthesized using (N)D tensor voting in each segment. Different feature scales in the input are automatically adapted by our tensor scale analysis. Results on a variety of difficult inputs demonstrate the effectiveness of our tensor voting approach.

Leveraging Automatic Speech Recognition Errors to Detect Challenging Speech Segments in TED Talks

Science.gov (United States)

Mirzaei, Maryam Sadat; Meshgi, Kourosh; Kawahara, Tatsuya

2016-01-01

This study investigates the use of Automatic Speech Recognition (ASR) systems to epitomize second language (L2) listeners' problems in perception of TED talks. ASR-generated transcripts of videos often involve recognition errors, which may indicate difficult segments for L2 listeners. This paper aims to discover the root-causes of the ASR errors…

Video Browsing on Handheld Devices

Science.gov (United States)

Hürst, Wolfgang

Recent improvements in processing power, storage space, and video codec development enable users now to playback video on their handheld devices in a reasonable quality. However, given the form factor restrictions of such a mobile device, screen size still remains a natural limit and - as the term "handheld" implies - always will be a critical resource. This is not only true for video but any data that is processed on such devices. For this reason, developers have come up with new and innovative ways to deal with large documents in such limited scenarios. For example, if you look at the iPhone, innovative techniques such as flicking have been introduced to skim large lists of text (e.g. hundreds of entries in your music collection). Automatically adapting the zoom level to, for example, the width of table cells when double tapping on the screen enables reasonable browsing of web pages that have originally been designed for large, desktop PC sized screens. A multi touch interface allows you to easily zoom in and out of large text documents and images using two fingers. In the next section, we will illustrate that advanced techniques to browse large video files have been developed in the past years, as well. However, if you look at state-of-the-art video players on mobile devices, normally just simple, VCR like controls are supported (at least at the time of this writing) that only allow users to just start, stop, and pause video playback. If supported at all, browsing and navigation functionality is often restricted to simple skipping of chapters via two single buttons for backward and forward navigation and a small and thus not very sensitive timeline slider.

Facial expression system on video using widrow hoff

Science.gov (United States)

Jannah, M.; Zarlis, M.; Mawengkang, H.

2018-03-01

Facial expressions recognition is one of interesting research. This research contains human feeling to computer application Such as the interaction between human and computer, data compression, facial animation and facial detection from the video. The purpose of this research is to create facial expression system that captures image from the video camera. The system in this research uses Widrow-Hoff learning method in training and testing image with Adaptive Linear Neuron (ADALINE) approach. The system performance is evaluated by two parameters, detection rate and false positive rate. The system accuracy depends on good technique and face position that trained and tested.

Detection of Upscale-Crop and Partial Manipulation in Surveillance Video Based on Sensor Pattern Noise

Science.gov (United States)

Hyun, Dai-Kyung; Ryu, Seung-Jin; Lee, Hae-Yeoun; Lee, Heung-Kyu

2013-01-01

In many court cases, surveillance videos are used as significant court evidence. As these surveillance videos can easily be forged, it may cause serious social issues, such as convicting an innocent person. Nevertheless, there is little research being done on forgery of surveillance videos. This paper proposes a forensic technique to detect forgeries of surveillance video based on sensor pattern noise (SPN). We exploit the scaling invariance of the minimum average correlation energy Mellin radial harmonic (MACE-MRH) correlation filter to reliably unveil traces of upscaling in videos. By excluding the high-frequency components of the investigated video and adaptively choosing the size of the local search window, the proposed method effectively localizes partially manipulated regions. Empirical evidence from a large database of test videos, including RGB (Red, Green, Blue)/infrared video, dynamic-/static-scene video and compressed video, indicates the superior performance of the proposed method. PMID:24051524

Development of a video-delivered relaxation treatment of late-life anxiety for veterans.

Science.gov (United States)

Gould, Christine E; Zapata, Aimee Marie L; Bruce, Janine; Bereknyei Merrell, Sylvia; Wetherell, Julie Loebach; O'Hara, Ruth; Kuhn, Eric; Goldstein, Mary K; Beaudreau, Sherry A

2017-10-01

Behavioral treatments reduce anxiety, yet many older adults may not have access to these efficacious treatments. To address this need, we developed and evaluated the feasibility and acceptability of a video-delivered anxiety treatment for older Veterans. This treatment program, BREATHE (Breathing, Relaxation, and Education for Anxiety Treatment in the Home Environment), combines psychoeducation, diaphragmatic breathing, and progressive muscle relaxation training with engagement in activities. A mixed methods concurrent study design was used to examine the clarity of the treatment videos. We conducted semi-structured interviews with 20 Veterans (M age = 69.5, SD = 7.3 years; 55% White, Non-Hispanic) and collected ratings of video clarity. Quantitative ratings revealed that 100% of participants generally or definitely could follow breathing and relaxation video instructions. Qualitative findings, however, demonstrated more variability in the extent to which each video segment was clear. Participants identified both immediate benefits and motivation challenges associated with a video-delivered treatment. Participants suggested that some patients may need encouragement, whereas others need face-to-face therapy. Quantitative ratings of video clarity and qualitative findings highlight the feasibility of a video-delivered treatment for older Veterans with anxiety. Our findings demonstrate the importance of ensuring patients can follow instructions provided in self-directed treatments and the role that an iterative testing process has in addressing these issues. Next steps include testing the treatment videos with older Veterans with anxiety disorders.

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 negative association between video game experience and proactive cognitive control.

Science.gov (United States)

Bailey, Kira; West, Robert; Anderson, Craig A

2010-01-01

Some evidence demonstrates that video game experience has a beneficial effect on visuospatial cognition. In contrast, other evidence indicates that video game experience may be negatively related to cognitive control. In this study we examined the specificity of the influence of video game experience on cognitive control. Participants with high and low video game experience performed the Stroop task while event-related brain potentials were recorded. The behavioral data revealed no difference between high and low gamers for the Stroop interference effect and a reduction in the conflict adaptation effect in high gamers. The amplitude of the medial frontal negativity and a frontal slow wave was attenuated in high gamers, and there was no effect of gaming status on the conflict slow potential. These data lead to the suggestion that video game experience has a negative influence on proactive, but not reactive, cognitive control.

