REM-3D Reference Datasets: Reconciling large and diverse compilations of travel-time observations

Science.gov (United States)

Moulik, P.; Lekic, V.; Romanowicz, B. A.

2017-12-01

A three-dimensional Reference Earth model (REM-3D) should ideally represent the consensus view of long-wavelength heterogeneity in the Earth's mantle through the joint modeling of large and diverse seismological datasets. This requires reconciliation of datasets obtained using various methodologies and identification of consistent features. The goal of REM-3D datasets is to provide a quality-controlled and comprehensive set of seismic observations that would not only enable construction of REM-3D, but also allow identification of outliers and assist in more detailed studies of heterogeneity. The community response to data solicitation has been enthusiastic with several groups across the world contributing recent measurements of normal modes, (fundamental mode and overtone) surface waves, and body waves. We present results from ongoing work with body and surface wave datasets analyzed in consultation with a Reference Dataset Working Group. We have formulated procedures for reconciling travel-time datasets that include: (1) quality control for salvaging missing metadata; (2) identification of and reasons for discrepant measurements; (3) homogenization of coverage through the construction of summary rays; and (4) inversions of structure at various wavelengths to evaluate inter-dataset consistency. In consultation with the Reference Dataset Working Group, we retrieved the station and earthquake metadata in several legacy compilations and codified several guidelines that would facilitate easy storage and reproducibility. We find strong agreement between the dispersion measurements of fundamental-mode Rayleigh waves, particularly when made using supervised techniques. The agreement deteriorates substantially in surface-wave overtones, for which discrepancies vary with frequency and overtone number. A half-cycle band of discrepancies is attributed to reversed instrument polarities at a limited number of stations, which are not reflected in the instrument response history

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

No-Reference Video Quality Assessment Model for Distortion Caused by Packet Loss in the Real-Time Mobile Video Services

Directory of Open Access Journals (Sweden)

Jiarun Song

2014-01-01

Full Text Available Packet loss will make severe errors due to the corruption of related video data. For most video streams, because the predictive coding structures are employed, the transmission errors in one frame will not only cause decoding failure of itself at the receiver side, but also propagate to its subsequent frames along the motion prediction path, which will bring a significant degradation of end-to-end video quality. To quantify the effects of packet loss on video quality, a no-reference objective quality assessment model is presented in this paper. Considering the fact that the degradation of video quality significantly relies on the video content, the temporal complexity is estimated to reflect the varying characteristic of video content, using the macroblocks with different motion activities in each frame. Then, the quality of the frame affected by the reference frame loss, by error propagation, or by both of them is evaluated, respectively. Utilizing a two-level temporal pooling scheme, the video quality is finally obtained. Extensive experimental results show that the video quality estimated by the proposed method matches well with the subjective quality.

Who Is at Risk for Problematic Video Gaming? Risk Factors in Problematic Video Gaming in Clinically Referred Canadian Children and Adolescents

OpenAIRE

Chloe Lau; Shannon L. Stewart; Catalina Sarmiento; Donald H. Saklofske; Paul F. Tremblay

2018-01-01

Both Internet and offline video gaming have become a normal aspect of child development, with estimates of children playing video games ranging from 90% to 97%. Research on problematic video gaming (PVG) has grown substantially in the last decade. Much of that research has focused on community samples, while research on clinically referred children and youth is lacking. The present study includes 5820 clinically referred children and youth across 44 mental health agencies, assessed using the ...

Multimodal Feature Learning for Video Captioning

Directory of Open Access Journals (Sweden)

Sujin Lee

2018-01-01

Full Text Available Video captioning refers to the task of generating a natural language sentence that explains the content of the input video clips. This study proposes a deep neural network model for effective video captioning. Apart from visual features, the proposed model learns additionally semantic features that describe the video content effectively. In our model, visual features of the input video are extracted using convolutional neural networks such as C3D and ResNet, while semantic features are obtained using recurrent neural networks such as LSTM. In addition, our model includes an attention-based caption generation network to generate the correct natural language captions based on the multimodal video feature sequences. Various experiments, conducted with the two large benchmark datasets, Microsoft Video Description (MSVD and Microsoft Research Video-to-Text (MSR-VTT, demonstrate the performance of the proposed model.

Video-Quality Estimation Based on Reduced-Reference Model Employing Activity-Difference

Science.gov (United States)

Yamada, Toru; Miyamoto, Yoshihiro; Senda, Yuzo; Serizawa, Masahiro

This paper presents a Reduced-reference based video-quality estimation method suitable for individual end-user quality monitoring of IPTV services. With the proposed method, the activity values for individual given-size pixel blocks of an original video are transmitted to end-user terminals. At the end-user terminals, the video quality of a received video is estimated on the basis of the activity-difference between the original video and the received video. Psychovisual weightings and video-quality score adjustments for fatal degradations are applied to improve estimation accuracy. In addition, low-bit-rate transmission is achieved by using temporal sub-sampling and by transmitting only the lower six bits of each activity value. The proposed method achieves accurate video quality estimation using only low-bit-rate original video information (15kbps for SDTV). The correlation coefficient between actual subjective video quality and estimated quality is 0.901 with 15kbps side information. The proposed method does not need computationally demanding spatial and gain-and-offset registrations. Therefore, it is suitable for real-time video-quality monitoring in IPTV services.

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

Directory of Open Access Journals (Sweden)

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.

Perceptual quality estimation of H.264/AVC videos using reduced-reference and no-reference models

Science.gov (United States)

Shahid, Muhammad; Pandremmenou, Katerina; Kondi, Lisimachos P.; Rossholm, Andreas; Lövström, Benny

2016-09-01

Reduced-reference (RR) and no-reference (NR) models for video quality estimation, using features that account for the impact of coding artifacts, spatio-temporal complexity, and packet losses, are proposed. The purpose of this study is to analyze a number of potentially quality-relevant features in order to select the most suitable set of features for building the desired models. The proposed sets of features have not been used in the literature and some of the features are used for the first time in this study. The features are employed by the least absolute shrinkage and selection operator (LASSO), which selects only the most influential of them toward perceptual quality. For comparison, we apply feature selection in the complete feature sets and ridge regression on the reduced sets. The models are validated using a database of H.264/AVC encoded videos that were subjectively assessed for quality in an ITU-T compliant laboratory. We infer that just two features selected by RR LASSO and two bitstream-based features selected by NR LASSO are able to estimate perceptual quality with high accuracy, higher than that of ridge, which uses more features. The comparisons with competing works and two full-reference metrics also verify the superiority of our models.

Who Is at Risk for Problematic Video Gaming? Risk Factors in Problematic Video Gaming in Clinically Referred Canadian Children and Adolescents

Directory of Open Access Journals (Sweden)

Chloe Lau

2018-04-01

Full Text Available Both Internet and offline video gaming have become a normal aspect of child development, with estimates of children playing video games ranging from 90% to 97%. Research on problematic video gaming (PVG has grown substantially in the last decade. Much of that research has focused on community samples, while research on clinically referred children and youth is lacking. The present study includes 5820 clinically referred children and youth across 44 mental health agencies, assessed using the interRAI Child and Youth Mental Health Assessment. Logistic regression analyses revealed that older age, male sex, extreme shyness, internalizing symptoms, externalizing symptoms, and poor relational strengths are all significant predictors of problematic video gaming (PVG. Further analyses suggested that, out of the internalizing symptoms, anhedonia was predictive of PVG in both males and females, but depressive symptoms and anxiety were not predictive of PVG when controlling for other variables in the model. Moreover, proactive aggression and extreme shyness were predictive of PVG in males, but not in females. The implications of these findings are discussed.

Calculation of climatic reference values and its use for automatic outlier detection in meteorological datasets

Directory of Open Access Journals (Sweden)

B. Téllez

2008-04-01

Full Text Available The climatic reference values for monthly and annual average air temperature and total precipitation in Catalonia – northeast of Spain – are calculated using a combination of statistical methods and geostatistical techniques of interpolation. In order to estimate the uncertainty of the method, the initial dataset is split into two parts that are, respectively, used for estimation and validation. The resulting maps are then used in the automatic outlier detection in meteorological datasets.

Video demystified

CERN Document Server

Jack, Keith

2004-01-01

This international bestseller and essential reference is the "bible" for digital video engineers and programmers worldwide. This is by far the most informative analog and digital video reference available, includes the hottest new trends and cutting-edge developments in the field. Video Demystified, Fourth Edition is a "one stop" reference guide for the various digital video technologies. The fourth edition is completely updated with all new chapters on MPEG-4, H.264, SDTV/HDTV, ATSC/DVB, and Streaming Video (Video over DSL, Ethernet, etc.), as well as discussions of the latest standards throughout. The accompanying CD-ROM is updated to include a unique set of video test files in the newest formats. *This essential reference is the "bible" for digital video engineers and programmers worldwide *Contains all new chapters on MPEG-4, H.264, SDTV/HDTV, ATSC/DVB, and Streaming Video *Completely revised with all the latest and most up-to-date industry standards.

No Reference Video-Quality-Assessment Model for Monitoring Video Quality of IPTV Services

Science.gov (United States)

Yamagishi, Kazuhisa; Okamoto, Jun; Hayashi, Takanori; Takahashi, Akira

Service providers should monitor the quality of experience of a communication service in real time to confirm its status. To do this, we previously proposed a packet-layer model that can be used for monitoring the average video quality of typical Internet protocol television content using parameters derived from transmitted packet headers. However, it is difficult to monitor the video quality per user using the average video quality because video quality depends on the video content. To accurately monitor the video quality per user, a model that can be used for estimating the video quality per video content rather than the average video quality should be developed. Therefore, to take into account the impact of video content on video quality, we propose a model that calculates the difference in video quality between the video quality of the estimation-target video and the average video quality estimated using a packet-layer model. We first conducted extensive subjective quality assessments for different codecs and video sequences. We then model their characteristics based on parameters related to compression and packet loss. Finally, we verify the performance of the proposed model by applying it to unknown data sets different from the training data sets used for developing the model.

Non-Cooperative Facial Recognition Video Dataset Collection Plan

Energy Technology Data Exchange (ETDEWEB)

Kimura, Marcia L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Erikson, Rebecca L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lombardo, Nicholas J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2013-08-31

The Pacific Northwest National Laboratory (PNNL) will produce a non-cooperative (i.e. not posing for the camera) facial recognition video data set for research purposes to evaluate and enhance facial recognition systems technology. The aggregate data set consists of 1) videos capturing PNNL role players and public volunteers in three key operational settings, 2) photographs of the role players for enrolling in an evaluation database, and 3) ground truth data that documents when the role player is within various camera fields of view. PNNL will deliver the aggregate data set to DHS who may then choose to make it available to other government agencies interested in evaluating and enhancing facial recognition systems. The three operational settings that will be the focus of the video collection effort include: 1) unidirectional crowd flow 2) bi-directional crowd flow, and 3) linear and/or serpentine queues.

Integrated remotely sensed datasets for disaster management

Science.gov (United States)

McCarthy, Timothy; Farrell, Ronan; Curtis, Andrew; Fotheringham, A. Stewart

2008-10-01

Video imagery can be acquired from aerial, terrestrial and marine based platforms and has been exploited for a range of remote sensing applications over the past two decades. Examples include coastal surveys using aerial video, routecorridor infrastructures surveys using vehicle mounted video cameras, aerial surveys over forestry and agriculture, underwater habitat mapping and disaster management. Many of these video systems are based on interlaced, television standards such as North America's NTSC and European SECAM and PAL television systems that are then recorded using various video formats. This technology has recently being employed as a front-line, remote sensing technology for damage assessment post-disaster. This paper traces the development of spatial video as a remote sensing tool from the early 1980s to the present day. The background to a new spatial-video research initiative based at National University of Ireland, Maynooth, (NUIM) is described. New improvements are proposed and include; low-cost encoders, easy to use software decoders, timing issues and interoperability. These developments will enable specialists and non-specialists collect, process and integrate these datasets within minimal support. This integrated approach will enable decision makers to access relevant remotely sensed datasets quickly and so, carry out rapid damage assessment during and post-disaster.

Deep video deblurring

KAUST Repository

Su, Shuochen

2016-11-25

Motion blur from camera shake is a major problem in videos captured by hand-held devices. Unlike single-image deblurring, video-based approaches can take advantage of the abundant information that exists across neighboring frames. As a result the best performing methods rely on aligning nearby frames. However, aligning images is a computationally expensive and fragile procedure, and methods that aggregate information must therefore be able to identify which regions have been accurately aligned and which have not, a task which requires high level scene understanding. In this work, we introduce a deep learning solution to video deblurring, where a CNN is trained end-to-end to learn how to accumulate information across frames. To train this network, we collected a dataset of real videos recorded with a high framerate camera, which we use to generate synthetic motion blur for supervision. We show that the features learned from this dataset extend to deblurring motion blur that arises due to camera shake in a wide range of videos, and compare the quality of results to a number of other baselines.

Efficient Temporal Action Localization in Videos

KAUST Repository

Alwassel, Humam

2018-04-17

State-of-the-art temporal action detectors inefficiently search the entire video for specific actions. Despite the encouraging progress these methods achieve, it is crucial to design automated approaches that only explore parts of the video which are the most relevant to the actions being searched. To address this need, we propose the new problem of action spotting in videos, which we define as finding a specific action in a video while observing a small portion of that video. Inspired by the observation that humans are extremely efficient and accurate in spotting and finding action instances in a video, we propose Action Search, a novel Recurrent Neural Network approach that mimics the way humans spot actions. Moreover, to address the absence of data recording the behavior of human annotators, we put forward the Human Searches dataset, which compiles the search sequences employed by human annotators spotting actions in the AVA and THUMOS14 datasets. We consider temporal action localization as an application of the action spotting problem. Experiments on the THUMOS14 dataset reveal that our model is not only able to explore the video efficiently (observing on average 17.3% of the video) but it also accurately finds human activities with 30.8% mAP (0.5 tIoU), outperforming state-of-the-art methods

No-Reference Video Quality Assessment Based on Statistical Analysis in 3D-DCT Domain.

Science.gov (United States)

Li, Xuelong; Guo, Qun; Lu, Xiaoqiang

2016-05-13

It is an important task to design models for universal no-reference video quality assessment (NR-VQA) in multiple video processing and computer vision applications. However, most existing NR-VQA metrics are designed for specific distortion types which are not often aware in practical applications. A further deficiency is that the spatial and temporal information of videos is hardly considered simultaneously. In this paper, we propose a new NR-VQA metric based on the spatiotemporal natural video statistics (NVS) in 3D discrete cosine transform (3D-DCT) domain. In the proposed method, a set of features are firstly extracted based on the statistical analysis of 3D-DCT coefficients to characterize the spatiotemporal statistics of videos in different views. These features are used to predict the perceived video quality via the efficient linear support vector regression (SVR) model afterwards. The contributions of this paper are: 1) we explore the spatiotemporal statistics of videos in 3DDCT domain which has the inherent spatiotemporal encoding advantage over other widely used 2D transformations; 2) we extract a small set of simple but effective statistical features for video visual quality prediction; 3) the proposed method is universal for multiple types of distortions and robust to different databases. The proposed method is tested on four widely used video databases. Extensive experimental results demonstrate that the proposed method is competitive with the state-of-art NR-VQA metrics and the top-performing FR-VQA and RR-VQA metrics.

Online Detection of Abnormal Events in Video Streams

Directory of Open Access Journals (Sweden)

Tian Wang

2013-01-01

an image descriptor and online nonlinear classification method. We introduce the covariance matrix of the optical flow and image intensity as a descriptor encoding moving information. The nonlinear online support vector machine (SVM firstly learns a limited set of the training frames to provide a basic reference model then updates the model and detects abnormal events in the current frame. We finally apply the method to detect abnormal events on a benchmark video surveillance dataset to demonstrate the effectiveness of the proposed technique.

Northern Chinese dental ages estimated from southern Chinese reference datasets closely correlate with chronological age

Directory of Open Access Journals (Sweden)

Hai Ming Wong

2016-12-01

Full Text Available While northern and southern Chinese are genetically correlated, there exists notable environmental differences in their living conditions. This study aimed to evaluate validity of the southern Chinese reference dataset for dental age estimation applied to northern Chinese. Dental panoramic tomographs of 437 northern Chinese aged 3 to 21 years were analysed. All the left maxillary and mandibular permanent teeth plus the 2 third molars on the right side were scored based on Demirjian’s classification of tooth development stages. Mean and standard error of dental age were obtained for each tooth development stage, followed by random effect meta-analysis for mean dental age estimation. Validity of the method was examined through measures of agreement (95% limits of agreement, standard error of measurement, and Lin’s concordance correlation coefficient and measure of reliability (Intraclass correlation coefficient. On average, the estimated dental age overestimated chronological age by only around 1 month in both females and males. The Intraclass correlation coefficient values were 0.99 for both sexes, suggesting excellent reliability of the method. Reference dataset for dental age estimation developed on the basis of southern Chinese was applicable for use among the northern Chinese.

A novel no-reference objective stereoscopic video quality assessment method based on visual saliency analysis

Science.gov (United States)

Yang, Xinyan; Zhao, Wei; Ye, Long; Zhang, Qin

2017-07-01

This paper proposes a no-reference objective stereoscopic video quality assessment method with the motivation that making the effect of objective experiments close to that of subjective way. We believe that the image regions with different visual salient degree should not have the same weights when designing an assessment metric. Therefore, we firstly use GBVS algorithm to each frame pairs and separate both the left and right viewing images into the regions with strong, general and week saliency. Besides, local feature information like blockiness, zero-crossing and depth are extracted and combined with a mathematical model to calculate a quality assessment score. Regions with different salient degree are assigned with different weights in the mathematical model. Experiment results demonstrate the superiority of our method compared with the existed state-of-the-art no-reference objective Stereoscopic video quality assessment methods.