Computer simulation of orthognathic surgery with video imaging

Science.gov (United States)

Sader, Robert; Zeilhofer, Hans-Florian U.; Horch, Hans-Henning

1994-04-01

Patients with extreme jaw imbalance must often undergo operative corrections. The goal of therapy is to harmonize the stomatognathic system and an aesthetical correction of the face profile. A new procedure will be presented which supports the maxillo-facial surgeon in planning the operation and which also presents the patient the result of the treatment by video images. Once an x-ray has been digitized it is possible to produce individualized cephalometric analyses. Using a ceph on screen, all current orthognathic operations can be simulated, whereby the bony segments are moved according to given parameters, and a new soft tissue profile can be calculated. The profile of the patient is fed into the computer by way of a video system and correlated to the ceph. Using the simulated operation the computer calculates a new video image of the patient which presents the expected postoperative appearance. In studies of patients treated between 1987-91, 76 out of 121 patients were able to be evaluated. The deviation in profile change varied between .0 and 1.6mm. A side effect of the practical applications was an increase in patient compliance.

Comparison of Video and Live Modeling in Teaching Response Chains to Children with Autism

Science.gov (United States)

Ergenekon, Yasemin; Tekin-Iftar, Elif; Kapan, Alper; Akmanoglu, Nurgul

2014-01-01

Research has shown that video and live modeling are both effective in teaching new skills to children with autism. An adapted alternating treatments design was used to compare the effectiveness and efficiency of video and live modeling in teaching response chains to three children with autism. Each child was taught two chained skills; one skill…

Assessment of YouTube videos as a source of information on medication use in pregnancy.

Science.gov (United States)

Hansen, Craig; Interrante, Julia D; Ailes, Elizabeth C; Frey, Meghan T; Broussard, Cheryl S; Godoshian, Valerie J; Lewis, Courtney; Polen, Kara N D; Garcia, Amanda P; Gilboa, Suzanne M

2016-01-01

When making decisions about medication use in pregnancy, women consult many information sources, including the Internet. The aim of this study was to assess the content of publicly accessible YouTube videos that discuss medication use in pregnancy. Using 2023 distinct combinations of search terms related to medications and pregnancy, we extracted metadata from YouTube videos using a YouTube video Application Programming Interface. Relevant videos were defined as those with a medication search term and a pregnancy-related search term in either the video title or description. We viewed relevant videos and abstracted content from each video into a database. We documented whether videos implied each medication to be "safe" or "unsafe" in pregnancy and compared that assessment with the medication's Teratogen Information System (TERIS) rating. After viewing 651 videos, 314 videos with information about medication use in pregnancy were available for the final analyses. The majority of videos were from law firms (67%), television segments (10%), or physicians (8%). Selective serotonin reuptake inhibitors (SSRIs) were the most common medication class named (225 videos, 72%), and 88% of videos about SSRIs indicated that they were unsafe for use in pregnancy. However, the TERIS ratings for medication products in this class range from "unlikely" to "minimal" teratogenic risk. For the majority of medications, current YouTube video content does not adequately reflect what is known about the safety of their use in pregnancy and should be interpreted cautiously. However, YouTube could serve as a platform for communicating evidence-based medication safety information. Copyright © 2015 John Wiley & Sons, Ltd.

Hyperspectral image segmentation using a cooperative nonparametric approach

Science.gov (United States)

Taher, Akar; Chehdi, Kacem; Cariou, Claude

2013-10-01

In this paper a new unsupervised nonparametric cooperative and adaptive hyperspectral image segmentation approach is presented. The hyperspectral images are partitioned band by band in parallel and intermediate classification results are evaluated and fused, to get the final segmentation result. Two unsupervised nonparametric segmentation methods are used in parallel cooperation, namely the Fuzzy C-means (FCM) method, and the Linde-Buzo-Gray (LBG) algorithm, to segment each band of the image. The originality of the approach relies firstly on its local adaptation to the type of regions in an image (textured, non-textured), and secondly on the introduction of several levels of evaluation and validation of intermediate segmentation results before obtaining the final partitioning of the image. For the management of similar or conflicting results issued from the two classification methods, we gradually introduced various assessment steps that exploit the information of each spectral band and its adjacent bands, and finally the information of all the spectral bands. In our approach, the detected textured and non-textured regions are treated separately from feature extraction step, up to the final classification results. This approach was first evaluated on a large number of monocomponent images constructed from the Brodatz album. Then it was evaluated on two real applications using a respectively multispectral image for Cedar trees detection in the region of Baabdat (Lebanon) and a hyperspectral image for identification of invasive and non invasive vegetation in the region of Cieza (Spain). A correct classification rate (CCR) for the first application is over 97% and for the second application the average correct classification rate (ACCR) is over 99%.

Segmentation of 3-D High-Frequency Ultrasound Images of Human Lymph Nodes Using Graph Cut With Energy Functional Adapted to Local Intensity Distribution.

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Kuo, Jen-Wei; Mamou, Jonathan; Wang, Yao; Saegusa-Beecroft, Emi; Machi, Junji; Feleppa, Ernest J

2017-10-01

Previous studies by our group have shown that 3-D high-frequency quantitative ultrasound (QUS) methods have the potential to differentiate metastatic lymph nodes (LNs) from cancer-free LNs dissected from human cancer patients. To successfully perform these methods inside the LN parenchyma (LNP), an automatic segmentation method is highly desired to exclude the surrounding thin layer of fat from QUS processing and accurately correct for ultrasound attenuation. In high-frequency ultrasound images of LNs, the intensity distribution of LNP and fat varies spatially because of acoustic attenuation and focusing effects. Thus, the intensity contrast between two object regions (e.g., LNP and fat) is also spatially varying. In our previous work, nested graph cut (GC) demonstrated its ability to simultaneously segment LNP, fat, and the outer phosphate-buffered saline bath even when some boundaries are lost because of acoustic attenuation and focusing effects. This paper describes a novel approach called GC with locally adaptive energy to further deal with spatially varying distributions of LNP and fat caused by inhomogeneous acoustic attenuation. The proposed method achieved Dice similarity coefficients of 0.937±0.035 when compared with expert manual segmentation on a representative data set consisting of 115 3-D LN images obtained from colorectal cancer patients.

Moving object detection in video satellite image based on deep learning

Science.gov (United States)

Zhang, Xueyang; Xiang, Junhua

2017-11-01

Moving object detection in video satellite image is studied. A detection algorithm based on deep learning is proposed. The small scale characteristics of remote sensing video objects are analyzed. Firstly, background subtraction algorithm of adaptive Gauss mixture model is used to generate region proposals. Then the objects in region proposals are classified via the deep convolutional neural network. Thus moving objects of interest are detected combined with prior information of sub-satellite point. The deep convolution neural network employs a 21-layer residual convolutional neural network, and trains the network parameters by transfer learning. Experimental results about video from Tiantuo-2 satellite demonstrate the effectiveness of the algorithm.

Dynamic Textures Modeling via Joint Video Dictionary Learning.

Science.gov (United States)

Wei, Xian; Li, Yuanxiang; Shen, Hao; Chen, Fang; Kleinsteuber, Martin; Wang, Zhongfeng

2017-04-06

Video representation is an important and challenging task in the computer vision community. In this paper, we consider the problem of modeling and classifying video sequences of dynamic scenes which could be modeled in a dynamic textures (DT) framework. At first, we assume that image frames of a moving scene can be modeled as a Markov random process. We propose a sparse coding framework, named joint video dictionary learning (JVDL), to model a video adaptively. By treating the sparse coefficients of image frames over a learned dictionary as the underlying "states", we learn an efficient and robust linear transition matrix between two adjacent frames of sparse events in time series. Hence, a dynamic scene sequence is represented by an appropriate transition matrix associated with a dictionary. In order to ensure the stability of JVDL, we impose several constraints on such transition matrix and dictionary. The developed framework is able to capture the dynamics of a moving scene by exploring both sparse properties and the temporal correlations of consecutive video frames. Moreover, such learned JVDL parameters can be used for various DT applications, such as DT synthesis and recognition. Experimental results demonstrate the strong competitiveness of the proposed JVDL approach in comparison with state-of-the-art video representation methods. Especially, it performs significantly better in dealing with DT synthesis and recognition on heavily corrupted data.

Incremental principal component pursuit for video background modeling

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Rodriquez-Valderrama, Paul A.; Wohlberg, Brendt

2017-03-14

An incremental Principal Component Pursuit (PCP) algorithm for video background modeling that is able to process one frame at a time while adapting to changes in background, with a computational complexity that allows for real-time processing, having a low memory footprint and is robust to translational and rotational jitter.

Dynamic Difficulty Adaptation for Heterogeneously Skilled Player Groups in Multiplayer Collaborative Games

OpenAIRE

Greciano, Miguel Cristian

2016-01-01

This work focuses on the combination of two key concepts: Dynamic Difficulty Adjustment/Adaptation (video games adapting their difficulty according to the in-game performance of players, making themselves easier if the player performs poorly or more difficult if the player performs well) and Collaborative Multiplayer Games (video games where two or more human players work together to achieve a common goal). It considers and analyzes the challenges, potential and possibilities of Dynamic Diffi...

Real-time high-level video understanding using data warehouse

Science.gov (United States)

Lienard, Bruno; Desurmont, Xavier; Barrie, Bertrand; Delaigle, Jean-Francois

2006-02-01

High-level Video content analysis such as video-surveillance is often limited by computational aspects of automatic image understanding, i.e. it requires huge computing resources for reasoning processes like categorization and huge amount of data to represent knowledge of objects, scenarios and other models. This article explains how to design and develop a "near real-time adaptive image datamart", used, as a decisional support system for vision algorithms, and then as a mass storage system. Using RDF specification as storing format of vision algorithms meta-data, we can optimise the data warehouse concepts for video analysis, add some processes able to adapt the current model and pre-process data to speed-up queries. In this way, when new data is sent from a sensor to the data warehouse for long term storage, using remote procedure call embedded in object-oriented interfaces to simplified queries, they are processed and in memory data-model is updated. After some processing, possible interpretations of this data can be returned back to the sensor. To demonstrate this new approach, we will present typical scenarios applied to this architecture such as people tracking and events detection in a multi-camera network. Finally we will show how this system becomes a high-semantic data container for external data-mining.

The Development of Videos in Culturally Grounded Drug Prevention for Rural Native Hawaiian Youth

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Okamoto, Scott K.; Helm, Susana; McClain, Latoya L.; Dinson, Ay-Laina

2012-01-01

The purpose of this study was to adapt and validate narrative scripts to be used for the video components of a culturally grounded drug prevention program for rural Native Hawaiian youth. Scripts to be used to film short video vignettes of drug-related problem situations were developed based on a foundation of pre-prevention research funded by the…

VideoSET: Video Summary Evaluation through Text

OpenAIRE

Yeung, Serena; Fathi, Alireza; Fei-Fei, Li

2014-01-01

In this paper we present VideoSET, a method for Video Summary Evaluation through Text that can evaluate how well a video summary is able to retain the semantic information contained in its original video. We observe that semantics is most easily expressed in words, and develop a text-based approach for the evaluation. Given a video summary, a text representation of the video summary is first generated, and an NLP-based metric is then used to measure its semantic distance to ground-truth text ...

A generic flexible and robust approach for intelligent real-time video-surveillance systems

Science.gov (United States)

Desurmont, Xavier; Delaigle, Jean-Francois; Bastide, Arnaud; Macq, Benoit

2004-05-01

In this article we present a generic, flexible and robust approach for an intelligent real-time video-surveillance system. A previous version of the system was presented in [1]. The goal of these advanced tools is to provide help to operators by detecting events of interest in visual scenes and highlighting alarms and compute statistics. The proposed system is a multi-camera platform able to handle different standards of video inputs (composite, IP, IEEE1394 ) and which can basically compress (MPEG4), store and display them. This platform also integrates advanced video analysis tools, such as motion detection, segmentation, tracking and interpretation. The design of the architecture is optimised to playback, display, and process video flows in an efficient way for video-surveillance application. The implementation is distributed on a scalable computer cluster based on Linux and IP network. It relies on POSIX threads for multitasking scheduling. Data flows are transmitted between the different modules using multicast technology and under control of a TCP-based command network (e.g. for bandwidth occupation control). We report here some results and we show the potential use of such a flexible system in third generation video surveillance system. We illustrate the interest of the system in a real case study, which is the indoor surveillance.

Boundary fitting based segmentation of fluorescence microscopy images

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Lee, Soonam; Salama, Paul; Dunn, Kenneth W.; Delp, Edward J.

2015-03-01

Segmentation is a fundamental step in quantifying characteristics, such as volume, shape, and orientation of cells and/or tissue. However, quantification of these characteristics still poses a challenge due to the unique properties of microscopy volumes. This paper proposes a 2D segmentation method that utilizes a combination of adaptive and global thresholding, potentials, z direction refinement, branch pruning, end point matching, and boundary fitting methods to delineate tubular objects in microscopy volumes. Experimental results demonstrate that the proposed method achieves better performance than an active contours based scheme.

Video event classification and image segmentation based on noncausal multidimensional hidden Markov models.