Learning from Narrated Instruction Videos.

Science.gov (United States)

Alayrac, Jean-Baptiste; Bojanowski, Piotr; Agrawal, Nishant; Sivic, Josef; Laptev, Ivan; Lacoste-Julien, Simon

2017-09-05

Automatic assistants could guide a person or a robot in performing new tasks, such as changing a car tire or repotting a plant. Creating such assistants, however, is non-trivial and requires understanding of visual and verbal content of a video. Towards this goal, we here address the problem of automatically learning the main steps of a task from a set of narrated instruction videos. We develop a new unsupervised learning approach that takes advantage of the complementary nature of the input video and the associated narration. The method sequentially clusters textual and visual representations of a task, where the two clustering problems are linked by joint constraints to obtain a single coherent sequence of steps in both modalities. To evaluate our method, we collect and annotate a new challenging dataset of real-world instruction videos from the Internet. The dataset contains videos for five different tasks with complex interactions between people and objects, captured in a variety of indoor and outdoor settings. We experimentally demonstrate that the proposed method can automatically discover, learn and localize the main steps of a task input videos.

Efficient Temporal Action Localization in Videos

KAUST Repository

Alwassel, Humam

2018-01-01

as an application of the action spotting problem. Experiments on the THUMOS14 dataset reveal that our model is not only able to explore the video efficiently (observing on average 17.3% of the video) but it also accurately finds human activities with 30.8% mAP (0

Learning Computational Models of Video Memorability from fMRI Brain Imaging.

Science.gov (United States)

Han, Junwei; Chen, Changyuan; Shao, Ling; Hu, Xintao; Han, Jungong; Liu, Tianming

2015-08-01

Generally, various visual media are unequally memorable by the human brain. This paper looks into a new direction of modeling the memorability of video clips and automatically predicting how memorable they are by learning from brain functional magnetic resonance imaging (fMRI). We propose a novel computational framework by integrating the power of low-level audiovisual features and brain activity decoding via fMRI. Initially, a user study experiment is performed to create a ground truth database for measuring video memorability and a set of effective low-level audiovisual features is examined in this database. Then, human subjects' brain fMRI data are obtained when they are watching the video clips. The fMRI-derived features that convey the brain activity of memorizing videos are extracted using a universal brain reference system. Finally, due to the fact that fMRI scanning is expensive and time-consuming, a computational model is learned on our benchmark dataset with the objective of maximizing the correlation between the low-level audiovisual features and the fMRI-derived features using joint subspace learning. The learned model can then automatically predict the memorability of videos without fMRI scans. Evaluations on publically available image and video databases demonstrate the effectiveness of the proposed framework.

Video Quality Assessment and Machine Learning: Performance and Interpretability

DEFF Research Database (Denmark)

Søgaard, Jacob; Forchhammer, Søren; Korhonen, Jari

2015-01-01

In this work we compare a simple and a complex Machine Learning (ML) method used for the purpose of Video Quality Assessment (VQA). The simple ML method chosen is the Elastic Net (EN), which is a regularized linear regression model and easier to interpret. The more complex method chosen is Support...... Vector Regression (SVR), which has gained popularity in VQA research. Additionally, we present an ML-based feature selection method. Also, it is investigated how well the methods perform when tested on videos from other datasets. Our results show that content-independent cross-validation performance...... on a single dataset can be misleading and that in the case of very limited training and test data, especially in regards to different content as is the case for many video datasets, a simple ML approach is the better choice....

Video segmentation using keywords

Science.gov (United States)

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

2018-04-01

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

A No-Reference Modular Video Quality Prediction Model for H.265/HEVC and VP9 Codecs on a Mobile Device

Directory of Open Access Journals (Sweden)

Debajyoti Pal

2017-01-01

Full Text Available We propose a modular no-reference video quality prediction model for videos that are encoded with H.265/HEVC and VP9 codecs and viewed on mobile devices. The impairments which can affect video transmission are classified into two broad types depending upon which layer of the TCP/IP model they originated from. Impairments from the network layer are called the network QoS factors, while those from the application layer are called the application/payload QoS factors. Initially we treat the network and application QoS factors separately and find out the 1 : 1 relationship between the respective QoS factors and the corresponding perceived video quality or QoE. The mapping from the QoS to the QoE domain is based upon a decision variable that gives an optimal performance. Next, across each group we choose multiple QoS factors and find out the QoE for such multifactor impaired videos by using an additive, multiplicative, and regressive approach. We refer to these as the integrated network and application QoE, respectively. At the end, we use a multiple regression approach to combine the network and application QoE for building the final model. We also use an Artificial Neural Network approach for building the model and compare its performance with the regressive approach.

Video Comparator

International Nuclear Information System (INIS)

Rose, R.P.

1978-01-01

The Video Comparator is a comparative gage that uses electronic images from two sources, a standard and an unknown. Two matched video cameras are used to obtain the electronic images. The video signals are mixed and displayed on a single video receiver (CRT). The video system is manufactured by ITP of Chatsworth, CA and is a Tele-Microscope II, Model 148. One of the cameras is mounted on a toolmaker's microscope stand and produces a 250X image of a cast. The other camera is mounted on a stand and produces an image of a 250X template. The two video images are mixed in a control box provided by ITP and displayed on a CRT. The template or the cast can be moved to align the desired features. Vertical reference lines are provided on the CRT, and a feature on the cast can be aligned with a line on the CRT screen. The stage containing the casts can be moved using a Boeckleler micrometer equipped with a digital readout, and a second feature aligned with the reference line and the distance moved obtained from the digital display

Relacije umetnosti i video igara / Relations of Art and Video Games

OpenAIRE

Manojlo Maravić

2012-01-01

When discussing the art of video games, three different contexts need to be considered: the 'high' art (video games and the art); commercial video games (video games as the art) and the fan art. Video games are a legitimate artistic medium subject to modifications and recontextualisations in the process of creating a specific experience of the player/user/audience and political action by referring to particular social problems. They represent a high technological medium that increases, with p...

MPEG2 video parameter and no reference PSNR estimation

DEFF Research Database (Denmark)

Li, Huiying; Forchhammer, Søren

2009-01-01

MPEG coded video may be processed for quality assessment or postprocessed to reduce coding artifacts or transcoded. Utilizing information about the MPEG stream may be useful for these tasks. This paper deals with estimating MPEG parameter information from the decoded video stream without access t...

REAL-TIME VIDEO SCALING BASED ON CONVOLUTION NEURAL NETWORK ARCHITECTURE

OpenAIRE

S Safinaz; A V Ravi Kumar

2017-01-01

In recent years, video super resolution techniques becomes mandatory requirements to get high resolution videos. Many super resolution techniques researched but still video super resolution or scaling is a vital challenge. In this paper, we have presented a real-time video scaling based on convolution neural network architecture to eliminate the blurriness in the images and video frames and to provide better reconstruction quality while scaling of large datasets from lower resolution frames t...

A multi-environment dataset for activity of daily living recognition in video streams.

Science.gov (United States)

Borreo, Alessandro; Onofri, Leonardo; Soda, Paolo

2015-08-01

Public datasets played a key role in the increasing level of interest that vision-based human action recognition has attracted in last years. While the production of such datasets has been influenced by the variability introduced by various actors performing the actions, the different modalities of interactions with the environment introduced by the variation of the scenes around the actors has been scarcely took into account. As a consequence, public datasets do not provide a proper test-bed for recognition algorithms that aim at achieving high accuracy, irrespective of the environment where actions are performed. This is all the more so, when systems are designed to recognize activities of daily living (ADL), which are characterized by a high level of human-environment interaction. For that reason, we present in this manuscript the MEA dataset, a new multi-environment ADL dataset, which permitted us to show how the change of scenario can affect the performances of state-of-the-art approaches for action recognition.

TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild

KAUST Repository

Mü ller, Matthias; Bibi, Adel Aamer; Giancola, Silvio; Al-Subaihi, Salman; Ghanem, Bernard

2018-01-01

Despite the numerous developments in object tracking, further development of current tracking algorithms is limited by small and mostly saturated datasets. As a matter of fact, data-hungry trackers based on deep-learning currently rely on object detection datasets due to the scarcity of dedicated large-scale tracking datasets. In this work, we present TrackingNet, the first large-scale dataset and benchmark for object tracking in the wild. We provide more than 30K videos with more than 14 million dense bounding box annotations. Our dataset covers a wide selection of object classes in broad and diverse context. By releasing such a large-scale dataset, we expect deep trackers to further improve and generalize. In addition, we introduce a new benchmark composed of 500 novel videos, modeled with a distribution similar to our training dataset. By sequestering the annotation of the test set and providing an online evaluation server, we provide a fair benchmark for future development of object trackers. Deep trackers fine-tuned on a fraction of our dataset improve their performance by up to 1.6% on OTB100 and up to 1.7% on TrackingNet Test. We provide an extensive benchmark on TrackingNet by evaluating more than 20 trackers. Our results suggest that object tracking in the wild is far from being solved.

TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild

KAUST Repository

Müller, Matthias

2018-03-28

Despite the numerous developments in object tracking, further development of current tracking algorithms is limited by small and mostly saturated datasets. As a matter of fact, data-hungry trackers based on deep-learning currently rely on object detection datasets due to the scarcity of dedicated large-scale tracking datasets. In this work, we present TrackingNet, the first large-scale dataset and benchmark for object tracking in the wild. We provide more than 30K videos with more than 14 million dense bounding box annotations. Our dataset covers a wide selection of object classes in broad and diverse context. By releasing such a large-scale dataset, we expect deep trackers to further improve and generalize. In addition, we introduce a new benchmark composed of 500 novel videos, modeled with a distribution similar to our training dataset. By sequestering the annotation of the test set and providing an online evaluation server, we provide a fair benchmark for future development of object trackers. Deep trackers fine-tuned on a fraction of our dataset improve their performance by up to 1.6% on OTB100 and up to 1.7% on TrackingNet Test. We provide an extensive benchmark on TrackingNet by evaluating more than 20 trackers. Our results suggest that object tracking in the wild is far from being solved.

REAL-TIME VIDEO SCALING BASED ON CONVOLUTION NEURAL NETWORK ARCHITECTURE

Directory of Open Access Journals (Sweden)

S Safinaz

2017-08-01

Full Text Available In recent years, video super resolution techniques becomes mandatory requirements to get high resolution videos. Many super resolution techniques researched but still video super resolution or scaling is a vital challenge. In this paper, we have presented a real-time video scaling based on convolution neural network architecture to eliminate the blurriness in the images and video frames and to provide better reconstruction quality while scaling of large datasets from lower resolution frames to high resolution frames. We compare our outcomes with multiple exiting algorithms. Our extensive results of proposed technique RemCNN (Reconstruction error minimization Convolution Neural Network shows that our model outperforms the existing technologies such as bicubic, bilinear, MCResNet and provide better reconstructed motioning images and video frames. The experimental results shows that our average PSNR result is 47.80474 considering upscale-2, 41.70209 for upscale-3 and 36.24503 for upscale-4 for Myanmar dataset which is very high in contrast to other existing techniques. This results proves our proposed model real-time video scaling based on convolution neural network architecture’s high efficiency and better performance.

Full-motion video analysis for improved gender classification

Science.gov (United States)

Flora, Jeffrey B.; Lochtefeld, Darrell F.; Iftekharuddin, Khan M.

2014-06-01

The ability of computer systems to perform gender classification using the dynamic motion of the human subject has important applications in medicine, human factors, and human-computer interface systems. Previous works in motion analysis have used data from sensors (including gyroscopes, accelerometers, and force plates), radar signatures, and video. However, full-motion video, motion capture, range data provides a higher resolution time and spatial dataset for the analysis of dynamic motion. Works using motion capture data have been limited by small datasets in a controlled environment. In this paper, we explore machine learning techniques to a new dataset that has a larger number of subjects. Additionally, these subjects move unrestricted through a capture volume, representing a more realistic, less controlled environment. We conclude that existing linear classification methods are insufficient for the gender classification for larger dataset captured in relatively uncontrolled environment. A method based on a nonlinear support vector machine classifier is proposed to obtain gender classification for the larger dataset. In experimental testing with a dataset consisting of 98 trials (49 subjects, 2 trials per subject), classification rates using leave-one-out cross-validation are improved from 73% using linear discriminant analysis to 88% using the nonlinear support vector machine classifier.

Advanced video coding systems

CERN Document Server

Gao, Wen

2015-01-01

This comprehensive and accessible text/reference presents an overview of the state of the art in video coding technology. Specifically, the book introduces the tools of the AVS2 standard, describing how AVS2 can help to achieve a significant improvement in coding efficiency for future video networks and applications by incorporating smarter coding tools such as scene video coding. Topics and features: introduces the basic concepts in video coding, and presents a short history of video coding technology and standards; reviews the coding framework, main coding tools, and syntax structure of AV

Interactive visualization and analysis of multimodal datasets for surgical applications.

Science.gov (United States)

Kirmizibayrak, Can; Yim, Yeny; Wakid, Mike; Hahn, James

2012-12-01

Surgeons use information from multiple sources when making surgical decisions. These include volumetric datasets (such as CT, PET, MRI, and their variants), 2D datasets (such as endoscopic videos), and vector-valued datasets (such as computer simulations). Presenting all the information to the user in an effective manner is a challenging problem. In this paper, we present a visualization approach that displays the information from various sources in a single coherent view. The system allows the user to explore and manipulate volumetric datasets, display analysis of dataset values in local regions, combine 2D and 3D imaging modalities and display results of vector-based computer simulations. Several interaction methods are discussed: in addition to traditional interfaces including mouse and trackers, gesture-based natural interaction methods are shown to control these visualizations with real-time performance. An example of a medical application (medialization laryngoplasty) is presented to demonstrate how the combination of different modalities can be used in a surgical setting with our approach.

Perceptual video quality assessment in H.264 video coding standard using objective modeling.

Science.gov (United States)

Karthikeyan, Ramasamy; Sainarayanan, Gopalakrishnan; Deepa, Subramaniam Nachimuthu

2014-01-01

Since usage of digital video is wide spread nowadays, quality considerations have become essential, and industry demand for video quality measurement is rising. This proposal provides a method of perceptual quality assessment in H.264 standard encoder using objective modeling. For this purpose, quality impairments are calculated and a model is developed to compute the perceptual video quality metric based on no reference method. Because of the shuttle difference between the original video and the encoded video the quality of the encoded picture gets degraded, this quality difference is introduced by the encoding process like Intra and Inter prediction. The proposed model takes into account of the artifacts introduced by these spatial and temporal activities in the hybrid block based coding methods and an objective modeling of these artifacts into subjective quality estimation is proposed. The proposed model calculates the objective quality metric using subjective impairments; blockiness, blur and jerkiness compared to the existing bitrate only calculation defined in the ITU G 1070 model. The accuracy of the proposed perceptual video quality metrics is compared against popular full reference objective methods as defined by VQEG.

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

Blind prediction of natural video quality.

Science.gov (United States)

Saad, Michele A; Bovik, Alan C; Charrier, Christophe

2014-03-01

We propose a blind (no reference or NR) video quality evaluation model that is nondistortion specific. The approach relies on a spatio-temporal model of video scenes in the discrete cosine transform domain, and on a model that characterizes the type of motion occurring in the scenes, to predict video quality. We use the models to define video statistics and perceptual features that are the basis of a video quality assessment (VQA) algorithm that does not require the presence of a pristine video to compare against in order to predict a perceptual quality score. The contributions of this paper are threefold. 1) We propose a spatio-temporal natural scene statistics (NSS) model for videos. 2) We propose a motion model that quantifies motion coherency in video scenes. 3) We show that the proposed NSS and motion coherency models are appropriate for quality assessment of videos, and we utilize them to design a blind VQA algorithm that correlates highly with human judgments of quality. The proposed algorithm, called video BLIINDS, is tested on the LIVE VQA database and on the EPFL-PoliMi video database and shown to perform close to the level of top performing reduced and full reference VQA algorithms.

Reference dataset of volcanic ash physicochemical and optical properties for atmospheric measurement retrievals and transport modelling

Science.gov (United States)

Vogel, Andreas; Durant, Adam; Sytchkova, Anna; Diplas, Spyros; Bonadonna, Costanza; Scarnato, Barbara; Krüger, Kirstin; Kylling, Arve; Kristiansen, Nina; Stohl, Andreas

2016-04-01

Explosive volcanic eruptions emit up to 50 wt.% (total erupted mass) of fine ash particles (estimates of the volcanic source term and the nature of the constituent volcanic ash properties. Consequently, it is important to include a quantitative assessment of measurement uncertainties of ash properties to provide realistic ash forecast uncertainty. Currently, information on volcanic ash physicochemical and optical properties is derived from a small number of somewhat dated publications. In this study, we provide a reference dataset for physical (size distribution and shape), chemical (bulk vs. surface chemistry) and optical properties (complex refractive index in the UV-vis-NIR range) of a representative selection of volcanic ash samples from 10 different volcanic eruptions covering the full variability in silica content (40-75 wt.% SiO2). Through the combination of empirical analytical methods (e.g., image analysis, Energy Dispersive Spectroscopy, X-ray Photoelectron Spectroscopy, Transmission Electron Microscopy and UV/Vis/NIR/FTIR Spectroscopy) and theoretical models (e.g., Bruggeman effective medium approach), it was possible to fully capture the natural variability of ash physicochemical and optical characteristics. The dataset will be applied in atmospheric measurement retrievals and atmospheric transport modelling to determine the sensitivity to uncertainty in ash particle characteristics.