Science.gov (United States)

Ma, Xiang; Schonfeld, Dan; Khokhar, Ashfaq A

2009-06-01

In this paper, we propose a novel solution to an arbitrary noncausal, multidimensional hidden Markov model (HMM) for image and video classification. First, we show that the noncausal model can be solved by splitting it into multiple causal HMMs and simultaneously solving each causal HMM using a fully synchronous distributed computing framework, therefore referred to as distributed HMMs. Next we present an approximate solution to the multiple causal HMMs that is based on an alternating updating scheme and assumes a realistic sequential computing framework. The parameters of the distributed causal HMMs are estimated by extending the classical 1-D training and classification algorithms to multiple dimensions. The proposed extension to arbitrary causal, multidimensional HMMs allows state transitions that are dependent on all causal neighbors. We, thus, extend three fundamental algorithms to multidimensional causal systems, i.e., 1) expectation-maximization (EM), 2) general forward-backward (GFB), and 3) Viterbi algorithms. In the simulations, we choose to limit ourselves to a noncausal 2-D model whose noncausality is along a single dimension, in order to significantly reduce the computational complexity. Simulation results demonstrate the superior performance, higher accuracy rate, and applicability of the proposed noncausal HMM framework to image and video classification.

Evaluation on the use of animated narrative video in teaching narrative text

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Soe’oed Rahmat

2018-01-01

Full Text Available In the 21st century, our life is strongly affected by the information technology. Educational technology has been rapidly improved by the development of audiovisual tools. Teachers may choose a number of different types of resources for teaching purposes, including videos and movies. Therefore, this study is aimed at evaluating animated narrative videos from YouTube for the teaching narrative text and identifying potential factors which influence the quality of educational videos. The videos were examined by using assessment rubric to see the quality and suitability of animated narrative videos which might be used in the teaching narrative text. The rubric was adapted from Prince Edward Island (PEI Department of Education: Evaluation and Selection of Learning Resources. It consists of four criteria, content, structure, instructional design, and technical design In addition, the study presents critical awareness of how these aspects can be interpreted to measure animated narrative videos and at the same time the engagement of the teachers in exploring animated narrative videos used in classroom.

Multiresolution Motion Estimation for Low-Rate Video Frame Interpolation

Directory of Open Access Journals (Sweden)

Hezerul Abdul Karim

2004-09-01

Full Text Available Interpolation of video frames with the purpose of increasing the frame rate requires the estimation of motion in the image so as to interpolate pixels along the path of the objects. In this paper, the specific challenges of low-rate video frame interpolation are illustrated by choosing one well-performing algorithm for high-frame-rate interpolation (Castango 1996 and applying it to low frame rates. The degradation of performance is illustrated by comparing the original algorithm, the algorithm adapted to low frame rate, and simple averaging. To overcome the particular challenges of low-frame-rate interpolation, two algorithms based on multiresolution motion estimation are developed and compared on objective and subjective basis and shown to provide an elegant solution to the specific challenges of low-frame-rate video interpolation.

Comparative Study of Retinal Vessel Segmentation Based on Global Thresholding Techniques

Directory of Open Access Journals (Sweden)

Temitope Mapayi

2015-01-01

Full Text Available Due to noise from uneven contrast and illumination during acquisition process of retinal fundus images, the use of efficient preprocessing techniques is highly desirable to produce good retinal vessel segmentation results. This paper develops and compares the performance of different vessel segmentation techniques based on global thresholding using phase congruency and contrast limited adaptive histogram equalization (CLAHE for the preprocessing of the retinal images. The results obtained show that the combination of preprocessing technique, global thresholding, and postprocessing techniques must be carefully chosen to achieve a good segmentation performance.

Active mask segmentation of fluorescence microscope images.

Science.gov (United States)

Srinivasa, Gowri; Fickus, Matthew C; Guo, Yusong; Linstedt, Adam D; Kovacević, Jelena

2009-08-01

We propose a new active mask algorithm for the segmentation of fluorescence microscope images of punctate patterns. It combines the (a) flexibility offered by active-contour methods, (b) speed offered by multiresolution methods, (c) smoothing offered by multiscale methods, and (d) statistical modeling offered by region-growing methods into a fast and accurate segmentation tool. The framework moves from the idea of the "contour" to that of "inside and outside," or masks, allowing for easy multidimensional segmentation. It adapts to the topology of the image through the use of multiple masks. The algorithm is almost invariant under initialization, allowing for random initialization, and uses a few easily tunable parameters. Experiments show that the active mask algorithm matches the ground truth well and outperforms the algorithm widely used in fluorescence microscopy, seeded watershed, both qualitatively, as well as quantitatively.

JPEG2000-Compatible Scalable Scheme for Wavelet-Based Video Coding

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Thomas André

2007-03-01

Full Text Available We present a simple yet efficient scalable scheme for wavelet-based video coders, able to provide on-demand spatial, temporal, and SNR scalability, and fully compatible with the still-image coding standard JPEG2000. Whereas hybrid video coders must undergo significant changes in order to support scalability, our coder only requires a specific wavelet filter for temporal analysis, as well as an adapted bit allocation procedure based on models of rate-distortion curves. Our study shows that scalably encoded sequences have the same or almost the same quality than nonscalably encoded ones, without a significant increase in complexity. A full compatibility with Motion JPEG2000, which tends to be a serious candidate for the compression of high-definition video sequences, is ensured.

JPEG2000-Compatible Scalable Scheme for Wavelet-Based Video Coding

Directory of Open Access Journals (Sweden)

André Thomas

2007-01-01

Full Text Available We present a simple yet efficient scalable scheme for wavelet-based video coders, able to provide on-demand spatial, temporal, and SNR scalability, and fully compatible with the still-image coding standard JPEG2000. Whereas hybrid video coders must undergo significant changes in order to support scalability, our coder only requires a specific wavelet filter for temporal analysis, as well as an adapted bit allocation procedure based on models of rate-distortion curves. Our study shows that scalably encoded sequences have the same or almost the same quality than nonscalably encoded ones, without a significant increase in complexity. A full compatibility with Motion JPEG2000, which tends to be a serious candidate for the compression of high-definition video sequences, is ensured.

Virtual Environmental Enrichment through Video Games Improves Hippocampal-Associated Memory

Science.gov (United States)

Clemenson, Gregory D.

2015-01-01

The positive effects of environmental enrichment and their neural bases have been studied extensively in the rodent (van Praag et al., 2000). For example, simply modifying an animal's living environment to promote sensory stimulation can lead to (but is not limited to) enhancements in hippocampal cognition and neuroplasticity and can alleviate hippocampal cognitive deficits associated with neurodegenerative diseases and aging. We are interested in whether these manipulations that successfully enhance cognition (or mitigate cognitive decline) have similar influences on humans. Although there are many “enriching” aspects to daily life, we are constantly adapting to new experiences and situations within our own environment on a daily basis. Here, we hypothesize that the exploration of the vast and visually stimulating virtual environments within video games is a human correlate of environmental enrichment. We show that video gamers who specifically favor complex 3D video games performed better on a demanding recognition memory task that assesses participants' ability to discriminate highly similar lure items from repeated items. In addition, after 2 weeks of training on the 3D video game Super Mario 3D World, naive video gamers showed improved mnemonic discrimination ability and improvements on a virtual water maze task. Two control conditions (passive and training in a 2D game, Angry Birds), showed no such improvements. Furthermore, individual performance in both hippocampal-associated behaviors correlated with performance in Super Mario but not Angry Birds, suggesting that how individuals explored the virtual environment may influence hippocampal behavior. SIGNIFICANCE STATEMENT The hippocampus has long been associated with episodic memory and is commonly thought to rely on neuroplasticity to adapt to the ever-changing environment. In animals, it is well understood that exposing animals to a more stimulating environment, known as environmental enrichment, can

Virtual Environmental Enrichment through Video Games Improves Hippocampal-Associated Memory.

Science.gov (United States)

Clemenson, Gregory D; Stark, Craig E L

2015-12-09

The positive effects of environmental enrichment and their neural bases have been studied extensively in the rodent (van Praag et al., 2000). For example, simply modifying an animal's living environment to promote sensory stimulation can lead to (but is not limited to) enhancements in hippocampal cognition and neuroplasticity and can alleviate hippocampal cognitive deficits associated with neurodegenerative diseases and aging. We are interested in whether these manipulations that successfully enhance cognition (or mitigate cognitive decline) have similar influences on humans. Although there are many "enriching" aspects to daily life, we are constantly adapting to new experiences and situations within our own environment on a daily basis. Here, we hypothesize that the exploration of the vast and visually stimulating virtual environments within video games is a human correlate of environmental enrichment. We show that video gamers who specifically favor complex 3D video games performed better on a demanding recognition memory task that assesses participants' ability to discriminate highly similar lure items from repeated items. In addition, after 2 weeks of training on the 3D video game Super Mario 3D World, naive video gamers showed improved mnemonic discrimination ability and improvements on a virtual water maze task. Two control conditions (passive and training in a 2D game, Angry Birds), showed no such improvements. Furthermore, individual performance in both hippocampal-associated behaviors correlated with performance in Super Mario but not Angry Birds, suggesting that how individuals explored the virtual environment may influence hippocampal behavior. The hippocampus has long been associated with episodic memory and is commonly thought to rely on neuroplasticity to adapt to the ever-changing environment. In animals, it is well understood that exposing animals to a more stimulating environment, known as environmental enrichment, can stimulate neuroplasticity and

Video-Assisted Minithoracotomy for Pulmonary Laceration with a Massive Hemothorax

Directory of Open Access Journals (Sweden)

Hideki Ota

2014-01-01

Full Text Available Severe intrathoracic hemorrhage from pulmonary parenchyma is the most serious complication of pulmonary laceration after blunt trauma requiring immediate surgical hemostasis through open thoracotomy. The safety and efficacy of video-assisted thoracoscopic surgery (VATS techniques for this life-threatening condition have not been fully evaluated yet. We report a case of pulmonary laceration with a massive hemothorax after blunt trauma successfully treated using a combination of muscle-sparing minithoracotomy with VATS techniques (video-assisted minithoracotomy. A 22-year-old man was transferred to our department after a falling accident. A diagnosis of right-sided pneumothorax was made on physical examination and urgent chest decompression was performed with a tube thoracostomy. Chest computed tomographic scan revealed pulmonary laceration with hematoma in the right lung. The pulmonary hematoma extending along segmental pulmonary artery in the helium of the middle lobe ruptured suddenly into the thoracic cavity, resulting in hemorrhagic shock on the fourth day after admission. Emergency right middle lobectomy was performed through video-assisted minithoracotomy. We used two cotton dissectors as a chopstick for achieving compression hemostasis during surgery. The patient recovered satisfactorily. Video-assisted minithoracotomy can be an alternative approach for the treatment of pulmonary lacerations with a massive hemothorax in hemodynamically unstable patients.

Discriminative Localization in CNNs for Weakly-Supervised Segmentation of Pulmonary Nodules.

Science.gov (United States)

Feng, Xinyang; Yang, Jie; Laine, Andrew F; Angelini, Elsa D

2017-09-01

Automated detection and segmentation of pulmonary nodules on lung computed tomography (CT) scans can facilitate early lung cancer diagnosis. Existing supervised approaches for automated nodule segmentation on CT scans require voxel-based annotations for training, which are labor- and time-consuming to obtain. In this work, we propose a weakly-supervised method that generates accurate voxel-level nodule segmentation trained with image-level labels only. By adapting a convolutional neural network (CNN) trained for image classification, our proposed method learns discriminative regions from the activation maps of convolution units at different scales, and identifies the true nodule location with a novel candidate-screening framework. Experimental results on the public LIDC-IDRI dataset demonstrate that, our weakly-supervised nodule segmentation framework achieves competitive performance compared to a fully-supervised CNN-based segmentation method.

Multiple Moving Object Detection for Fast Video Content Description in Compressed Domain

Directory of Open Access Journals (Sweden)

Boris Mansencal

2007-11-01

Full Text Available Indexing deals with the automatic extraction of information with the objective of automatically describing and organizing the content. Thinking of a video stream, different types of information can be considered semantically important. Since we can assume that the most relevant one is linked to the presence of moving foreground objects, their number, their shape, and their appearance can constitute a good mean for content description. For this reason, we propose to combine both motion information and region-based color segmentation to extract moving objects from an MPEG2 compressed video stream starting only considering low-resolution data. This approach, which we refer to as “rough indexing,” consists in processing P-frame motion information first, and then in performing I-frame color segmentation. Next, since many details can be lost due to the low-resolution data, to improve the object detection results, a novel spatiotemporal filtering has been developed which is constituted by a quadric surface modeling the object trace along time. This method enables to effectively correct possible former detection errors without heavily increasing the computational effort.

Body Segment Kinematics and Energy Expenditure in Active Videogames.