Human Pose Estimation and Activity Recognition from Multi-View Videos

DEFF Research Database (Denmark)

Holte, Michael Boelstoft; Tran, Cuong; Trivedi, Mohan

2012-01-01

approaches which have been proposed to comply with these requirements. We report a comparison of the most promising methods for multi-view human action recognition using two publicly available datasets: the INRIA Xmas Motion Acquisition Sequences (IXMAS) Multi-View Human Action Dataset, and the i3DPost Multi......–computer interaction (HCI), assisted living, gesture-based interactive games, intelligent driver assistance systems, movies, 3D TV and animation, physical therapy, autonomous mental development, smart environments, sport motion analysis, video surveillance, and video annotation. Next, we review and categorize recent......-View Human Action and Interaction Dataset. To compare the proposed methods, we give a qualitative assessment of methods which cannot be compared quantitatively, and analyze some prominent 3D pose estimation techniques for application, where not only the performed action needs to be identified but a more...

An unsupervised method for summarizing egocentric sport videos

Science.gov (United States)

Habibi Aghdam, Hamed; Jahani Heravi, Elnaz; Puig, Domenec

2015-12-01

People are getting more interested to record their sport activities using head-worn or hand-held cameras. This type of videos which is called egocentric sport videos has different motion and appearance patterns compared with life-logging videos. While a life-logging video can be defined in terms of well-defined human-object interactions, notwithstanding, it is not trivial to describe egocentric sport videos using well-defined activities. For this reason, summarizing egocentric sport videos based on human-object interaction might fail to produce meaningful results. In this paper, we propose an unsupervised method for summarizing egocentric videos by identifying the key-frames of the video. Our method utilizes both appearance and motion information and it automatically finds the number of the key-frames. Our blind user study on the new dataset collected from YouTube shows that in 93:5% cases, the users choose the proposed method as their first video summary choice. In addition, our method is within the top 2 choices of the users in 99% of studies.

Less Words, More Action: Using On-the-Fly Videos and Screenshots in Your Library's IM/Chat and Email Reference Transactions

Science.gov (United States)

Sekyere, Kwabena

2010-01-01

Email and chat/IM reference services have become a convenient and easily accessible option for the online community and libraries, particularly with increasing amounts of library resources now available electronically. This article gives an overview of Jing, which can be used to produce videos and screenshots on-the-fly, and demonstrates how to…

The right frame of reference makes it simple: an example of introductory mechanics supported by video analysis of motion

International Nuclear Information System (INIS)

Klein, P; Gröber, S; Kuhn, J; Fleischhauer, A; Müller, A

2015-01-01

The selection and application of coordinate systems is an important issue in physics. However, considering different frames of references in a given problem sometimes seems un-intuitive and is difficult for students. We present a concrete problem of projectile motion which vividly demonstrates the value of considering different frames of references. We use this example to explore the effectiveness of video-based motion analysis (VBMA) as an instructional technique at university level in enhancing students’ understanding of the abstract concept of coordinate systems. A pilot study with 47 undergraduate students indicates that VBMA instruction improves conceptual understanding of this issue. (paper)

The right frame of reference makes it simple: an example of introductory mechanics supported by video analysis of motion

Science.gov (United States)

Klein, P.; Gröber, S.; Kuhn, J.; Fleischhauer, A.; Müller, A.

2015-01-01

The selection and application of coordinate systems is an important issue in physics. However, considering different frames of references in a given problem sometimes seems un-intuitive and is difficult for students. We present a concrete problem of projectile motion which vividly demonstrates the value of considering different frames of references. We use this example to explore the effectiveness of video-based motion analysis (VBMA) as an instructional technique at university level in enhancing students’ understanding of the abstract concept of coordinate systems. A pilot study with 47 undergraduate students indicates that VBMA instruction improves conceptual understanding of this issue.

Camera network video summarization

Science.gov (United States)

Panda, Rameswar; Roy-Chowdhury, Amit K.

2017-05-01

Networks of vision sensors are deployed in many settings, ranging from security needs to disaster response to environmental monitoring. Many of these setups have hundreds of cameras and tens of thousands of hours of video. The difficulty of analyzing such a massive volume of video data is apparent whenever there is an incident that requires foraging through vast video archives to identify events of interest. As a result, video summarization, that automatically extract a brief yet informative summary of these videos, has attracted intense attention in the recent years. Much progress has been made in developing a variety of ways to summarize a single video in form of a key sequence or video skim. However, generating a summary from a set of videos captured in a multi-camera network still remains as a novel and largely under-addressed problem. In this paper, with the aim of summarizing videos in a camera network, we introduce a novel representative selection approach via joint embedding and capped l21-norm minimization. The objective function is two-fold. The first is to capture the structural relationships of data points in a camera network via an embedding, which helps in characterizing the outliers and also in extracting a diverse set of representatives. The second is to use a capped l21-norm to model the sparsity and to suppress the influence of data outliers in representative selection. We propose to jointly optimize both of the objectives, such that embedding can not only characterize the structure, but also indicate the requirements of sparse representative selection. Extensive experiments on standard multi-camera datasets well demonstrate the efficacy of our method over state-of-the-art methods.

Recognizing flu-like symptoms from videos.

Science.gov (United States)

Thi, Tuan Hue; Wang, Li; Ye, Ning; Zhang, Jian; Maurer-Stroh, Sebastian; Cheng, Li

2014-09-12

Vision-based surveillance and monitoring is a potential alternative for early detection of respiratory disease outbreaks in urban areas complementing molecular diagnostics and hospital and doctor visit-based alert systems. Visible actions representing typical flu-like symptoms include sneeze and cough that are associated with changing patterns of hand to head distances, among others. The technical difficulties lie in the high complexity and large variation of those actions as well as numerous similar background actions such as scratching head, cell phone use, eating, drinking and so on. In this paper, we make a first attempt at the challenging problem of recognizing flu-like symptoms from videos. Since there was no related dataset available, we created a new public health dataset for action recognition that includes two major flu-like symptom related actions (sneeze and cough) and a number of background actions. We also developed a suitable novel algorithm by introducing two types of Action Matching Kernels, where both types aim to integrate two aspects of local features, namely the space-time layout and the Bag-of-Words representations. In particular, we show that the Pyramid Match Kernel and Spatial Pyramid Matching are both special cases of our proposed kernels. Besides experimenting on standard testbed, the proposed algorithm is evaluated also on the new sneeze and cough set. Empirically, we observe that our approach achieves competitive performance compared to the state-of-the-arts, while recognition on the new public health dataset is shown to be a non-trivial task even with simple single person unobstructed view. Our sneeze and cough video dataset and newly developed action recognition algorithm is the first of its kind and aims to kick-start the field of action recognition of flu-like symptoms from videos. It will be challenging but necessary in future developments to consider more complex real-life scenario of detecting these actions simultaneously from

Video Game Structural Characteristics: A New Psychological Taxonomy

Science.gov (United States)

King, Daniel; Delfabbro, Paul; Griffiths, Mark

2010-01-01

Excessive video game playing behaviour may be influenced by a variety of factors including the structural characteristics of video games. Structural characteristics refer to those features inherent within the video game itself that may facilitate initiation, development and maintenance of video game playing over time. Numerous structural…

High efficiency video coding coding tools and specification

CERN Document Server

Wien, Mathias

2015-01-01

The video coding standard High Efficiency Video Coding (HEVC) targets at improved compression performance for video resolutions of HD and beyond, providing Ultra HD video at similar compressed bit rates as for HD video encoded with the well-established video coding standard H.264 | AVC. Based on known concepts, new coding structures and improved coding tools have been developed and specified in HEVC. The standard is expected to be taken up easily by established industry as well as new endeavors, answering the needs of todays connected and ever-evolving online world. This book presents the High Efficiency Video Coding standard and explains it in a clear and coherent language. It provides a comprehensive and consistently written description, all of a piece. The book targets at both, newbies to video coding as well as experts in the field. While providing sections with introductory text for the beginner, it suits as a well-arranged reference book for the expert. The book provides a comprehensive reference for th...

GPM GROUND VALIDATION PRECIPITATION VIDEO IMAGER (PVI) GCPEX V1

Data.gov (United States)

National Aeronautics and Space Administration — The GPM Ground Validation Precipitation Video Imager (PVI) GCPEx dataset collected precipitation particle images and drop size distribution data from November 2011...

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.

Real-time Multiple Abnormality Detection in Video Data

DEFF Research Database (Denmark)

Have, Simon Hartmann; Ren, Huamin; Moeslund, Thomas B.

2013-01-01

Automatic abnormality detection in video sequences has recently gained an increasing attention within the research community. Although progress has been seen, there are still some limitations in current research. While most systems are designed at detecting specific abnormality, others which...... are capable of detecting more than two types of abnormalities rely on heavy computation. Therefore, we provide a framework for detecting abnormalities in video surveillance by using multiple features and cascade classifiers, yet achieve above real-time processing speed. Experimental results on two datasets...... show that the proposed framework can reliably detect abnormalities in the video sequence, outperforming the current state-of-the-art methods....

Violent Interaction Detection in Video Based on Deep Learning

Science.gov (United States)

Zhou, Peipei; Ding, Qinghai; Luo, Haibo; Hou, Xinglin

2017-06-01

Violent interaction detection is of vital importance in some video surveillance scenarios like railway stations, prisons or psychiatric centres. Existing vision-based methods are mainly based on hand-crafted features such as statistic features between motion regions, leading to a poor adaptability to another dataset. En lightened by the development of convolutional networks on common activity recognition, we construct a FightNet to represent the complicated visual violence interaction. In this paper, a new input modality, image acceleration field is proposed to better extract the motion attributes. Firstly, each video is framed as RGB images. Secondly, optical flow field is computed using the consecutive frames and acceleration field is obtained according to the optical flow field. Thirdly, the FightNet is trained with three kinds of input modalities, i.e., RGB images for spatial networks, optical flow images and acceleration images for temporal networks. By fusing results from different inputs, we conclude whether a video tells a violent event or not. To provide researchers a common ground for comparison, we have collected a violent interaction dataset (VID), containing 2314 videos with 1077 fight ones and 1237 no-fight ones. By comparison with other algorithms, experimental results demonstrate that the proposed model for violent interaction detection shows higher accuracy and better robustness.

The Effect of Motion Analysis Activities in a Video-Based Laboratory in Students' Understanding of Position, Velocity and Frames of Reference

Science.gov (United States)

Koleza, Eugenia; Pappas, John

2008-01-01

In this article, we present the results of a qualitative research project on the effect of motion analysis activities in a Video-Based Laboratory (VBL) on students' understanding of position, velocity and frames of reference. The participants in our research were 48 pre-service teachers enrolled in Education Departments with no previous strong…

High End Visualization of Geophysical Datasets Using Immersive Technology: The SIO Visualization Center.

Science.gov (United States)

Newman, R. L.

2002-12-01

How many images can you display at one time with Power Point without getting "postage stamps"? Do you have fantastic datasets that you cannot view because your computer is too slow/small? Do you assume a few 2-D images of a 3-D picture are sufficient? High-end visualization centers can minimize and often eliminate these problems. The new visualization center [http://siovizcenter.ucsd.edu] at Scripps Institution of Oceanography [SIO] immerses users into a virtual world by projecting 3-D images onto a Panoram GVR-120E wall-sized floor-to-ceiling curved screen [7' x 23'] that has 3.2 mega-pixels of resolution. The Infinite Reality graphics subsystem is driven by a single-pipe SGI Onyx 3400 with a system bandwidth of 44 Gbps. The Onyx is powered by 16 MIPS R12K processors and 16 GB of addressable memory. The system is also equipped with transmitters and LCD shutter glasses which permit stereographic 3-D viewing of high-resolution images. This center is ideal for groups of up to 60 people who can simultaneously view these large-format images. A wide range of hardware and software is available, giving the users a totally immersive working environment in which to display, analyze, and discuss large datasets. The system enables simultaneous display of video and audio streams from sources such as SGI megadesktop and stereo megadesktop, S-VHS video, DVD video, and video from a Macintosh or PC. For instance, one-third of the screen might be displaying S-VHS video from a remotely-operated-vehicle [ROV], while the remaining portion of the screen might be used for an interactive 3-D flight over the same parcel of seafloor. The video and audio combinations using this system are numerous, allowing users to combine and explore data and images in innovative ways, greatly enhancing scientists' ability to visualize, understand and collaborate on complex datasets. In the not-distant future, with the rapid growth in networking speeds in the US, it will be possible for Earth Sciences

Legal drug content in music video programs shown on Australian television on saturday mornings.

Science.gov (United States)

Johnson, Rebecca; Croager, Emma; Pratt, Iain S; Khoo, Natalie

2013-01-01

To examine the extent to which legal drug references (alcohol and tobacco) are present in the music video clips shown on two music video programs broadcast in Australia on Saturday mornings. Further, to examine the music genres in which the references appeared and the dominant messages associated with the references. Music video clips shown on the music video programs 'Rage' (ABC TV) and [V] 'Music Video Chart' (Channel [V]) were viewed over 8 weeks from August 2011 to October 2011 and the number of clips containing verbal and/or visual drug references in each program was counted. The songs were classified by genre and the dominant messages associated with drug references were also classified and analysed. A considerable proportion of music videos (approximately one-third) contained drug references. Alcohol featured in 95% of the music videos that contained drug references. References to alcohol generally associated it with fun and humour, and alcohol and tobacco were both overwhelmingly presented in contexts that encouraged, rather than discouraged, their use. In Australia, Saturday morning is generally considered a children's television viewing timeslot, and several broadcaster Codes of Practice dictate that programs shown on Saturday mornings must be appropriate for viewing by audiences of all ages. Despite this, our findings show that music video programs aired on Saturday mornings contain a considerable level of drug-related content.

Creating a streaming video collection for your library

CERN Document Server

Duncan, Cheryl J

2014-01-01

Creating a Streaming Video Collection for Your Library covers the main processes associated with streaming video, from licensing to access and evaluation, and will serve as a key reference and source of best practices for libraries adding streaming video titles to their collections.

GRIP: A web-based system for constructing Gold Standard datasets for protein-protein interaction prediction

Directory of Open Access Journals (Sweden)

Zheng Huiru

2009-01-01

Full Text Available Abstract Background Information about protein interaction networks is fundamental to understanding protein function and cellular processes. Interaction patterns among proteins can suggest new drug targets and aid in the design of new therapeutic interventions. Efforts have been made to map interactions on a proteomic-wide scale using both experimental and computational techniques. Reference datasets that contain known interacting proteins (positive cases and non-interacting proteins (negative cases are essential to support computational prediction and validation of protein-protein interactions. Information on known interacting and non interacting proteins are usually stored within databases. Extraction of these data can be both complex and time consuming. Although, the automatic construction of reference datasets for classification is a useful resource for researchers no public resource currently exists to perform this task. Results GRIP (Gold Reference dataset constructor from Information on Protein complexes is a web-based system that provides researchers with the functionality to create reference datasets for protein-protein interaction prediction in Saccharomyces cerevisiae. Both positive and negative cases for a reference dataset can be extracted, organised and downloaded by the user. GRIP also provides an upload facility whereby users can submit proteins to determine protein complex membership. A search facility is provided where a user can search for protein complex information in Saccharomyces cerevisiae. Conclusion GRIP is developed to retrieve information on protein complex, cellular localisation, and physical and genetic interactions in Saccharomyces cerevisiae. Manual construction of reference datasets can be a time consuming process requiring programming knowledge. GRIP simplifies and speeds up this process by allowing users to automatically construct reference datasets. GRIP is free to access at http://rosalind.infj.ulst.ac.uk/GRIP/.

Deep hierarchical attention network for video description

Science.gov (United States)

Li, Shuohao; Tang, Min; Zhang, Jun

2018-03-01

Pairing video to natural language description remains a challenge in computer vision and machine translation. Inspired by image description, which uses an encoder-decoder model for reducing visual scene into a single sentence, we propose a deep hierarchical attention network for video description. The proposed model uses convolutional neural network (CNN) and bidirectional LSTM network as encoders while a hierarchical attention network is used as the decoder. Compared to encoder-decoder models used in video description, the bidirectional LSTM network can capture the temporal structure among video frames. Moreover, the hierarchical attention network has an advantage over single-layer attention network on global context modeling. To make a fair comparison with other methods, we evaluate the proposed architecture with different types of CNN structures and decoders. Experimental results on the standard datasets show that our model has a more superior performance than the state-of-the-art techniques.

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.

CAMEX-4 NOAA WP-3D VIDEO V1

Data.gov (United States)

National Aeronautics and Space Administration — The CAMEX-4 NOAA WP-3D Video dataset was collected during the fourth field campaign in the CAMEX series (CAMEX-4), which ran from 16 August to 25 September, 2001 and...

Comparison of CORA and EN4 in-situ datasets validation methods, toward a better quality merged dataset.

Science.gov (United States)

Szekely, Tanguy; Killick, Rachel; Gourrion, Jerome; Reverdin, Gilles

2017-04-01

CORA and EN4 are both global delayed time mode validated in-situ ocean temperature and salinity datasets distributed by the Met Office (http://www.metoffice.gov.uk/) and Copernicus (www.marine.copernicus.eu). A large part of the profiles distributed by CORA and EN4 in recent years are Argo profiles from the ARGO DAC, but profiles are also extracted from the World Ocean Database and TESAC profiles from GTSPP. In the case of CORA, data coming from the EUROGOOS Regional operationnal oserving system( ROOS) operated by European institutes no managed by National Data Centres and other datasets of profiles povided by scientific sources can also be found (Sea mammals profiles from MEOP, XBT datasets from cruises ...). (EN4 also takes data from the ASBO dataset to supplement observations in the Arctic). First advantage of this new merge product is to enhance the space and time coverage at global and european scales for the period covering 1950 till a year before the current year. This product is updated once a year and T&S gridded fields are alos generated for the period 1990-year n-1. The enhancement compared to the revious CORA product will be presented Despite the fact that the profiles distributed by both datasets are mostly the same, the quality control procedures developed by the Met Office and Copernicus teams differ, sometimes leading to different quality control flags for the same profile. Started in 2016 a new study started that aims to compare both validation procedures to move towards a Copernicus Marine Service dataset with the best features of CORA and EN4 validation.A reference data set composed of the full set of in-situ temperature and salinity measurements collected by Coriolis during 2015 is used. These measurements have been made thanks to wide range of instruments (XBTs, CTDs, Argo floats, Instrumented sea mammals,...), covering the global ocean. The reference dataset has been validated simultaneously by both teams.An exhaustive comparison of the

A synthetic dataset for evaluating soft and hard fusion algorithms

Science.gov (United States)

Graham, Jacob L.; Hall, David L.; Rimland, Jeffrey

2011-06-01

There is an emerging demand for the development of data fusion techniques and algorithms that are capable of combining conventional "hard" sensor inputs such as video, radar, and multispectral sensor data with "soft" data including textual situation reports, open-source web information, and "hard/soft" data such as image or video data that includes human-generated annotations. New techniques that assist in sense-making over a wide range of vastly heterogeneous sources are critical to improving tactical situational awareness in counterinsurgency (COIN) and other asymmetric warfare situations. A major challenge in this area is the lack of realistic datasets available for test and evaluation of such algorithms. While "soft" message sets exist, they tend to be of limited use for data fusion applications due to the lack of critical message pedigree and other metadata. They also lack corresponding hard sensor data that presents reasonable "fusion opportunities" to evaluate the ability to make connections and inferences that span the soft and hard data sets. This paper outlines the design methodologies, content, and some potential use cases of a COIN-based synthetic soft and hard dataset created under a United States Multi-disciplinary University Research Initiative (MURI) program funded by the U.S. Army Research Office (ARO). The dataset includes realistic synthetic reports from a variety of sources, corresponding synthetic hard data, and an extensive supporting database that maintains "ground truth" through logical grouping of related data into "vignettes." The supporting database also maintains the pedigree of messages and other critical metadata.

Video content analysis of surgical procedures.

Science.gov (United States)

Loukas, Constantinos

2018-02-01

In addition to its therapeutic benefits, minimally invasive surgery offers the potential for video recording of the operation. The videos may be archived and used later for reasons such as cognitive training, skills assessment, and workflow analysis. Methods from the major field of video content analysis and representation are increasingly applied in the surgical domain. In this paper, we review recent developments and analyze future directions in the field of content-based video analysis of surgical operations. The review was obtained from PubMed and Google Scholar search on combinations of the following keywords: 'surgery', 'video', 'phase', 'task', 'skills', 'event', 'shot', 'analysis', 'retrieval', 'detection', 'classification', and 'recognition'. The collected articles were categorized and reviewed based on the technical goal sought, type of surgery performed, and structure of the operation. A total of 81 articles were included. The publication activity is constantly increasing; more than 50% of these articles were published in the last 3 years. Significant research has been performed for video task detection and retrieval in eye surgery. In endoscopic surgery, the research activity is more diverse: gesture/task classification, skills assessment, tool type recognition, shot/event detection and retrieval. Recent works employ deep neural networks for phase and tool recognition as well as shot detection. Content-based video analysis of surgical operations is a rapidly expanding field. Several future prospects for research exist including, inter alia, shot boundary detection, keyframe extraction, video summarization, pattern discovery, and video annotation. The development of publicly available benchmark datasets to evaluate and compare task-specific algorithms is essential.

Applied learning-based color tone mapping for face recognition in video surveillance system

Science.gov (United States)

Yew, Chuu Tian; Suandi, Shahrel Azmin

2012-04-01

In this paper, we present an applied learning-based color tone mapping technique for video surveillance system. This technique can be applied onto both color and grayscale surveillance images. The basic idea is to learn the color or intensity statistics from a training dataset of photorealistic images of the candidates appeared in the surveillance images, and remap the color or intensity of the input image so that the color or intensity statistics match those in the training dataset. It is well known that the difference in commercial surveillance cameras models, and signal processing chipsets used by different manufacturers will cause the color and intensity of the images to differ from one another, thus creating additional challenges for face recognition in video surveillance system. Using Multi-Class Support Vector Machines as the classifier on a publicly available video surveillance camera database, namely SCface database, this approach is validated and compared to the results of using holistic approach on grayscale images. The results show that this technique is suitable to improve the color or intensity quality of video surveillance system for face recognition.

U.S. Climate Divisional Dataset (Version Superseded)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data has been superseded by a newer version of the dataset. Please refer to NOAA's Climate Divisional Database for more information. The U.S. Climate Divisional...

GPM GROUND VALIDATION TWO-DIMENSIONAL VIDEO DISDROMETER (2DVD) IPHEX V1

Data.gov (United States)

National Aeronautics and Space Administration — The GPM Ground Validation Two-Dimensional Video Disdrometer (2DVD) IPHEx dataset was collected during the GPM Ground Validation Integrated Precipitation and...

Intra prediction using face continuity in 360-degree video coding

Science.gov (United States)

Hanhart, Philippe; He, Yuwen; Ye, Yan

2017-09-01

This paper presents a new reference sample derivation method for intra prediction in 360-degree video coding. Unlike the conventional reference sample derivation method for 2D video coding, which uses the samples located directly above and on the left of the current block, the proposed method considers the spherical nature of 360-degree video when deriving reference samples located outside the current face to which the block belongs, and derives reference samples that are geometric neighbors on the sphere. The proposed reference sample derivation method was implemented in the Joint Exploration Model 3.0 (JEM-3.0) for the cubemap projection format. Simulation results for the all intra configuration show that, when compared with the conventional reference sample derivation method, the proposed method gives, on average, luma BD-rate reduction of 0.3% in terms of the weighted spherical PSNR (WS-PSNR) and spherical PSNR (SPSNR) metrics.

Two-Stream Transformer Networks for Video-based Face Alignment.

Science.gov (United States)

Liu, Hao; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie

2017-08-01

In this paper, we propose a two-stream transformer networks (TSTN) approach for video-based face alignment. Unlike conventional image-based face alignment approaches which cannot explicitly model the temporal dependency in videos and motivated by the fact that consistent movements of facial landmarks usually occur across consecutive frames, our TSTN aims to capture the complementary information of both the spatial appearance on still frames and the temporal consistency information across frames. To achieve this, we develop a two-stream architecture, which decomposes the video-based face alignment into spatial and temporal streams accordingly. Specifically, the spatial stream aims to transform the facial image to the landmark positions by preserving the holistic facial shape structure. Accordingly, the temporal stream encodes the video input as active appearance codes, where the temporal consistency information across frames is captured to help shape refinements. Experimental results on the benchmarking video-based face alignment datasets show very competitive performance of our method in comparisons to the state-of-the-arts.

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.

Fast Aerial Video Stitching

Directory of Open Access Journals (Sweden)

Jing Li

2014-10-01

Full Text Available The highly efficient and robust stitching of aerial video captured by unmanned aerial vehicles (UAVs is a challenging problem in the field of robot vision. Existing commercial image stitching systems have seen success with offline stitching tasks, but they cannot guarantee high-speed performance when dealing with online aerial video sequences. In this paper, we present a novel system which has an unique ability to stitch high-frame rate aerial video at a speed of 150 frames per second (FPS. In addition, rather than using a high-speed vision platform such as FPGA or CUDA, our system is running on a normal personal computer. To achieve this, after the careful comparison of the existing invariant features, we choose the FAST corner and binary descriptor for efficient feature extraction and representation, and present a spatial and temporal coherent filter to fuse the UAV motion information into the feature matching. The proposed filter can remove the majority of feature correspondence outliers and significantly increase the speed of robust feature matching by up to 20 times. To achieve a balance between robustness and efficiency, a dynamic key frame-based stitching framework is used to reduce the accumulation errors. Extensive experiments on challenging UAV datasets demonstrate that our approach can break through the speed limitation and generate an accurate stitching image for aerial video stitching tasks.

2001 – 2010 Danish Design Reference Year

DEFF Research Database (Denmark)

Grunnet Wang, Peter; Scharling, Mikael; Pagh Nielsen, Kristian

This report presents the Danish Design Reference Year based on observed data from 2001 – 2010. In various sectors - i.e. building and construction, energy, etc. - the climate and weather usually plays a part in a given project. The Danish Design Reference Year dataset is a collection of data series...... for eleven specific parameters, that each represents a typical year in Denmark. The uses of the dataset may vary from simulations to statistical analysis, graphical overviews etc. The Danish land areas have been sectionalized into five to six climatological zones depending on the parameter, each...... characterized by distinct diurnal and yearly variations. The dataset consists of observed data from one station located within and representing each zone. In addition to the complete Danish Design Reference Year dataset, a subset specifically selected to be used for energy performance calculations for obtaining...

Reference values for paediatric pulmonary function testing: The Utrecht dataset.

Science.gov (United States)

Koopman, Marije; Zanen, Pieter; Kruitwagen, Cas L J J; van der Ent, Cornelis K; Arets, Hubertus G M

2011-01-01

Since populations evolve, measurement protocols and equipment improve and analysis techniques progress, there is an ongoing need to reassess reference data for pulmonary function tests. Furthermore, reference values for total lung capacity and carbon monoxide diffusion capacity are scarcely available in children. We aimed to provide updated reference equations for most commonly used pulmonary function indices in Caucasian children. In the 'Utrecht Pulmonary Function Reference Data Study' we collected data in Caucasian children aged 2-18 years. We analyzed them using the 'Generalized Additive Models for Location Scale and Shape' (GAMLSS) statistical method. Measurements of interrupter resistance (R(int)) (n = 877), spirometry (n = 1042), body plethysmography (n = 723) and carbon monoxide diffusion/helium dilution (n = 543) were obtained in healthy children. Height (or the natural logarithm of height) and age (or the natural logarithm of age) were both significantly related to most outcome measures. Also sex was a significant determinant, except for RV, RV/TLC, FRC(pleth), Raw(0,5), Raw(tot), R(int) and FEF values. The application of previously published reference equations on the study population resulted in misinterpretation of pulmonary function. These new paediatric reference equations provide accurate estimates of the range of normality for most commonly used pulmonary function indices, resulting in less underdiagnosis and overdiagnosis of pulmonary diseases. Copyright © 2010 Elsevier Ltd. All rights reserved.

Subjective Quality Assessment of H.264/AVC Video Streaming with Packet Losses

Directory of Open Access Journals (Sweden)

Naccari Matteo

2011-01-01

Full Text Available Research in the field of video quality assessment relies on the availability of subjective scores, collected by means of experiments in which groups of people are asked to rate the quality of video sequences. The availability of subjective scores is fundamental to enable validation and comparative benchmarking of the objective algorithms that try to predict human perception of video quality by automatically analyzing the video sequences, in a way to support reproducible and reliable research results. In this paper, a publicly available database of subjective quality scores and corrupted video sequences is described. The scores refer to 156 sequences at CIF and 4CIF spatial resolutions, encoded with H.264/AVC and corrupted by simulating the transmission over an error-prone network. The subjective evaluation has been performed by 40 subjects at the premises of two academic institutions, in standard-compliant controlled environments. In order to support reproducible research in the field of full-reference, reduced-reference, and no-reference video quality assessment algorithms, both the uncompressed files and the H.264/AVC bitstreams, as well as the packet loss patterns, have been made available to the research community.

GPM GROUND VALIDATION TWO-DIMENSIONAL VIDEO DISDROMETER (2DVD) IFLOODS V1

Data.gov (United States)

National Aeronautics and Space Administration — The GPM Ground Validation Two-Dimensional Video Disdrometer (2DVD) IFloodS dataset was collected during the GPM Ground Validation Iowa Flood Studies (IFloodS) field...

ActivityNet: A Large-Scale Video Benchmark for Human Activity Understanding

KAUST Repository

Heilbron, Fabian Caba

2015-06-02

In spite of many dataset efforts for human action recognition, current computer vision algorithms are still severely limited in terms of the variability and complexity of the actions that they can recognize. This is in part due to the simplicity of current benchmarks, which mostly focus on simple actions and movements occurring on manually trimmed videos. In this paper we introduce ActivityNet, a new largescale video benchmark for human activity understanding. Our benchmark aims at covering a wide range of complex human activities that are of interest to people in their daily living. In its current version, ActivityNet provides samples from 203 activity classes with an average of 137 untrimmed videos per class and 1.41 activity instances per video, for a total of 849 video hours. We illustrate three scenarios in which ActivityNet can be used to compare algorithms for human activity understanding: untrimmed video classification, trimmed activity classification and activity detection.

ActivityNet: A Large-Scale Video Benchmark for Human Activity Understanding

KAUST Repository

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

2015-01-01

In spite of many dataset efforts for human action recognition, current computer vision algorithms are still severely limited in terms of the variability and complexity of the actions that they can recognize. This is in part due to the simplicity of current benchmarks, which mostly focus on simple actions and movements occurring on manually trimmed videos. In this paper we introduce ActivityNet, a new largescale video benchmark for human activity understanding. Our benchmark aims at covering a wide range of complex human activities that are of interest to people in their daily living. In its current version, ActivityNet provides samples from 203 activity classes with an average of 137 untrimmed videos per class and 1.41 activity instances per video, for a total of 849 video hours. We illustrate three scenarios in which ActivityNet can be used to compare algorithms for human activity understanding: untrimmed video classification, trimmed activity classification and activity detection.

Performance comparison of AV1, HEVC, and JVET video codecs on 360 (spherical) video

Science.gov (United States)

Topiwala, Pankaj; Dai, Wei; Krishnan, Madhu; Abbas, Adeel; Doshi, Sandeep; Newman, David

2017-09-01

This paper compares the coding efficiency performance on 360 videos, of three software codecs: (a) AV1 video codec from the Alliance for Open Media (AOM); (b) the HEVC Reference Software HM; and (c) the JVET JEM Reference SW. Note that 360 video is especially challenging content, in that one codes full res globally, but typically looks locally (in a viewport), which magnifies errors. These are tested in two different projection formats ERP and RSP, to check consistency. Performance is tabulated for 1-pass encoding on two fronts: (1) objective performance based on end-to-end (E2E) metrics such as SPSNR-NN, and WS-PSNR, currently developed in the JVET committee; and (2) informal subjective assessment of static viewports. Constant quality encoding is performed with all the three codecs for an unbiased comparison of the core coding tools. Our general conclusion is that under constant quality coding, AV1 underperforms HEVC, which underperforms JVET. We also test with rate control, where AV1 currently underperforms the open source X265 HEVC codec. Objective and visual evidence is provided.

Geoseq: a tool for dissecting deep-sequencing datasets

Directory of Open Access Journals (Sweden)

Homann Robert

2010-10-01

Full Text Available Abstract Background Datasets generated on deep-sequencing platforms have been deposited in various public repositories such as the Gene Expression Omnibus (GEO, Sequence Read Archive (SRA hosted by the NCBI, or the DNA Data Bank of Japan (ddbj. Despite being rich data sources, they have not been used much due to the difficulty in locating and analyzing datasets of interest. Results Geoseq http://geoseq.mssm.edu provides a new method of analyzing short reads from deep sequencing experiments. Instead of mapping the reads to reference genomes or sequences, Geoseq maps a reference sequence against the sequencing data. It is web-based, and holds pre-computed data from public libraries. The analysis reduces the input sequence to tiles and measures the coverage of each tile in a sequence library through the use of suffix arrays. The user can upload custom target sequences or use gene/miRNA names for the search and get back results as plots and spreadsheet files. Geoseq organizes the public sequencing data using a controlled vocabulary, allowing identification of relevant libraries by organism, tissue and type of experiment. Conclusions Analysis of small sets of sequences against deep-sequencing datasets, as well as identification of public datasets of interest, is simplified by Geoseq. We applied Geoseq to, a identify differential isoform expression in mRNA-seq datasets, b identify miRNAs (microRNAs in libraries, and identify mature and star sequences in miRNAS and c to identify potentially mis-annotated miRNAs. The ease of using Geoseq for these analyses suggests its utility and uniqueness as an analysis tool.

Review of Interactive Video--Romanian Project Proposal

Science.gov (United States)

Onita, Mihai; Petan, Sorin; Vasiu, Radu

2016-01-01

In the recent years, the globalization and massification of video education offer involved more and more eLearning scenarios within universities. This article refers to interactive video and proposes an overview of it. We analyze the background information, regarding the eLearning campus used in virtual universities around the world, the MOOC…

Video astronomy on the go using video cameras with small telescopes

CERN Document Server

Ashley, Joseph

2017-01-01

Author Joseph Ashley explains video astronomy's many benefits in this comprehensive reference guide for amateurs. Video astronomy offers a wonderful way to see objects in far greater detail than is possible through an eyepiece, and the ability to use the modern, entry-level video camera to image deep space objects is a wonderful development for urban astronomers in particular, as it helps sidestep the issue of light pollution. The author addresses both the positive attributes of these cameras for deep space imaging as well as the limitations, such as amp glow. The equipment needed for imaging as well as how it is configured is identified with hook-up diagrams and photographs. Imaging techniques are discussed together with image processing (stacking and image enhancement). Video astronomy has evolved to offer great results and great ease of use, and both novices and more experienced amateurs can use this book to find the set-up that works best for them. Flexible and portable, they open up a whole new way...