Science.gov (United States)

Böhm, Birgit; Hartmann, Michael; Böhm, Harald

2016-06-01

Energy expenditure (EE) in active videogames (AVGs) is a component for assessing its benefit for cardiovascular health. Existing evidence suggests that AVGs are able to increase EE above rest and when compared with playing passive videogames. However, the association between body movement and EE remains unclear. Furthermore, for goal-directed game design, it is important to know the contribution of body segments to EE. This knowledge will help to acquire a certain level of exercise intensity during active gaming. Therefore, the purpose of this study was to determine the best predictors of EE from body segment energies, acceleration, and heart rate during different game situations. EE and body segment movement of 17 subjects, aged 22.1 ± 2.5 years, were measured in two different AVGs. In randomized order, the subjects played a handheld-controlled Nintendo(®) Wii™ tennis (NWT) game and a whole body-controlled Sony EyeToy(®) waterfall (ETW) game. Body segment movement was analyzed using a three-dimensional motion capture system. From the video data, mean values of mechanical energy change and acceleration of 10 body segments were analyzed. Measured EE was significantly higher in ETW (7.8 ± 1.4 metabolic equivalents [METs]) than in NWT (3.4 ± 1.0 METs). The best prediction parameter for the more intense ETW game was the energy change of the right thigh and for the less intense hand-controlled NWT game was the energy change of the upper torso. Segment acceleration was less accurate in predicting EE. The best predictors of metabolic EE were the thighs and the upper torso in whole body and handheld-controlled games, respectively. Increasing movement of these body segments would lead to higher physical activity intensity during gaming, reducing sedentary behavior.

Qualitative and quantitative analyses of the morphological-dynamics of early cardiac pumping function using video densitometry and optical coherence tomography (OCT)

DEFF Research Database (Denmark)

Happel, C.; Männer, J.; Thommes, J.

has become a matter of dispute. Uncovering of the pumping mechanism of tubular embryonic hearts requires detailed information about the hemodynamics as well as morphological dynamics of the pump action. We have analyzed the morphological dynamics of cardiac pump action in chick embryos (HH-stage 16......) of the embryonic heart segments (common atrium, AV-canal, embryonic ventricles, outflow tract). Video densitometric M-mode curves show remarkable similarities to OCT M-mode recordings. OCT M-mode recordings can only be taken at one site at a time whereas video densitometry allows simultaneous recordings at any...... striking differences in contraction behavior of different heart segments of the tubular embryonic heart. These findings are important for the understanding of the pumping mechanism of the developing valveless embryonic heart....

Fast and Sequence-Adaptive Whole-Brain Segmentation Using Parametric Bayesian Modeling

DEFF Research Database (Denmark)

Puonti, Oula; Iglesias, Juan Eugenio; Van Leemput, Koen

2016-01-01

the performance of a segmentation algorithm designed to meet these requirements, building upon generative parametric models previously used in tissue classification. The method is tested on four different datasets acquired with different scanners, field strengths and pulse sequences, demonstrating comparable...

Creating an animation-enhanced video library of hepato-pancreato-biliary and transplantation surgical procedures.

Science.gov (United States)

Fung, Albert; Kelly, Paul; Tait, Gordon; Greig, Paul D; McGilvray, Ian D

2016-01-01

The potential for integrating real-time surgical video and state-of-the art animation techniques has not been widely applied to surgical education. This paper describes the use of new technology for creating videos of liver, pancreas and transplant surgery, annotating them with 3D animations, resulting in a freely-accessible online resource: The Toronto Video Atlas of Liver, Pancreas and Transplant Surgery ( http://tvasurg.ca ). The atlas complements the teaching provided to trainees in the operating room, and the techniques described in this study can be readily adapted by other surgical training programmes.

Intelligent Packet Shaper to Avoid Network Congestion for Improved Streaming Video Quality at Clients

DEFF Research Database (Denmark)

Kaul, Manohar; Khosla, Rajiv; Mitsukura, Y

2003-01-01

of this intelligent traffic-shaping algorithm on the underlying network real time packet traffic and the eradication of unwanted abruption in the streaming video qualiy. This paper concluded from the end results of the simulation that neural networks are a very superior means of modeling real-time traffic......This paper proposes a traffic shaping algorithm based on neural networks, which adapts to a network over which streaming video is being transmitted. The purpose of this intelligent shaper is to eradicate all traffic congestion and improve the end-user's video quality. It possesses the capability...

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.

Fast and Accurate Video PQoS Estimation over Wireless Networks

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Emanuele Viterbo

2008-06-01

Full Text Available This paper proposes a curve fitting technique for fast and accurate estimation of the perceived quality of streaming media contents, delivered within a wireless network. The model accounts for the effects of various network parameters such as congestion, radio link power, and video transmission bit rate. The evaluation of the perceived quality of service (PQoS is based on the well-known VQM objective metric, a powerful technique which is highly correlated to the more expensive and time consuming subjective metrics. Currently, PQoS is used only for offline analysis after delivery of the entire video content. Thanks to the proposed simple model, we can estimate in real time the video PQoS and we can rapidly adapt the content transmission through scalable video coding and bit rates in order to offer the best perceived quality to the end users. The designed model has been validated through many different measurements in realistic wireless environments using an ad hoc WiFi test bed.

Correction tool for Active Shape Model based lumbar muscle segmentation.

Science.gov (United States)

Valenzuela, Waldo; Ferguson, Stephen J; Ignasiak, Dominika; Diserens, Gaelle; Vermathen, Peter; Boesch, Chris; Reyes, Mauricio

2015-08-01

In the clinical environment, accuracy and speed of the image segmentation process plays a key role in the analysis of pathological regions. Despite advances in anatomic image segmentation, time-effective correction tools are commonly needed to improve segmentation results. Therefore, these tools must provide faster corrections with a low number of interactions, and a user-independent solution. In this work we present a new interactive correction method for correcting the image segmentation. Given an initial segmentation and the original image, our tool provides a 2D/3D environment, that enables 3D shape correction through simple 2D interactions. Our scheme is based on direct manipulation of free form deformation adapted to a 2D environment. This approach enables an intuitive and natural correction of 3D segmentation results. The developed method has been implemented into a software tool and has been evaluated for the task of lumbar muscle segmentation from Magnetic Resonance Images. Experimental results show that full segmentation correction could be performed within an average correction time of 6±4 minutes and an average of 68±37 number of interactions, while maintaining the quality of the final segmentation result within an average Dice coefficient of 0.92±0.03.

A new visual navigation system for exploring biomedical Open Educational Resource (OER) videos.