Video2vec Embeddings Recognize Events When Examples Are Scarce.

Science.gov (United States)

Habibian, Amirhossein; Mensink, Thomas; Snoek, Cees G M

2017-10-01

This paper aims for event recognition when video examples are scarce or even completely absent. The key in such a challenging setting is a semantic video representation. Rather than building the representation from individual attribute detectors and their annotations, we propose to learn the entire representation from freely available web videos and their descriptions using an embedding between video features and term vectors. In our proposed embedding, which we call Video2vec, the correlations between the words are utilized to learn a more effective representation by optimizing a joint objective balancing descriptiveness and predictability. We show how learning the Video2vec embedding using a multimodal predictability loss, including appearance, motion and audio features, results in a better predictable representation. We also propose an event specific variant of Video2vec to learn a more accurate representation for the words, which are indicative of the event, by introducing a term sensitive descriptiveness loss. Our experiments on three challenging collections of web videos from the NIST TRECVID Multimedia Event Detection and Columbia Consumer Videos datasets demonstrate: i) the advantages of Video2vec over representations using attributes or alternative embeddings, ii) the benefit of fusing video modalities by an embedding over common strategies, iii) the complementarity of term sensitive descriptiveness and multimodal predictability for event recognition. By its ability to improve predictability of present day audio-visual video features, while at the same time maximizing their semantic descriptiveness, Video2vec leads to state-of-the-art accuracy for both few- and zero-example recognition of events in video.

Spatial data processing for the purpose of video games

Directory of Open Access Journals (Sweden)

Chądzyńska Dominika

2016-03-01

Full Text Available Advanced terrain models are currently commonly used in many video/computers games. Professional GIS technologies, existing spatial datasets and cartographic methodology are more widely used in their development. This allows for achieving a realistic model of the world. On the other hand, the so-called game engines have very high capability of spatial data visualization. Preparing terrain models for the purpose of video games requires knowledge and experience of GIS specialists and cartographers, although it is also accessible for non-professionals. The authors point out commonness and variety of use of terrain models in video games and the existence of a series of ready, advanced tools and procedures of terrain model creating. Finally the authors describe the experiment of performing the process of data modeling for “Condor Soar Simulator”.

The 3D Reference Earth Model: Status and Preliminary Results

Science.gov (United States)

Moulik, P.; Lekic, V.; Romanowicz, B. A.

2017-12-01

In the 20th century, seismologists constructed models of how average physical properties (e.g. density, rigidity, compressibility, anisotropy) vary with depth in the Earth's interior. These one-dimensional (1D) reference Earth models (e.g. PREM) have proven indispensable in earthquake location, imaging of interior structure, understanding material properties under extreme conditions, and as a reference in other fields, such as particle physics and astronomy. Over the past three decades, new datasets motivated more sophisticated efforts that yielded models of how properties vary both laterally and with depth in the Earth's interior. Though these three-dimensional (3D) models exhibit compelling similarities at large scales, differences in the methodology, representation of structure, and dataset upon which they are based, have prevented the creation of 3D community reference models. As part of the REM-3D project, we are compiling and reconciling reference seismic datasets of body wave travel-time measurements, fundamental mode and overtone surface wave dispersion measurements, and normal mode frequencies and splitting functions. These reference datasets are being inverted for a long-wavelength, 3D reference Earth model that describes the robust long-wavelength features of mantle heterogeneity. As a community reference model with fully quantified uncertainties and tradeoffs and an associated publically available dataset, REM-3D will facilitate Earth imaging studies, earthquake characterization, inferences on temperature and composition in the deep interior, and be of improved utility to emerging scientific endeavors, such as neutrino geoscience. Here, we summarize progress made in the construction of the reference long period dataset and present a preliminary version of REM-3D in the upper-mantle. In order to determine the level of detail warranted for inclusion in REM-3D, we analyze the spectrum of discrepancies between models inverted with different subsets of the

PROVIDING GEOGRAPHIC DATASETS AS LINKED DATA IN SDI

Directory of Open Access Journals (Sweden)

E. Hietanen

2016-06-01

Full Text Available In this study, a prototype service to provide data from Web Feature Service (WFS as linked data is implemented. At first, persistent and unique Uniform Resource Identifiers (URI are created to all spatial objects in the dataset. The objects are available from those URIs in Resource Description Framework (RDF data format. Next, a Web Ontology Language (OWL ontology is created to describe the dataset information content using the Open Geospatial Consortium’s (OGC GeoSPARQL vocabulary. The existing data model is modified in order to take into account the linked data principles. The implemented service produces an HTTP response dynamically. The data for the response is first fetched from existing WFS. Then the Geographic Markup Language (GML format output of the WFS is transformed on-the-fly to the RDF format. Content Negotiation is used to serve the data in different RDF serialization formats. This solution facilitates the use of a dataset in different applications without replicating the whole dataset. In addition, individual spatial objects in the dataset can be referred with URIs. Furthermore, the needed information content of the objects can be easily extracted from the RDF serializations available from those URIs. A solution for linking data objects to the dataset URI is also introduced by using the Vocabulary of Interlinked Datasets (VoID. The dataset is divided to the subsets and each subset is given its persistent and unique URI. This enables the whole dataset to be explored with a web browser and all individual objects to be indexed by search engines.

Action Search: Learning to Search for Human Activities in Untrimmed Videos

KAUST Repository

Alwassel, Humam

2017-06-13

Traditional approaches for action detection use trimmed data to learn sophisticated action detector models. Although these methods have achieved great success at detecting human actions, we argue that huge information is discarded when ignoring the process, through which this trimmed data is obtained. In this paper, we propose Action Search, a novel approach that mimics the way people annotate activities in video sequences. Using a Recurrent Neural Network, Action Search can efficiently explore a video and determine the time boundaries during which an action occurs. Experiments on the THUMOS14 dataset reveal that our model is not only able to explore the video efficiently but also accurately find human activities, outperforming state-of-the-art methods.

Video-Aided GPS/INS Positioning and Attitude Determination

National Research Council Canada - National Science Library

Brown, Alison; Silva, Randy

2006-01-01

... precise positioning and attitude information to be maintained, even during periods of extended GPS dropouts. This relies on information extracted from the video images of reference points and features to continue to update the inertial navigation solution. In this paper, the principles of the video-update method aredescribed.

Video game playing as a risk factor in adolescence?

OpenAIRE

Lysý, Jan

2013-01-01

Diploma thesis "Video game playing as a risk factor in adolescence?" deals with actuality of risks for children and youth linked to video games. This topic is currently intensively disscused because of cases of high school shootings. There are concerns that violence in video games is connected to rising of children and youth violence. Another risks refered to video games are addiction and obesity. This diploma thesis deals with these risk too. Goal of this thesis is find out if these risks ar...

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.

Fall Detection for Elderly from Partially Observed Depth-Map Video Sequences Based on View-Invariant Human Activity Representation

Directory of Open Access Journals (Sweden)

Rami Alazrai

2017-03-01

Full Text Available This paper presents a new approach for fall detection from partially-observed depth-map video sequences. The proposed approach utilizes the 3D skeletal joint positions obtained from the Microsoft Kinect sensor to build a view-invariant descriptor for human activity representation, called the motion-pose geometric descriptor (MPGD. Furthermore, we have developed a histogram-based representation (HBR based on the MPGD to construct a length-independent representation of the observed video subsequences. Using the constructed HBR, we formulate the fall detection problem as a posterior-maximization problem in which the posteriori probability for each observed video subsequence is estimated using a multi-class SVM (support vector machine classifier. Then, we combine the computed posteriori probabilities from all of the observed subsequences to obtain an overall class posteriori probability of the entire partially-observed depth-map video sequence. To evaluate the performance of the proposed approach, we have utilized the Kinect sensor to record a dataset of depth-map video sequences that simulates four fall-related activities of elderly people, including: walking, sitting, falling form standing and falling from sitting. Then, using the collected dataset, we have developed three evaluation scenarios based on the number of unobserved video subsequences in the testing videos, including: fully-observed video sequence scenario, single unobserved video subsequence of random lengths scenarios and two unobserved video subsequences of random lengths scenarios. Experimental results show that the proposed approach achieved an average recognition accuracy of 93 . 6 % , 77 . 6 % and 65 . 1 % , in recognizing the activities during the first, second and third evaluation scenario, respectively. These results demonstrate the feasibility of the proposed approach to detect falls from partially-observed videos.

Monitoring tool usage in surgery videos using boosted convolutional and recurrent neural networks.

Science.gov (United States)

Al Hajj, Hassan; Lamard, Mathieu; Conze, Pierre-Henri; Cochener, Béatrice; Quellec, Gwenolé

2018-05-09

This paper investigates the automatic monitoring of tool usage during a surgery, with potential applications in report generation, surgical training and real-time decision support. Two surgeries are considered: cataract surgery, the most common surgical procedure, and cholecystectomy, one of the most common digestive surgeries. Tool usage is monitored in videos recorded either through a microscope (cataract surgery) or an endoscope (cholecystectomy). Following state-of-the-art video analysis solutions, each frame of the video is analyzed by convolutional neural networks (CNNs) whose outputs are fed to recurrent neural networks (RNNs) in order to take temporal relationships between events into account. Novelty lies in the way those CNNs and RNNs are trained. Computational complexity prevents the end-to-end training of "CNN+RNN" systems. Therefore, CNNs are usually trained first, independently from the RNNs. This approach is clearly suboptimal for surgical tool analysis: many tools are very similar to one another, but they can generally be differentiated based on past events. CNNs should be trained to extract the most useful visual features in combination with the temporal context. A novel boosting strategy is proposed to achieve this goal: the CNN and RNN parts of the system are simultaneously enriched by progressively adding weak classifiers (either CNNs or RNNs) trained to improve the overall classification accuracy. Experiments were performed in a dataset of 50 cataract surgery videos, where the usage of 21 surgical tools was manually annotated, and a dataset of 80 cholecystectomy videos, where the usage of 7 tools was manually annotated. Very good classification performance are achieved in both datasets: tool usage could be labeled with an average area under the ROC curve of A z =0.9961 and A z =0.9939, respectively, in offline mode (using past, present and future information), and A z =0.9957 and A z =0.9936, respectively, in online mode (using past and present

Developing a Data-Set for Stereopsis

Directory of Open Access Journals (Sweden)

D.W Hunter

2014-08-01

Full Text Available Current research on binocular stereopsis in humans and non-human primates has been limited by a lack of available data-sets. Current data-sets fall into two categories; stereo-image sets with vergence but no ranging information (Hibbard, 2008, Vision Research, 48(12, 1427-1439 or combinations of depth information with binocular images and video taken from cameras in fixed fronto-parallel configurations exhibiting neither vergence or focus effects (Hirschmuller & Scharstein, 2007, IEEE Conf. Computer Vision and Pattern Recognition. The techniques for generating depth information are also imperfect. Depth information is normally inaccurate or simply missing near edges and on partially occluded surfaces. For many areas of vision research these are the most interesting parts of the image (Goutcher, Hunter, Hibbard, 2013, i-Perception, 4(7, 484; Scarfe & Hibbard, 2013, Vision Research. Using state-of-the-art open-source ray-tracing software (PBRT as a back-end, our intention is to release a set of tools that will allow researchers in this field to generate artificial binocular stereoscopic data-sets. Although not as realistic as photographs, computer generated images have significant advantages in terms of control over the final output and ground-truth information about scene depth is easily calculated at all points in the scene, even partially occluded areas. While individual researchers have been developing similar stimuli by hand for many decades, we hope that our software will greatly reduce the time and difficulty of creating naturalistic binocular stimuli. Our intension in making this presentation is to elicit feedback from the vision community about what sort of features would be desirable in such software.

Alcohol, tobacco and illicit substances in music videos: a content analysis of prevalence and genre.

Science.gov (United States)

Gruber, Enid L; Thau, Helaine M; Hill, Douglas L; Fisher, Deborah A; Grube, Joel W

2005-07-01

Content analyses examined mention of alcohol, tobacco, and illicit substances in music videos (n = 359) broadcast in 2001, as well as genre and presence of humor. Findings indicated that references to illicit substances were more prevalent than tobacco in music videos. Humor was 2.5 times as likely to appear in videos containing references to substances than those without substances.

Fast-track video-assisted thoracoscopic surgery

DEFF Research Database (Denmark)

Holbek, Bo Laksafoss; Petersen, René Horsleben; Kehlet, Henrik

2016-01-01

Objectives To provide a short overview of fast-track video-assisted thoracoscopic surgery (VATS) and to identify areas requiring further research. Design A literature search was made using key words including: fast-track, enhanced recovery, video-assisted thoracoscopic surgery, robot......-assisted thoracoscopic surgery (RATS), robotic, thoracotomy, single-incision, uniportal, natural orifice transluminal endoscopic surgery (NOTES), chest tube, air-leak, digital drainage, pain management, analgesia, perioperative management, anaesthesia and non-intubated. References from articles were screened for further...

The art of digital video

CERN Document Server

Watkinson, John

2013-01-01

The industry ""bible"" is back and it's better than ever. The Art of Digital Video has served as the ultimate reference guide for those working with digital video for generations. Now this classic has been revised and re-written by international consultant and industry leader John Watkinson to include important technical updates on this ever-evolving topic. The format has also been improved to include optional sections that provide additional information that you can choose to skip or investigate further, depending on your interests and comfort level with the s

Hierarchical Context Modeling for Video Event Recognition.

Science.gov (United States)

Wang, Xiaoyang; Ji, Qiang

2016-10-11

Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

Introducing New Library Services: Nuclear Malaysia Gallery Photos and Videos

International Nuclear Information System (INIS)

Mohd Hafizal Yusof; Nasaruddin Ahmad; Habibah Adnan

2015-01-01

The main purpose of the existing of library is to preserve books and journals for the organizations main business. The role of library itself is to organize the books such as borrowing and renewal services as consulting their customers on getting the best references for the customers need and demand. Nowadays, the role of library also expands and the need for storing and preserving non-monograph resources such as photo and video also increase. Follow that current situation, Nuclear Malaysia's Library also take a step forwards by introducing new services so called Photo and Video Gallery. Realizing that Nuclear Malaysia also have their valuable photo and video that contains so called memorable moment and must be preserve for future reference, the management of Nuclear Malaysia's Library have decided to buy the system so called P-Canvas. The main purpose of this paper is to explain the library new services, Photo and Video Gallery, development and advantage of this system in storing and preserving Nuclear Malaysia's photo and video. (author)

Video Monitoring a Simulation-Based Quality Improvement Program in Bihar, India.

Science.gov (United States)

Dyer, Jessica; Spindler, Hilary; Christmas, Amelia; Shah, Malay Bharat; Morgan, Melissa; Cohen, Susanna R; Sterne, Jason; Mahapatra, Tanmay; Walker, Dilys

2018-04-01

Simulation-based training has become an accepted clinical training andragogy in high-resource settings with its use increasing in low-resource settings. Video recordings of simulated scenarios are commonly used by facilitators. Beyond using the videos during debrief sessions, researchers can also analyze the simulation videos to quantify technical and nontechnical skills during simulated scenarios over time. Little is known about the feasibility and use of large-scale systems to video record and analyze simulation and debriefing data for monitoring and evaluation in low-resource settings. This manuscript describes the process of designing and implementing a large-scale video monitoring system. Mentees and Mentors were consented and all simulations and debriefs conducted at 320 Primary Health Centers (PHCs) were video recorded. The system design, number of video recordings, and inter-rater reliability of the coded videos were assessed. The final dataset included a total of 11,278 videos. Overall, a total of 2,124 simulation videos were coded and 183 (12%) were blindly double-coded. For the double-coded sample, the average inter-rater reliability (IRR) scores were 80% for nontechnical skills, and 94% for clinical technical skills. Among 4,450 long debrief videos received, 216 were selected for coding and all were double-coded. Data quality of simulation videos was found to be very good in terms of recorded instances of "unable to see" and "unable to hear" in Phases 1 and 2. This study demonstrates that video monitoring systems can be effectively implemented at scale in resource limited settings. Further, video monitoring systems can play several vital roles within program implementation, including monitoring and evaluation, provision of actionable feedback to program implementers, and assurance of program fidelity.

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%).

The art of assessing quality for images and video

International Nuclear Information System (INIS)

Deriche, M.

2011-01-01

The early years of this century have witnessed a tremendous growth in the use of digital multimedia data for di?erent communication applications. Researchers from around the world are spending substantial research efforts in developing techniques for improving the appearance of images/video. However, as we know, preserving high quality is a challenging task. Images are subject to distortions during acquisition, compression, transmission, analysis, and reconstruction. For this reason, the research area focusing on image and video quality assessment has attracted a lot of attention in recent years. In particular, compression applications and other multimedia applications need powerful techniques for evaluating quality objectively without human interference. This tutorial will cover the di?erent faces of image quality assessment. We will motivate the need for robust image quality assessment techniques, then discuss the main algorithms found in the literature with a critical perspective. We will present the di?erent metrics used for full reference, reduced reference and no reference applications. We will then discuss the difference between image and video quality assessment. In all of the above, we will take a critical approach to explain which metric can be used for which application. Finally we will discuss the different approaches to analyze the performance of image/video quality metrics, and end the tutorial with some perspectives on newly introduced metrics and their potential applications.

Endnote Referencing Software: Importing references from an Ebsco database, attaching full text, organising your Endnote library

OpenAIRE

Turner, Susan

2017-01-01

This video demonstrates importing bibliographic references from EBSCO Discovery Service, the same method can be used for all EBSCO databases. \\ud The video also demonstrates how to attach full text files to the references and how to organise your references within the endnote library using groups.

TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015

Science.gov (United States)

Abatzoglou, John T.; Dobrowski, Solomon Z.; Parks, Sean A.; Hegewisch, Katherine C.

2018-01-01

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958-2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.

Constructing a no-reference H.264/AVC bitstream-based video quality metric using genetic programming-based symbolic regression

OpenAIRE

Staelens, Nicolas; Deschrijver, Dirk; Vladislavleva, E; Vermeulen, Brecht; Dhaene, Tom; Demeester, Piet

2013-01-01

In order to ensure optimal quality of experience toward end users during video streaming, automatic video quality assessment becomes an important field-of-interest to video service providers. Objective video quality metrics try to estimate perceived quality with high accuracy and in an automated manner. In traditional approaches, these metrics model the complex properties of the human visual system. More recently, however, it has been shown that machine learning approaches can also yield comp...

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.

Vehicle Plate Detection in Car Black Box Video

Directory of Open Access Journals (Sweden)

Dongjin Park

2017-01-01

Full Text Available Internet services that share vehicle black box videos need a way to obfuscate license plates in uploaded videos because of privacy issues. Thus, plate detection is one of the critical functions that such services rely on. Even though various types of detection methods are available, they are not suitable for black box videos because no assumption about size, number of plates, and lighting conditions can be made. We propose a method to detect Korean vehicle plates from black box videos. It works in two stages: the first stage aims to locate a set of candidate plate regions and the second stage identifies only actual plates from candidates by using a support vector machine classifier. The first stage consists of five sequential substeps. At first, it produces candidate regions by combining single character areas and then eliminates candidate regions that fail to meet plate conditions through the remaining substeps. For the second stage, we propose a feature vector that captures the characteristics of plates in texture and color. For performance evaluation, we compiled our dataset which contains 2,627 positive and negative images. The evaluation results show that the proposed method improves accuracy and sensitivity by at least 5% and is 30 times faster compared with an existing method.

Dataset of Building and Environment Publication in 2016, A reference method for measuring emissions of SVOCs in small chambers

Data.gov (United States)

U.S. Environmental Protection Agency — The data presented in this data file is a product of a journal publication. The dataset contains DEHP air concentrations in the emission test chamber. This dataset...

Creation of the Naturalistic Engagement in Secondary Tasks (NEST) distracted driving dataset.

Science.gov (United States)

Owens, Justin M; Angell, Linda; Hankey, Jonathan M; Foley, James; Ebe, Kazutoshi

2015-09-01

Distracted driving has become a topic of critical importance to driving safety research over the past several decades. Naturalistic driving data offer a unique opportunity to study how drivers engage with secondary tasks in real-world driving; however, the complexities involved with identifying and coding relevant epochs of naturalistic data have limited its accessibility to the general research community. This project was developed to help address this problem by creating an accessible dataset of driver behavior and situational factors observed during distraction-related safety-critical events and baseline driving epochs, using the Strategic Highway Research Program 2 (SHRP2) naturalistic dataset. The new NEST (Naturalistic Engagement in Secondary Tasks) dataset was created using crashes and near-crashes from the SHRP2 dataset that were identified as including secondary task engagement as a potential contributing factor. Data coding included frame-by-frame video analysis of secondary task and hands-on-wheel activity, as well as summary event information. In addition, information about each secondary task engagement within the trip prior to the crash/near-crash was coded at a higher level. Data were also coded for four baseline epochs and trips per safety-critical event. 1,180 events and baseline epochs were coded, and a dataset was constructed. The project team is currently working to determine the most useful way to allow broad public access to the dataset. We anticipate that the NEST dataset will be extraordinarily useful in allowing qualified researchers access to timely, real-world data concerning how drivers interact with secondary tasks during safety-critical events and baseline driving. The coded dataset developed for this project will allow future researchers to have access to detailed data on driver secondary task engagement in the real world. It will be useful for standalone research, as well as for integration with additional SHRP2 data to enable the

Improving Photometric Calibration of Meteor Video Camera Systems

Science.gov (United States)

Ehlert, Steven; Kingery, Aaron; Suggs, Robert

2017-01-01

We present the results of new calibration tests performed by the NASA Meteoroid Environment Office (MEO) designed to help quantify and minimize systematic uncertainties in meteor photometry from video camera observations. These systematic uncertainties can be categorized by two main sources: an imperfect understanding of the linearity correction for the MEO's Watec 902H2 Ultimate video cameras and uncertainties in meteor magnitudes arising from transformations between the Watec camera's Sony EX-View HAD bandpass and the bandpasses used to determine reference star magnitudes. To address the first point, we have measured the linearity response of the MEO's standard meteor video cameras using two independent laboratory tests on eight cameras. Our empirically determined linearity correction is critical for performing accurate photometry at low camera intensity levels. With regards to the second point, we have calculated synthetic magnitudes in the EX bandpass for reference stars. These synthetic magnitudes enable direct calculations of the meteor's photometric flux within the camera bandpass without requiring any assumptions of its spectral energy distribution. Systematic uncertainties in the synthetic magnitudes of individual reference stars are estimated at approx. 0.20 mag, and are limited by the available spectral information in the reference catalogs. These two improvements allow for zero-points accurate to 0.05 - 0.10 mag in both filtered and unfiltered camera observations with no evidence for lingering systematics. These improvements are essential to accurately measuring photometric masses of individual meteors and source mass indexes.

Error characterisation of global active and passive microwave soil moisture datasets

Directory of Open Access Journals (Sweden)

W. A. Dorigo

2010-12-01

Full Text Available Understanding the error structures of remotely sensed soil moisture observations is essential for correctly interpreting observed variations and trends in the data or assimilating them in hydrological or numerical weather prediction models. Nevertheless, a spatially coherent assessment of the quality of the various globally available datasets is often hampered by the limited availability over space and time of reliable in-situ measurements. As an alternative, this study explores the triple collocation error estimation technique for assessing the relative quality of several globally available soil moisture products from active (ASCAT and passive (AMSR-E and SSM/I microwave sensors. The triple collocation is a powerful statistical tool to estimate the root mean square error while simultaneously solving for systematic differences in the climatologies of a set of three linearly related data sources with independent error structures. Prerequisite for this technique is the availability of a sufficiently large number of timely corresponding observations. In addition to the active and passive satellite-based datasets, we used the ERA-Interim and GLDAS-NOAH reanalysis soil moisture datasets as a third, independent reference. The prime objective is to reveal trends in uncertainty related to different observation principles (passive versus active, the use of different frequencies (C-, X-, and Ku-band for passive microwave observations, and the choice of the independent reference dataset (ERA-Interim versus GLDAS-NOAH. The results suggest that the triple collocation method provides realistic error estimates. Observed spatial trends agree well with the existing theory and studies on the performance of different observation principles and frequencies with respect to land cover and vegetation density. In addition, if all theoretical prerequisites are fulfilled (e.g. a sufficiently large number of common observations is available and errors of the different

PROBLEM PENDIDIKAN VIDEO GAMES DALAM PERSPEKTIF TEORI SIMULACRA JEAN BAUDRILLARD

OpenAIRE

Siti Murtiningsih, Joko Siswanto, M. Mukhtasar Syamsudin

2013-01-01

Abstract: Education Problems of Video Games in the Perspective of Jean Baudrillard’s Theory of Simulacra. In the era of digital age, we are witnessing how video games penetrate children’s daily life and it is believed to have some impacts on their cognitive and affective processes. Referring to hermeneutical approach, the present library research seeks to answer the question whether video games create a real identity or simply forge false consciousness in children. In the first step, the data...

Influence of secular trends and sample size on reference equations for lung function tests.

Science.gov (United States)

Quanjer, P H; Stocks, J; Cole, T J; Hall, G L; Stanojevic, S

2011-03-01

The aim of our study was to determine the contribution of secular trends and sample size to lung function reference equations, and establish the number of local subjects required to validate published reference values. 30 spirometry datasets collected between 1978 and 2009 provided data on healthy, white subjects: 19,291 males and 23,741 females aged 2.5-95 yrs. The best fit for forced expiratory volume in 1 s (FEV(1)), forced vital capacity (FVC) and FEV(1)/FVC as functions of age, height and sex were derived from the entire dataset using GAMLSS. Mean z-scores were calculated for individual datasets to determine inter-centre differences. This was repeated by subdividing one large dataset (3,683 males and 4,759 females) into 36 smaller subsets (comprising 18-227 individuals) to preclude differences due to population/technique. No secular trends were observed and differences between datasets comprising >1,000 subjects were small (maximum difference in FEV(1) and FVC from overall mean: 0.30- -0.22 z-scores). Subdividing one large dataset into smaller subsets reproduced the above sample size-related differences and revealed that at least 150 males and 150 females would be necessary to validate reference values to avoid spurious differences due to sampling error. Use of local controls to validate reference equations will rarely be practical due to the numbers required. Reference equations derived from large or collated datasets are recommended.

Video Transect Images (1999) from the Hawaii Coral Reef Assessment and Monitoring Program (CRAMP) (NODC Accession 0000671)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of video transect images (JPEG files) from CRAMP surveys taken in 1999 at 26 sites, some of which had multiple depths. Estimates of substrate...

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

Perceived Quality of Full HD Video - Subjective Quality Assessment

Directory of Open Access Journals (Sweden)

Juraj Bienik

2016-01-01

Full Text Available In recent years, an interest in multimedia services has become a global trend and this trend is still rising. The video quality is a very significant part from the bundle of multimedia services, which leads to a requirement for quality assessment in the video domain. Video quality of a streamed video across IP networks is generally influenced by two factors “transmission link imperfection and efficiency of compression standards. This paper deals with subjective video quality assessment and the impact of the compression standards H.264, H.265 and VP9 on perceived video quality of these compression standards. The evaluation is done for four full HD sequences, the difference of scenes is in the content“ distinction is based on Spatial (SI and Temporal (TI Index of test sequences. Finally, experimental results follow up to 30% bitrate reducing of H.265 and VP9 compared with the reference H.264.

Quantifying uncertainty in observational rainfall datasets

Science.gov (United States)

Lennard, Chris; Dosio, Alessandro; Nikulin, Grigory; Pinto, Izidine; Seid, Hussen

2015-04-01

The CO-ordinated Regional Downscaling Experiment (CORDEX) has to date seen the publication of at least ten journal papers that examine the African domain during 2012 and 2013. Five of these papers consider Africa generally (Nikulin et al. 2012, Kim et al. 2013, Hernandes-Dias et al. 2013, Laprise et al. 2013, Panitz et al. 2013) and five have regional foci: Tramblay et al. (2013) on Northern Africa, Mariotti et al. (2014) and Gbobaniyi el al. (2013) on West Africa, Endris et al. (2013) on East Africa and Kalagnoumou et al. (2013) on southern Africa. There also are a further three papers that the authors know about under review. These papers all use an observed rainfall and/or temperature data to evaluate/validate the regional model output and often proceed to assess projected changes in these variables due to climate change in the context of these observations. The most popular reference rainfall data used are the CRU, GPCP, GPCC, TRMM and UDEL datasets. However, as Kalagnoumou et al. (2013) point out there are many other rainfall datasets available for consideration, for example, CMORPH, FEWS, TAMSAT & RIANNAA, TAMORA and the WATCH & WATCH-DEI data. They, with others (Nikulin et al. 2012, Sylla et al. 2012) show that the observed datasets can have a very wide spread at a particular space-time coordinate. As more ground, space and reanalysis-based rainfall products become available, all which use different methods to produce precipitation data, the selection of reference data is becoming an important factor in model evaluation. A number of factors can contribute to a uncertainty in terms of the reliability and validity of the datasets such as radiance conversion algorithims, the quantity and quality of available station data, interpolation techniques and blending methods used to combine satellite and guage based products. However, to date no comprehensive study has been performed to evaluate the uncertainty in these observational datasets. We assess 18 gridded

Video games and surgical ability: a literature review.

Science.gov (United States)

Lynch, Jeremy; Aughwane, Paul; Hammond, Toby M

2010-01-01

Surgical training is rapidly evolving because of reduced training hours and the reduction of training opportunities due to patient safety concerns. There is a popular conception that video game usage might be linked to improved operating ability especially those techniques involving endoscopic modalities. If true this might suggest future directions for training. A search was made of the MEDLINE databases for the MeSH term, "Video Games," combined with the terms "Surgical Procedures, Operative," "Endoscopy," "Robotics," "Education," "Learning," "Simulators," "Computer Simulation," "Psychomotor Performance," and "Surgery, Computer-Assisted,"encompassing all journal articles before November 2009. References of articles were searched for further studies. Twelve relevant journal articles were discovered. Video game usage has been studied in relationship to laparoscopic, gastrointestinal endoscopic, endovascular, and robotic surgery. Video game users acquire endoscopic but not robotic techniques quicker, and training on video games appears to improve performance. Copyright (c) 2010 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

A bias-corrected CMIP5 dataset for Africa using the CDF-t method - a contribution to agricultural impact studies

Science.gov (United States)

Moise Famien, Adjoua; Janicot, Serge; Delfin Ochou, Abe; Vrac, Mathieu; Defrance, Dimitri; Sultan, Benjamin; Noël, Thomas

2018-03-01

The objective of this paper is to present a new dataset of bias-corrected CMIP5 global climate model (GCM) daily data over Africa. This dataset was obtained using the cumulative distribution function transform (CDF-t) method, a method that has been applied to several regions and contexts but never to Africa. Here CDF-t has been applied over the period 1950-2099 combining Historical runs and climate change scenarios for six variables: precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface downwelling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. WFDEI has been used as the reference dataset to correct the GCMs. Evaluation of the results over West Africa has been carried out on a list of priority user-based metrics that were discussed and selected with stakeholders. It includes simulated yield using a crop model simulating maize growth. These bias-corrected GCM data have been compared with another available dataset of bias-corrected GCMs using WATCH Forcing Data as the reference dataset. The impact of WFD, WFDEI, and also EWEMBI reference datasets has been also examined in detail. It is shown that CDF-t is very effective at removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets. This is particularly true for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields. Projections of future yields over West Africa are quite different, depending on the bias-correction method used. However all these projections show a similar relative decreasing trend over the 21st century.

The presentation of seizures and epilepsy in YouTube videos.

Science.gov (United States)

Wong, Victoria S S; Stevenson, Matthew; Selwa, Linda

2013-04-01

We evaluated videos on the social media website, YouTube, containing references to seizures and epilepsy. Of 100 videos, 28% contained an ictal event, and 25% featured a person with epilepsy recounting his or her personal experience. Videos most commonly fell into categories of Personal Experience/Anecdotal (44%) and Informative/Educational (38%). Fifty-one percent of videos were judged as accurate, and 9% were inaccurate; accuracy was not an applicable attribute in the remainder of the videos. Eighty-five percent of videos were sympathetic towards those with seizures or epilepsy, 9% were neutral, and only 6% were derogatory. Ninety-eight percent of videos were thought to be easily understood by a layperson. The user-generated content on YouTube appears to be more sympathetic and accurate compared to other forms of mass media. We are optimistic that with a shifting ratio towards sympathetic content about epilepsy, the amount of stigma towards epilepsy and seizures will continue to lessen. Copyright © 2013 Elsevier Inc. All rights reserved.

A novel video recommendation system based on efficient retrieval of human actions

Science.gov (United States)

Ramezani, Mohsen; Yaghmaee, Farzin

2016-09-01

In recent years, fast growth of online video sharing eventuated new issues such as helping users to find their requirements in an efficient way. Hence, Recommender Systems (RSs) are used to find the users' most favorite items. Finding these items relies on items or users similarities. Though, many factors like sparsity and cold start user impress the recommendation quality. In some systems, attached tags are used for searching items (e.g. videos) as personalized recommendation. Different views, incomplete and inaccurate tags etc. can weaken the performance of these systems. Considering the advancement of computer vision techniques can help improving RSs. To this end, content based search can be used for finding items (here, videos are considered). In such systems, a video is taken from the user to find and recommend a list of most similar videos to the query one. Due to relating most videos to humans, we present a novel low complex scalable method to recommend videos based on the model of included action. This method has recourse to human action retrieval approaches. For modeling human actions, some interest points are extracted from each action and their motion information are used to compute the action representation. Moreover, a fuzzy dissimilarity measure is presented to compare videos for ranking them. The experimental results on HMDB, UCFYT, UCF sport and KTH datasets illustrated that, in most cases, the proposed method can reach better results than most used methods.

Introduction of a simple-model-based land surface dataset for Europe

Science.gov (United States)

Orth, Rene; Seneviratne, Sonia I.

2015-04-01

Land surface hydrology can play a crucial role during extreme events such as droughts, floods and even heat waves. We introduce in this study a new hydrological dataset for Europe that consists of soil moisture, runoff and evapotranspiration (ET). It is derived with a simple water balance model (SWBM) forced with precipitation, temperature and net radiation. The SWBM dataset extends over the period 1984-2013 with a daily time step and 0.5° × 0.5° resolution. We employ a novel calibration approach, in which we consider 300 random parameter sets chosen from an observation-based range. Using several independent validation datasets representing soil moisture (or terrestrial water content), ET and streamflow, we identify the best performing parameter set and hence the new dataset. To illustrate its usefulness, the SWBM dataset is compared against several state-of-the-art datasets (ERA-Interim/Land, MERRA-Land, GLDAS-2-Noah, simulations of the Community Land Model Version 4), using all validation datasets as reference. For soil moisture dynamics it outperforms the benchmarks. Therefore the SWBM soil moisture dataset constitutes a reasonable alternative to sparse measurements, little validated model results, or proxy data such as precipitation indices. Also in terms of runoff the SWBM dataset performs well, whereas the evaluation of the SWBM ET dataset is overall satisfactory, but the dynamics are less well captured for this variable. This highlights the limitations of the dataset, as it is based on a simple model that uses uniform parameter values. Hence some processes impacting ET dynamics may not be captured, and quality issues may occur in regions with complex terrain. Even though the SWBM is well calibrated, it cannot replace more sophisticated models; but as their calibration is a complex task the present dataset may serve as a benchmark in future. In addition we investigate the sources of skill of the SWBM dataset and find that the parameter set has a similar

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...

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.

Human recognition at a distance in video

CERN Document Server

Bhanu, Bir

2010-01-01

Most biometric systems employed for human recognition require physical contact with, or close proximity to, a cooperative subject. Far more challenging is the ability to reliably recognize individuals at a distance, when viewed from an arbitrary angle under real-world environmental conditions. Gait and face data are the two biometrics that can be most easily captured from a distance using a video camera. This comprehensive and logically organized text/reference addresses the fundamental problems associated with gait and face-based human recognition, from color and infrared video data that are

Current status of digital reference services in academic libraries in ...

African Journals Online (AJOL)

This paper investigates the extent of the application of digital reference services in academic libraries in Nigeria, highlighting the emerging formats and models of digital reference services, to include email and web forms, Ask A librarian services, online chat reference, video conferencing, digital robots, and collaborative ...

Real-time video analysis for retail stores

Science.gov (United States)

Hassan, Ehtesham; Maurya, Avinash K.

2015-03-01

With the advancement in video processing technologies, we can capture subtle human responses in a retail store environment which play decisive role in the store management. In this paper, we present a novel surveillance video based analytic system for retail stores targeting localized and global traffic estimate. Development of an intelligent system for human traffic estimation in real-life poses a challenging problem because of the variation and noise involved. In this direction, we begin with a novel human tracking system by an intelligent combination of motion based and image level object detection. We demonstrate the initial evaluation of this approach on available standard dataset yielding promising result. Exact traffic estimate in a retail store require correct separation of customers from service providers. We present a role based human classification framework using Gaussian mixture model for this task. A novel feature descriptor named graded colour histogram is defined for object representation. Using, our role based human classification and tracking system, we have defined a novel computationally efficient framework for two types of analytics generation i.e., region specific people count and dwell-time estimation. This system has been extensively evaluated and tested on four hours of real-life video captured from a retail store.

Fish4Knowledge collecting and analyzing massive coral reef fish video data

CERN Document Server

Chen-Burger, Yun-Heh; Giordano, Daniela; Hardman, Lynda; Lin, Fang-Pang

2016-01-01

This book gives a start-to-finish overview of the whole Fish4Knowledge project, in 18 short chapters, each describing one aspect of the project. The Fish4Knowledge project explored the possibilities of big video data, in this case from undersea video. Recording and analyzing 90 thousand hours of video from ten camera locations, the project gives a 3 year view of fish abundance in several tropical coral reefs off the coast of Taiwan. The research system built a remote recording network, over 100 Tb of storage, supercomputer processing, video target detection and tracking, fish species recognition and analysis, a large SQL database to record the results and an efficient retrieval mechanism. Novel user interface mechanisms were developed to provide easy access for marine ecologists, who wanted to explore the dataset. The book is a useful resource for system builders, as it gives an overview of the many new methods that were created to build the Fish4Knowledge system in a manner that also allows readers to see ho...

Youth access, creation, and content of smokeless tobacco ("dip") videos in social media.

Science.gov (United States)

Seidenberg, Andrew B; Rodgers, Elizabeth J; Rees, Vaughan W; Connolly, Gregory N

2012-04-01

Smokeless tobacco (SLT) use among white adolescent males has increased in recent years, and prevalence of SLT use among adolescent males exceeds that for smoking in several U.S. states. Recent reports have described the presence of cigarette-related content on social media Web sites popular among youth; however, little has been reported on SLT content. The YouTube video search engine was searched for the popular SLT brand Skoal, and the first 50 search results were downloaded. Video statistics data were collected for and content analysis was performed on all videos featuring smokeless use (82%). Access to SLT YouTube videos by youth was also determined by assessing whether YouTube permits youth viewing and creation of SLT videos. Mean number of views for videos analyzed was 15,422, and the most watched video had 124,276 views. Descriptions of SLT flavor/smell and social references/interactions were found in 48.8% and 63.4% of videos, respectively. By contrast, references to drug (nicotine) effects (12.2%) and public health messaging (9.8%) were less common. None of the SLT videos in the sample had restrictions that would block youth viewing. In addition, evidence of self-identified youth creating SLT videos was found for 13% of unique users in the sample. YouTube does not restrict youth from creating or viewing "dip videos." Proactive efforts are needed to ensure that YouTube and other online media do not become influential vehicles for tobacco promotion to youth. Copyright © 2012 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Automated Video Surveillance for the Study of Marine Mammal Behavior and Cognition

Directory of Open Access Journals (Sweden)

Jeremy Karnowski

2016-11-01

Full Text Available Systems for detecting and tracking social marine mammals, including dolphins, can provide data to help explain their social dynamics, predict their behavior, and measure the impact of human interference. Data collected from video surveillance methods can be consistently and systematically sampled for studies of behavior, and frame-by-frame analyses can uncover insights impossible to observe from real-time, freely occurring natural behavior. Advances in boat-based, aerial, and underwater recording platforms provide opportunities to document the behavior of marine mammals and create massive datasets. The use of human experts to detect, track, identify individuals, and recognize activity in video demands significant time and financial investment. This paper examines automated methods designed to analyze large video corpora containing marine mammals. While research is converging on best solutions for some automated tasks, particularly detection and classification, many research domains are ripe for exploration.

Effect of Home Video on the Reading Habit of Literate Nigerian ...

African Journals Online (AJOL)

The study investigated the effects of home-video on the reading habit of a hundred (100) randomly selected literate house-wives in one of the 752 local government areas of Nigeria. The descriptive survey method was used to field the views of the respondents on the use of home made video with reference to their reading ...

ClimateNet: A Machine Learning dataset for Climate Science Research

Science.gov (United States)

Prabhat, M.; Biard, J.; Ganguly, S.; Ames, S.; Kashinath, K.; Kim, S. K.; Kahou, S.; Maharaj, T.; Beckham, C.; O'Brien, T. A.; Wehner, M. F.; Williams, D. N.; Kunkel, K.; Collins, W. D.

2017-12-01

Deep Learning techniques have revolutionized commercial applications in Computer vision, speech recognition and control systems. The key for all of these developments was the creation of a curated, labeled dataset ImageNet, for enabling multiple research groups around the world to develop methods, benchmark performance and compete with each other. The success of Deep Learning can be largely attributed to the broad availability of this dataset. Our empirical investigations have revealed that Deep Learning is similarly poised to benefit the task of pattern detection in climate science. Unfortunately, labeled datasets, a key pre-requisite for training, are hard to find. Individual research groups are typically interested in specialized weather patterns, making it hard to unify, and share datasets across groups and institutions. In this work, we are proposing ClimateNet: a labeled dataset that provides labeled instances of extreme weather patterns, as well as associated raw fields in model and observational output. We develop a schema in NetCDF to enumerate weather pattern classes/types, store bounding boxes, and pixel-masks. We are also working on a TensorFlow implementation to natively import such NetCDF datasets, and are providing a reference convolutional architecture for binary classification tasks. Our hope is that researchers in Climate Science, as well as ML/DL, will be able to use (and extend) ClimateNet to make rapid progress in the application of Deep Learning for Climate Science research.

Challenges in Archiving and Sharing Video Data: Considering Moral, Pragmatic, and Substantial Arguments

Directory of Open Access Journals (Sweden)

Terhi Kirsi Korkiakangas

2014-05-01

Full Text Available Social science researchers are facing new challenges in data archiving and sharing. The challenges encountered for video data are different from those encountered for other types of qualitative data. I will consider these challenges with respect to the moral, pragmatic, and substantial arguments with which funding bodies justify data archiving and sharing. Throughout the article, I will draw on a recent Economic and Social Research Council funded project, “Transient Teams in the Operating Theatre,” in which our research team video recorded work activities in the operating theatre of a UK hospital, thereby dealing with highly sensitive footage. I will consider how video data, on most occasions, cannot be archived for re-use by the wider research community, but how new avenues could be developed so as to benefit from further research on such “unarchivable” datasets.

annot8r: GO, EC and KEGG annotation of EST datasets

Directory of Open Access Journals (Sweden)

Schmid Ralf

2008-04-01

Full Text Available Abstract Background The expressed sequence tag (EST methodology is an attractive option for the generation of sequence data for species for which no completely sequenced genome is available. The annotation and comparative analysis of such datasets poses a formidable challenge for research groups that do not have the bioinformatics infrastructure of major genome sequencing centres. Therefore, there is a need for user-friendly tools to facilitate the annotation of non-model species EST datasets with well-defined ontologies that enable meaningful cross-species comparisons. To address this, we have developed annot8r, a platform for the rapid annotation of EST datasets with GO-terms, EC-numbers and KEGG-pathways. Results annot8r automatically downloads all files relevant for the annotation process and generates a reference database that stores UniProt entries, their associated Gene Ontology (GO, Enzyme Commission (EC and Kyoto Encyclopaedia of Genes and Genomes (KEGG annotation and additional relevant data. For each of GO, EC and KEGG, annot8r extracts a specific sequence subset from the UniProt dataset based on the information stored in the reference database. These three subsets are then formatted for BLAST searches. The user provides the protein or nucleotide sequences to be annotated and annot8r runs BLAST searches against these three subsets. The BLAST results are parsed and the corresponding annotations retrieved from the reference database. The annotations are saved both as flat files and also in a relational postgreSQL results database to facilitate more advanced searches within the results. annot8r is integrated with the PartiGene suite of EST analysis tools. Conclusion annot8r is a tool that assigns GO, EC and KEGG annotations for data sets resulting from EST sequencing projects both rapidly and efficiently. The benefits of an underlying relational database, flexibility and the ease of use of the program make it ideally suited for non

Capturing Better Photos and Video with your iPhone

CERN Document Server

Thomas, J Dennis; Sammon, Rick

2011-01-01

Offers unique advice for taking great photos and videos with your iPod or iPhone!. Packed with unique advice, tips, and tricks, this one-of-a-kind, full-color reference presents step-by-step guidance for taking the best possible quality photos and videos using your iPod or iPhone. Top This unique book walks you through everything from composing a picture, making minor edits, and posting content to using apps to create more dynamic images. You'll quickly put to use this up-to-date coverage of executing both common and uncommon photo and video tasks on your mobile device.: Presents unique advice

A Generalized Pyramid Matching Kernel for Human Action Recognition in Realistic Videos

Directory of Open Access Journals (Sweden)

Wenjun Zhang

2013-10-01

Full Text Available Human action recognition is an increasingly important research topic in the fields of video sensing, analysis and understanding. Caused by unconstrained sensing conditions, there exist large intra-class variations and inter-class ambiguities in realistic videos, which hinder the improvement of recognition performance for recent vision-based action recognition systems. In this paper, we propose a generalized pyramid matching kernel (GPMK for recognizing human actions in realistic videos, based on a multi-channel “bag of words” representation constructed from local spatial-temporal features of video clips. As an extension to the spatial-temporal pyramid matching (STPM kernel, the GPMK leverages heterogeneous visual cues in multiple feature descriptor types and spatial-temporal grid granularity levels, to build a valid similarity metric between two video clips for kernel-based classification. Instead of the predefined and fixed weights used in STPM, we present a simple, yet effective, method to compute adaptive channel weights of GPMK based on the kernel target alignment from training data. It incorporates prior knowledge and the data-driven information of different channels in a principled way. The experimental results on three challenging video datasets (i.e., Hollywood2, Youtube and HMDB51 validate the superiority of our GPMK w.r.t. the traditional STPM kernel for realistic human action recognition and outperform the state-of-the-art results in the literature.

Towards interoperable and reproducible QSAR analyses: Exchange of datasets.

Science.gov (United States)

Spjuth, Ola; Willighagen, Egon L; Guha, Rajarshi; Eklund, Martin; Wikberg, Jarl Es

2010-06-30

QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data. We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR datasets, consisting of an open XML format (QSAR-ML) which builds on an open and extensible descriptor ontology. The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a dataset described by QSAR-ML makes its setup completely reproducible. We also provide a reference implementation as a set of plugins for Bioclipse which simplifies setup of QSAR datasets, and allows for exporting in QSAR-ML as well as old-fashioned CSV formats. The implementation facilitates addition of new descriptor implementations from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services. Standardized QSAR datasets open up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible creation of datasets, solving the problems of defining which software components were used and their versions, and the descriptor ontology eliminates confusions regarding descriptors by defining them crisply. This makes is easy to join, extend, combine datasets and hence work collectively, but

Towards interoperable and reproducible QSAR analyses: Exchange of datasets

Directory of Open Access Journals (Sweden)

Spjuth Ola

2010-06-01

Full Text Available Abstract Background QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data. Results We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR datasets, consisting of an open XML format (QSAR-ML which builds on an open and extensible descriptor ontology. The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a dataset described by QSAR-ML makes its setup completely reproducible. We also provide a reference implementation as a set of plugins for Bioclipse which simplifies setup of QSAR datasets, and allows for exporting in QSAR-ML as well as old-fashioned CSV formats. The implementation facilitates addition of new descriptor implementations from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services. Conclusions Standardized QSAR datasets open up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible creation of datasets, solving the problems of defining which software components were used and their versions, and the descriptor ontology eliminates confusions regarding descriptors by defining them crisply. This makes is easy to join

Let the Game Begin: Ergodic as an Approach for Video Game Translation

OpenAIRE

SF. Lukfianka Sanjaya Purnama; SF. Luthfie Arguby Purnomo; Dyah Nugrahani

2016-01-01

This paper attempts to propose ergodic as an approach for video game translation. The word approach here refers to an approach for translation products and to an approach for the translation process. The steps to formulate ergodic as an approach are first, Aarseth’sergodic literature is reviewed to elicit a basis for comprehension toward its relationship with video games and video game translation Secondly, taking the translation of Electronic Arts’Need for Speed: Own the City, Midway’s Morta...

Video Transect Images from the Hawaii Coral Reef Assessment and Monitoring Program (CRAMP): Data from 2002 (NODC Accession 0000961)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of video transect images (TIF files) from CRAMP surveys taken in 2002 at 23 sites, some of which had multiple depths. Estimates of substrate...

Video Transect Images from the Hawaii Coral Reef Assessment and Monitoring Program (CRAMP):Data from 2003 (NODC Accession 0001732)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of video transect images (TIF files) from CRAMP surveys taken in 2003 at 15 sites, some of which had multiple depths. Estimates of substrate...

Video Transect Images from the Hawaii Coral Reef Assessment and Monitoring Program (CRAMP): Data from 2003 (NODC Accession 0001732)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of video transect images (TIF files) from CRAMP surveys taken in 2003 at 15 sites, some of which had multiple depths. Estimates of substrate...

Video transect images from the Hawaii Coral Reef Assessment and Monitoring Program (CRAMP): data from 2002 (NODC Accession 0000961)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of video transect images (TIF files) from CRAMP surveys taken in 2002 at 23 sites, some of which had multiple depths. Estimates of substrate...

Video Transect Images from the Hawaii Coral Reef Assessment and Monitoring Program (CRAMP): Data from 2000 (NODC Accession 0000728)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of video transect images (TIF files) from CRAMP surveys taken in 2000 at 23 sites, some of which had multiple depths. Estimates of substrate...

Know your data: understanding implicit usage versus explicit action in video content classification

Science.gov (United States)

Yew, Jude; Shamma, David A.

2011-02-01

In this paper, we present a method for video category classification using only social metadata from websites like YouTube. In place of content analysis, we utilize communicative and social contexts surrounding videos as a means to determine a categorical genre, e.g. Comedy, Music. We hypothesize that video clips belonging to different genre categories would have distinct signatures and patterns that are reflected in their collected metadata. In particular, we define and describe social metadata as usage or action to aid in classification. We trained a Naive Bayes classifier to predict categories from a sample of 1,740 YouTube videos representing the top five genre categories. Using just a small number of the available metadata features, we compare the classifications produced by our Naive Bayes classifier with those provided by the uploader of that particular video. Compared to random predictions with the YouTube data (21% accurate), our classifier attained a mediocre 33% accuracy in predicting video genres. However, we found that the accuracy of our classifier significantly improves by nominal factoring of the explicit data features. By factoring the ratings of the videos in the dataset, the classifier was able to accurately predict the genres of 75% of the videos. We argue that the patterns of social activity found in the metadata are not just meaningful in their own right, but are indicative of the meaning of the shared video content. The results presented by this project represents a first step in investigating the potential meaning and significance of social metadata and its relation to the media experience.