Science.gov (United States)

Zhao, Baoquan; Xu, Songhua; Lin, Shujin; Luo, Xiaonan; Duan, Lian

2016-04-01

Biomedical videos as open educational resources (OERs) are increasingly proliferating on the Internet. Unfortunately, seeking personally valuable content from among the vast corpus of quality yet diverse OER videos is nontrivial due to limitations of today's keyword- and content-based video retrieval techniques. To address this need, this study introduces a novel visual navigation system that facilitates users' information seeking from biomedical OER videos in mass quantity by interactively offering visual and textual navigational clues that are both semantically revealing and user-friendly. The authors collected and processed around 25 000 YouTube videos, which collectively last for a total length of about 4000 h, in the broad field of biomedical sciences for our experiment. For each video, its semantic clues are first extracted automatically through computationally analyzing audio and visual signals, as well as text either accompanying or embedded in the video. These extracted clues are subsequently stored in a metadata database and indexed by a high-performance text search engine. During the online retrieval stage, the system renders video search results as dynamic web pages using a JavaScript library that allows users to interactively and intuitively explore video content both efficiently and effectively.ResultsThe authors produced a prototype implementation of the proposed system, which is publicly accessible athttps://patentq.njit.edu/oer To examine the overall advantage of the proposed system for exploring biomedical OER videos, the authors further conducted a user study of a modest scale. The study results encouragingly demonstrate the functional effectiveness and user-friendliness of the new system for facilitating information seeking from and content exploration among massive biomedical OER videos. Using the proposed tool, users can efficiently and effectively find videos of interest, precisely locate video segments delivering personally valuable

An Efficient Periodic Broadcasting with Small Latency and Buffer Demand for Near Video on Demand

Directory of Open Access Journals (Sweden)

Ying-Nan Chen

2012-01-01

Full Text Available Broadcasting Protocols can efficiently transmit videos that simultaneously shared by clients with partitioning the videos into segments. Many studies focus on decreasing clients' waiting time, such as the fixed-delay pagoda broadcasting (FDPB and the harmonic broadcasting schemes. However, limited-capability client devices such as PDAs and set-top boxes (STBs suffer from storing a significant fraction of each video while it is being watched. How to reduce clients' buffer demands is thus an important issue. Related works include the staircase broadcasting (SB, the reverse fast broadcasting (RFB, and the hybrid broadcasting (HyB schemes. This work improves FDPB to save client buffering space as well as waiting time. In comparison with SB, RFB, and HyB, the improved FDPB scheme can yield the smallest waiting time under the same buffer requirements.

Adaptive stress response in segmental progeria resembles long-lived dwarfism and calorie restriction in mice

NARCIS (Netherlands)

H.W.M. van de Ven (Marieke); J.-O. Andressoo (Jaan-Olle); V.B. Holcomb (Valerie); M.M. von Lindern (Marieke); W.M.C. Jong (Willeke); C.I. de Zeeuw (Chris); Y. Suh (Yousin); P. Hasty (Paul); J.H.J. Hoeijmakers (Jan); G.T.J. van der Horst (Gijsbertus); J.R. Mitchell (James)

2006-01-01

textabstractHow congenital defects causing genome instability can result in the pleiotropic symptoms reminiscent of aging but in a segmental and accelerated fashion remains largely unknown. Most segmental progerias are associated with accelerated fibroblast senescence, suggesting that cellular

Improved embedded non-linear processing of video for camera surveillance

NARCIS (Netherlands)

Cvetkovic, S.D.; With, de P.H.N.

2009-01-01

For a real time imaging in surveillance applications, image fidelity is of primary importance to ensure customer confidence. The fidelity is obtained amongst others via dynamic range expansion and video signal enhancement. The dynamic range of the signal needs adaptation, because the sensor signal

Detection of illegal transfer of videos over the Internet

Science.gov (United States)

Chaisorn, Lekha; Sainui, Janya; Manders, Corey

2010-07-01

In this paper, a method for detecting infringements or modifications of a video in real-time is proposed. The method first segments a video stream into shots, after which it extracts some reference frames as keyframes. This process is performed employing a Singular Value Decomposition (SVD) technique developed in this work. Next, for each input video (represented by its keyframes), ordinal-based signature and SIFT (Scale Invariant Feature Transform) descriptors are generated. The ordinal-based method employs a two-level bitmap indexing scheme to construct the index for each video signature. The first level clusters all input keyframes into k clusters while the second level converts the ordinal-based signatures into bitmap vectors. On the other hand, the SIFT-based method directly uses the descriptors as the index. Given a suspect video (being streamed or transferred on the Internet), we generate the signature (ordinal and SIFT descriptors) then we compute similarity between its signature and those signatures in the database based on ordinal signature and SIFT descriptors separately. For similarity measure, besides the Euclidean distance, Boolean operators are also utilized during the matching process. We have tested our system by performing several experiments on 50 videos (each about 1/2 hour in duration) obtained from the TRECVID 2006 data set. For experiments set up, we refer to the conditions provided by TRECVID 2009 on "Content-based copy detection" task. In addition, we also refer to the requirements issued in the call for proposals by MPEG standard on the similar task. Initial result shows that our framework is effective and robust. As compared to our previous work, on top of the achievement we obtained by reducing the storage space and time taken in the ordinal based method, by introducing the SIFT features, we could achieve an overall accuracy in F1 measure of about 96% (improved about 8%).

Nuclear information for video presentation

International Nuclear Information System (INIS)

Dalton, J.

1979-01-01

In an effort to help calm the turbulence left in the wake of the Three Mile Island (TMI) nuclear accident, the Georgia Society of Professional Engineers sponsored the production of a video tape on the inner workings of a nuclear power plant. A 30-minute segment was shown on public television and a longer version is being prepared for use on a commercial network. The tape is neither pro nor con in the multitude of issues surrounding the future of nuclear energy. It simply gives a layman's tour of a nuclear power plant and hopes to provide the public with objective information on how nuclear power is generated. The article discusses the background of the taping program project, and how it was put together

Adaptive stress response in segmental progeria resembles long-lived dwarfism and calorie restriction in mice

NARCIS (Netherlands)

van de Ven, Marieke; Andressoo, Jaan-Olle; Holcomb, Valerie B.; von Lindern, Marieke; Jong, Willeke M. C.; de Zeeuw, Chris I.; Suh, Yousin; Hasty, Paul; Hoeijmakers, Jan H. J.; van der Horst, Gijsbertus T. J.; Mitchell, James R.

2006-01-01

How congenital defects causing genome instability can result in the pleiotropic symptoms reminiscent of aging but in a segmental and accelerated fashion remains largely unknown. Most segmental progerias are associated with accelerated fibroblast senescence, suggesting that cellular senescence is a

An optimized video system for augmented reality in endodontics: a feasibility study.

Science.gov (United States)

Bruellmann, D D; Tjaden, H; Schwanecke, U; Barth, P

2013-03-01

We propose an augmented reality system for the reliable detection of root canals in video sequences based on a k-nearest neighbor color classification and introduce a simple geometric criterion for teeth. The new software was implemented using C++, Qt, and the image processing library OpenCV. Teeth are detected in video images to restrict the segmentation of the root canal orifices by using a k-nearest neighbor algorithm. The location of the root canal orifices were determined using Euclidean distance-based image segmentation. A set of 126 human teeth with known and verified locations of the root canal orifices was used for evaluation. The software detects root canals orifices for automatic classification of the teeth in video images and stores location and size of the found structures. Overall 287 of 305 root canals were correctly detected. The overall sensitivity was about 94 %. Classification accuracy for molars ranged from 65.0 to 81.2 % and from 85.7 to 96.7 % for premolars. The realized software shows that observations made in anatomical studies can be exploited to automate real-time detection of root canal orifices and tooth classification with a software system. Automatic storage of location, size, and orientation of the found structures with this software can be used for future anatomical studies. Thus, statistical tables with canal locations will be derived, which can improve anatomical knowledge of the teeth to alleviate root canal detection in the future. For this purpose the software is freely available at: http://www.dental-imaging.zahnmedizin.uni-mainz.de/.

Segmentation of nodules on chest computed tomography for growth assessment

International Nuclear Information System (INIS)

Mullally, William; Betke, Margrit; Wang Jingbin; Ko, Jane P.

2004-01-01

Several segmentation methods to evaluate growth of small isolated pulmonary nodules on chest computed tomography (CT) are presented. The segmentation methods are based on adaptively thresholding attenuation levels and use measures of nodule shape. The segmentation methods were first tested on a realistic chest phantom to evaluate their performance with respect to specific nodule characteristics. The segmentation methods were also tested on sequential CT scans of patients. The methods' estimation of nodule growth were compared to the volume change calculated by a chest radiologist. The best method segmented nodules on average 43% smaller or larger than the actual nodule when errors were computed across all nodule variations on the phantom. Some methods achieved smaller errors when examined with respect to certain nodule properties. In particular, on the phantom individual methods segmented solid nodules to within 23% of their actual size and nodules with 60.7 mm3 volumes to within 14%. On the clinical data, none of the methods examined showed a statistically significant difference in growth estimation from the radiologist

A Content-Adaptive Analysis and Representation Framework for Audio Event Discovery from "Unscripted" Multimedia

Science.gov (United States)

Radhakrishnan, Regunathan; Divakaran, Ajay; Xiong, Ziyou; Otsuka, Isao

2006-12-01

We propose a content-adaptive analysis and representation framework to discover events using audio features from "unscripted" multimedia such as sports and surveillance for summarization. The proposed analysis framework performs an inlier/outlier-based temporal segmentation of the content. It is motivated by the observation that "interesting" events in unscripted multimedia occur sparsely in a background of usual or "uninteresting" events. We treat the sequence of low/mid-level features extracted from the audio as a time series and identify subsequences that are outliers. The outlier detection is based on eigenvector analysis of the affinity matrix constructed from statistical models estimated from the subsequences of the time series. We define the confidence measure on each of the detected outliers as the probability that it is an outlier. Then, we establish a relationship between the parameters of the proposed framework and the confidence measure. Furthermore, we use the confidence measure to rank the detected outliers in terms of their departures from the background process. Our experimental results with sequences of low- and mid-level audio features extracted from sports video show that "highlight" events can be extracted effectively as outliers from a background process using the proposed framework. We proceed to show the effectiveness of the proposed framework in bringing out suspicious events from surveillance videos without any a priori knowledge. We show that such temporal segmentation into background and outliers, along with the ranking based on the departure from the background, can be used to generate content summaries of any desired length. Finally, we also show that the proposed framework can be used to systematically select "key audio classes" that are indicative of events of interest in the chosen domain.

AUTOMATED CELL SEGMENTATION WITH 3D FLUORESCENCE MICROSCOPY IMAGES.

Science.gov (United States)

Kong, Jun; Wang, Fusheng; Teodoro, George; Liang, Yanhui; Zhu, Yangyang; Tucker-Burden, Carol; Brat, Daniel J

2015-04-01

A large number of cell-oriented cancer investigations require an effective and reliable cell segmentation method on three dimensional (3D) fluorescence microscopic images for quantitative analysis of cell biological properties. In this paper, we present a fully automated cell segmentation method that can detect cells from 3D fluorescence microscopic images. Enlightened by fluorescence imaging techniques, we regulated the image gradient field by gradient vector flow (GVF) with interpolated and smoothed data volume, and grouped voxels based on gradient modes identified by tracking GVF field. Adaptive thresholding was then applied to voxels associated with the same gradient mode where voxel intensities were enhanced by a multiscale cell filter. We applied the method to a large volume of 3D fluorescence imaging data of human brain tumor cells with (1) small cell false detection and missing rates for individual cells; and (2) trivial over and under segmentation incidences for clustered cells. Additionally, the concordance of cell morphometry structure between automated and manual segmentation was encouraging. These results suggest a promising 3D cell segmentation method applicable to cancer studies.

The Use of Videos in Teaching - Some Experiences From the University of Copenhagen

Directory of Open Access Journals (Sweden)

Henrik Bregnhøj

2016-11-01

Full Text Available This paper covers videos created and used in different learning patterns. The videos are grouped according to the teaching or learning activities in which they are used. One group of videos are used by the teacher for one-way communication, including: online lectures, experts interacting with one another, instruction videos and introduction videos. Further videos are teacher-student interactive videos, including: feedback on student deliveries, student productions and interactive videos. Examples from different courses at different faculties at The University of Copenhagen of different types of videos (screencasts, pencasts and different kinds of camera recordings, from quick-and-dirty videos made by teachers at their own computer to professionally produced studio recordings as well as audio files are presented with links, as an empirical basis for the discussion. The paper is very practically oriented and looks at e.g. which course design and teaching situation is suitable for which type of video; at which point is an audio file preferable to a video file; and how to produce videos easily and without specialized equipment, if you don’t have access to (or time for professional assistance. In the article, we also point out how a small amount of tips & tricks regarding planning, design and presentation technique can improve recordings made by teachers themselves. We argue that the way to work with audio and video is to start by analyzing the pedagogical needs, in this way adapting the type and use of audio and video to the pedagogical context.

Concurrent Calculations on Reconfigurable Logic Devices Applied to the Analysis of Video Images

Directory of Open Access Journals (Sweden)

Sergio R. Geninatti

2010-01-01

Full Text Available This paper presents the design and implementation on FPGA devices of an algorithm for computing similarities between neighboring frames in a video sequence using luminance information. By taking advantage of the well-known flexibility of Reconfigurable Logic Devices, we have designed a hardware implementation of the algorithm used in video segmentation and indexing. The experimental results show the tradeoff between concurrent sequential resources and the functional blocks needed to achieve maximum operational speed while achieving minimum silicon area usage. To evaluate system efficiency, we compare the performance of the hardware solution to that of calculations done via software using general-purpose processors with and without an SIMD instruction set.

HMM Adaptation for Improving a Human Activity Recognition System

Directory of Open Access Journals (Sweden)