Neural Basis of Video Gaming: A Systematic Review

Science.gov (United States)

Palaus, Marc; Marron, Elena M.; Viejo-Sobera, Raquel; Redolar-Ripoll, Diego

2017-01-01

Background: Video gaming is an increasingly popular activity in contemporary society, especially among young people, and video games are increasing in popularity not only as a research tool but also as a field of study. Many studies have focused on the neural and behavioral effects of video games, providing a great deal of video game derived brain correlates in recent decades. There is a great amount of information, obtained through a myriad of methods, providing neural correlates of video games. Objectives: We aim to understand the relationship between the use of video games and their neural correlates, taking into account the whole variety of cognitive factors that they encompass. Methods: A systematic review was conducted using standardized search operators that included the presence of video games and neuro-imaging techniques or references to structural or functional brain changes. Separate categories were made for studies featuring Internet Gaming Disorder and studies focused on the violent content of video games. Results: A total of 116 articles were considered for the final selection. One hundred provided functional data and 22 measured structural brain changes. One-third of the studies covered video game addiction, and 14% focused on video game related violence. Conclusions: Despite the innate heterogeneity of the field of study, it has been possible to establish a series of links between the neural and cognitive aspects, particularly regarding attention, cognitive control, visuospatial skills, cognitive workload, and reward processing. However, many aspects could be improved. The lack of standardization in the different aspects of video game related research, such as the participants' characteristics, the features of each video game genre and the diverse study goals could contribute to discrepancies in many related studies. PMID:28588464

Neural Basis of Video Gaming: A Systematic Review

Directory of Open Access Journals (Sweden)

Marc Palaus

2017-05-01

Full Text Available Background: Video gaming is an increasingly popular activity in contemporary society, especially among young people, and video games are increasing in popularity not only as a research tool but also as a field of study. Many studies have focused on the neural and behavioral effects of video games, providing a great deal of video game derived brain correlates in recent decades. There is a great amount of information, obtained through a myriad of methods, providing neural correlates of video games.Objectives: We aim to understand the relationship between the use of video games and their neural correlates, taking into account the whole variety of cognitive factors that they encompass.Methods: A systematic review was conducted using standardized search operators that included the presence of video games and neuro-imaging techniques or references to structural or functional brain changes. Separate categories were made for studies featuring Internet Gaming Disorder and studies focused on the violent content of video games.Results: A total of 116 articles were considered for the final selection. One hundred provided functional data and 22 measured structural brain changes. One-third of the studies covered video game addiction, and 14% focused on video game related violence.Conclusions: Despite the innate heterogeneity of the field of study, it has been possible to establish a series of links between the neural and cognitive aspects, particularly regarding attention, cognitive control, visuospatial skills, cognitive workload, and reward processing. However, many aspects could be improved. The lack of standardization in the different aspects of video game related research, such as the participants' characteristics, the features of each video game genre and the diverse study goals could contribute to discrepancies in many related studies.

Neural Basis of Video Gaming: A Systematic Review.

Science.gov (United States)

Palaus, Marc; Marron, Elena M; Viejo-Sobera, Raquel; Redolar-Ripoll, Diego

2017-01-01

Background: Video gaming is an increasingly popular activity in contemporary society, especially among young people, and video games are increasing in popularity not only as a research tool but also as a field of study. Many studies have focused on the neural and behavioral effects of video games, providing a great deal of video game derived brain correlates in recent decades. There is a great amount of information, obtained through a myriad of methods, providing neural correlates of video games. Objectives: We aim to understand the relationship between the use of video games and their neural correlates, taking into account the whole variety of cognitive factors that they encompass. Methods: A systematic review was conducted using standardized search operators that included the presence of video games and neuro-imaging techniques or references to structural or functional brain changes. Separate categories were made for studies featuring Internet Gaming Disorder and studies focused on the violent content of video games. Results: A total of 116 articles were considered for the final selection. One hundred provided functional data and 22 measured structural brain changes. One-third of the studies covered video game addiction, and 14% focused on video game related violence. Conclusions: Despite the innate heterogeneity of the field of study, it has been possible to establish a series of links between the neural and cognitive aspects, particularly regarding attention, cognitive control, visuospatial skills, cognitive workload, and reward processing. However, many aspects could be improved. The lack of standardization in the different aspects of video game related research, such as the participants' characteristics, the features of each video game genre and the diverse study goals could contribute to discrepancies in many related studies.

Advances in top-down and bottom-up approaches to video-based camera tracking

OpenAIRE

Marimón Sanjuán, David

2007-01-01

Video-based camera tracking consists in trailing the three dimensional pose followed by a mobile camera using video as sole input. In order to estimate the pose of a camera with respect to a real scene, one or more three dimensional references are needed. Examples of such references are landmarks with known geometric shape, or objects for which a model is generated beforehand. By comparing what is seen by a camera with what is geometrically known from reality, it is possible to recover the po...

Advances in top-down and bottom-up approaches to video-based camera tracking

OpenAIRE

Marimón Sanjuán, David; Ebrahimi, Touradj

2008-01-01

Video-based camera tracking consists in trailing the three dimensional pose followed by a mobile camera using video as sole input. In order to estimate the pose of a camera with respect to a real scene, one or more three dimensional references are needed. Examples of such references are landmarks with known geometric shape, or objects for which a model is generated beforehand. By comparing what is seen by a camera with what is geometrically known from reality, it is possible to recover the po...

Tracking and recognition face in videos with incremental local sparse representation model

Science.gov (United States)

Wang, Chao; Wang, Yunhong; Zhang, Zhaoxiang

2013-10-01

This paper addresses the problem of tracking and recognizing faces via incremental local sparse representation. First a robust face tracking algorithm is proposed via employing local sparse appearance and covariance pooling method. In the following face recognition stage, with the employment of a novel template update strategy, which combines incremental subspace learning, our recognition algorithm adapts the template to appearance changes and reduces the influence of occlusion and illumination variation. This leads to a robust video-based face tracking and recognition with desirable performance. In the experiments, we test the quality of face recognition in real-world noisy videos on YouTube database, which includes 47 celebrities. Our proposed method produces a high face recognition rate at 95% of all videos. The proposed face tracking and recognition algorithms are also tested on a set of noisy videos under heavy occlusion and illumination variation. The tracking results on challenging benchmark videos demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods. In the case of the challenging dataset in which faces undergo occlusion and illumination variation, and tracking and recognition experiments under significant pose variation on the University of California, San Diego (Honda/UCSD) database, our proposed method also consistently demonstrates a high recognition rate.

Performance evaluation of packet video transfer over local area networks

OpenAIRE

Lu, Jie

1993-01-01

This research investigates the implementation and performance of packet video transfer over local area networks. A network architecture is defined for packet video such that most of the processing is performed by the higher layers of the Open Systems Interconnection (OSI) reference model, while the lower layers provide real-time services. Implementation methods are discussed for coding schemes, including data compression, the network interface unit, and the underlying local are...

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 ...

PhD students at Science & Technology exploring student learning in a collaborative video-circle

DEFF Research Database (Denmark)

Nielsen, Birgitte Lund; Hougaard, Rikke F.

examined using video, audio and questionnaires. The TAs reported a high level of outcomes and referred to the importance of the video as evidence supporting the discussions. The importance of the collaboration between peers and staff (educational developers) was emphasized: highlighting the benefit...

Video Game Characters. Theory and Analysis

Directory of Open Access Journals (Sweden)

Felix Schröter

2014-06-01

Full Text Available This essay develops a method for the analysis of video game characters based on a theoretical understanding of their medium-specific representation and the mental processes involved in their intersubjective construction by video game players. We propose to distinguish, first, between narration, simulation, and communication as three modes of representation particularly salient for contemporary video games and the characters they represent, second, between narrative, ludic, and social experience as three ways in which players perceive video game characters and their representations, and, third, between three dimensions of video game characters as ‘intersubjective constructs’, which usually are to be analyzed not only as fictional beings with certain diegetic properties but also as game pieces with certain ludic properties and, in those cases in which they function as avatars in the social space of a multiplayer game, as representations of other players. Having established these basic distinctions, we proceed to analyze their realization and interrelation by reference to the character of Martin Walker from the third-person shooter Spec Ops: The Line (Yager Development 2012, the highly customizable player-controlled characters from the role-playing game The Elder Scrolls V: Skyrim (Bethesda 2011, and the complex multidimensional characters in the massively multiplayer online role-playing game Star Wars: The Old Republic (BioWare 2011-2014.

A reference dataset for deformable image registration spatial accuracy evaluation using the COPDgene study archive

International Nuclear Information System (INIS)

Castillo, Richard; Castillo, Edward; Wood, Abbie M; Ludwig, Michelle S; Guerrero, Thomas; Fuentes, David; Ahmad, Moiz

2013-01-01

Landmark point-pairs provide a strategy to assess deformable image registration (DIR) accuracy in terms of the spatial registration of the underlying anatomy depicted in medical images. In this study, we propose to augment a publicly available database (www.dir-lab.com) of medical images with large sets of manually identified anatomic feature pairs between breath-hold computed tomography (BH-CT) images for DIR spatial accuracy evaluation. Ten BH-CT image pairs were randomly selected from the COPDgene study cases. Each patient had received CT imaging of the entire thorax in the supine position at one-fourth dose normal expiration and maximum effort full dose inspiration. Using dedicated in-house software, an imaging expert manually identified large sets of anatomic feature pairs between images. Estimates of inter- and intra-observer spatial variation in feature localization were determined by repeat measurements of multiple observers over subsets of randomly selected features. 7298 anatomic landmark features were manually paired between the 10 sets of images. Quantity of feature pairs per case ranged from 447 to 1172. Average 3D Euclidean landmark displacements varied substantially among cases, ranging from 12.29 (SD: 6.39) to 30.90 (SD: 14.05) mm. Repeat registration of uniformly sampled subsets of 150 landmarks for each case yielded estimates of observer localization error, which ranged in average from 0.58 (SD: 0.87) to 1.06 (SD: 2.38) mm for each case. The additions to the online web database (www.dir-lab.com) described in this work will broaden the applicability of the reference data, providing a freely available common dataset for targeted critical evaluation of DIR spatial accuracy performance in multiple clinical settings. Estimates of observer variance in feature localization suggest consistent spatial accuracy for all observers across both four-dimensional CT and COPDgene patient cohorts. (paper)

Efficient Power Allocation for Video over Superposition Coding

KAUST Repository

Lau, Chun Pong

2013-03-01

In this paper we consider a wireless multimedia system by mapping scalable video coded (SVC) bit stream upon superposition coded (SPC) signals, referred to as (SVC-SPC) architecture. Empirical experiments using a software-defined radio(SDR) emulator are conducted to gain a better understanding of its efficiency, specifically, the impact of the received signal due to different power allocation ratios. Our experimental results show that to maintain high video quality, the power allocated to the base layer should be approximately four times higher than the power allocated to the enhancement layer.

Video transect images from the Hawaii Coral Reef Assessment and Monitoring Program (CRAMP): data from year 1999 (NODC Accession 0000671)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of video transect images (JPEG files) from CRAMP surveys taken in 1999 at 26 sites, some of which had multiple depths. Estimates of substrate...

First- and third-party ground truth for key frame extraction from consumer video clips

Science.gov (United States)

Costello, Kathleen; Luo, Jiebo

2007-02-01

Extracting key frames (KF) from video is of great interest in many applications, such as video summary, video organization, video compression, and prints from video. KF extraction is not a new problem. However, current literature has been focused mainly on sports or news video. In the consumer video space, the biggest challenges for key frame selection from consumer videos are the unconstrained content and lack of any preimposed structure. In this study, we conduct ground truth collection of key frames from video clips taken by digital cameras (as opposed to camcorders) using both first- and third-party judges. The goals of this study are: (1) to create a reference database of video clips reasonably representative of the consumer video space; (2) to identify associated key frames by which automated algorithms can be compared and judged for effectiveness; and (3) to uncover the criteria used by both first- and thirdparty human judges so these criteria can influence algorithm design. The findings from these ground truths will be discussed.

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.

An Efficient Fractal Video Sequences Codec with Multiviews

Directory of Open Access Journals (Sweden)

Shiping Zhu

2013-01-01

Full Text Available Multiview video consists of multiple views of the same scene. They require enormous amount of data to achieve high image quality, which makes it indispensable to compress multiview video. Therefore, data compression is a major issue for multiviews. In this paper, we explore an efficient fractal video codec to compress multiviews. The proposed scheme first compresses a view-dependent geometry of the base view using fractal video encoder with homogeneous region condition. With the extended fractional pel motion estimation algorithm and fast disparity estimation algorithm, it then generates prediction images of other views. The prediction image uses the image-based rendering techniques based on the decoded video. And the residual signals are obtained by the prediction image and the original image. Finally, it encodes residual signals by the fractal video encoder. The idea is also to exploit the statistical dependencies from both temporal and interview reference pictures for motion compensated prediction. Experimental results show that the proposed algorithm is consistently better than JMVC8.5, with 62.25% bit rate decrease and 0.37 dB PSNR increase based on the Bjontegaard metric, and the total encoding time (TET of the proposed algorithm is reduced by 92%.

EPA Nanorelease Dataset

Data.gov (United States)

U.S. Environmental Protection Agency — EPA Nanorelease Dataset. This dataset is associated with the following publication: Wohlleben, W., C. Kingston, J. Carter, E. Sahle-Demessie, S. Vazquez-Campos, B....

A time-varying subjective quality model for mobile streaming videos with stalling events

Science.gov (United States)

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

2015-09-01

Over-the-top mobile video streaming is invariably influenced by volatile network conditions which cause playback interruptions (stalling events), thereby impairing users' quality of experience (QoE). Developing models that can accurately predict users' QoE could enable the more efficient design of quality-control protocols for video streaming networks that reduce network operational costs while still delivering high-quality video content to the customers. Existing objective models that predict QoE are based on global video features, such as the number of stall events and their lengths, and are trained and validated on a small pool of ad hoc video datasets, most of which are not publicly available. The model we propose in this work goes beyond previous models as it also accounts for the fundamental effect that a viewer's recent level of satisfaction or dissatisfaction has on their overall viewing experience. In other words, the proposed model accounts for and adapts to the recency, or hysteresis effect caused by a stall event in addition to accounting for the lengths, frequency of occurrence, and the positions of stall events - factors that interact in a complex way to affect a user's QoE. On the recently introduced LIVE-Avvasi Mobile Video Database, which consists of 180 distorted videos of varied content that are afflicted solely with over 25 unique realistic stalling events, we trained and validated our model to accurately predict the QoE, attaining standout QoE prediction performance.

Quality and noise measurements in mobile phone video capture

Science.gov (United States)

Petrescu, Doina; Pincenti, John

2011-02-01

The quality of videos captured with mobile phones has become increasingly important particularly since resolutions and formats have reached a level that rivals the capabilities available in the digital camcorder market, and since many mobile phones now allow direct playback on large HDTVs. The video quality is determined by the combined quality of the individual parts of the imaging system including the image sensor, the digital color processing, and the video compression, each of which has been studied independently. In this work, we study the combined effect of these elements on the overall video quality. We do this by evaluating the capture under various lighting, color processing, and video compression conditions. First, we measure full reference quality metrics between encoder input and the reconstructed sequence, where the encoder input changes with light and color processing modifications. Second, we introduce a system model which includes all elements that affect video quality, including a low light additive noise model, ISP color processing, as well as the video encoder. Our experiments show that in low light conditions and for certain choices of color processing the system level visual quality may not improve when the encoder becomes more capable or the compression ratio is reduced.

Medicare Referring Provider (DMEPOS) Data CY2013

Data.gov (United States)

U.S. Department of Health & Human Services — The Centers for Medicare and Medicaid Services (CMS) released a new dataset, the Referring Provider Durable Medical Equipment, Prosthetics, Orthotics and Supplies...

Video based object representation and classification using multiple covariance matrices.

Science.gov (United States)

Zhang, Yurong; Liu, Quan

2017-01-01

Video based object recognition and classification has been widely studied in computer vision and image processing area. One main issue of this task is to develop an effective representation for video. This problem can generally be formulated as image set representation. In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. The core idea of MCDL is to represent an image set using multiple covariance matrices with each covariance matrix representing one cluster of images. Firstly, we use the Nonnegative Matrix Factorization (NMF) method to do image clustering within each image set, and then adopt Covariance Discriminative Learning on each cluster (subset) of images. At last, we adopt KLDA and nearest neighborhood classification method for image set classification. Promising experimental results on several datasets show the effectiveness of our MCDL method.

Resampling Methods Improve the Predictive Power of Modeling in Class-Imbalanced Datasets

Directory of Open Access Journals (Sweden)

Paul H. Lee

2014-09-01

Full Text Available In the medical field, many outcome variables are dichotomized, and the two possible values of a dichotomized variable are referred to as classes. A dichotomized dataset is class-imbalanced if it consists mostly of one class, and performance of common classification models on this type of dataset tends to be suboptimal. To tackle such a problem, resampling methods, including oversampling and undersampling can be used. This paper aims at illustrating the effect of resampling methods using the National Health and Nutrition Examination Survey (NHANES wave 2009–2010 dataset. A total of 4677 participants aged ≥20 without self-reported diabetes and with valid blood test results were analyzed. The Classification and Regression Tree (CART procedure was used to build a classification model on undiagnosed diabetes. A participant demonstrated evidence of diabetes according to WHO diabetes criteria. Exposure variables included demographics and socio-economic status. CART models were fitted using a randomly selected 70% of the data (training dataset, and area under the receiver operating characteristic curve (AUC was computed using the remaining 30% of the sample for evaluation (testing dataset. CART models were fitted using the training dataset, the oversampled training dataset, the weighted training dataset, and the undersampled training dataset. In addition, resampling case-to-control ratio of 1:1, 1:2, and 1:4 were examined. Resampling methods on the performance of other extensions of CART (random forests and generalized boosted trees were also examined. CARTs fitted on the oversampled (AUC = 0.70 and undersampled training data (AUC = 0.74 yielded a better classification power than that on the training data (AUC = 0.65. Resampling could also improve the classification power of random forests and generalized boosted trees. To conclude, applying resampling methods in a class-imbalanced dataset improved the classification power of CART, random forests

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.

Benchmarking of Typical Meteorological Year datasets dedicated to Concentrated-PV systems

Science.gov (United States)

Realpe, Ana Maria; Vernay, Christophe; Pitaval, Sébastien; Blanc, Philippe; Wald, Lucien; Lenoir, Camille

2016-04-01

Accurate analysis of meteorological and pyranometric data for long-term analysis is the basis of decision-making for banks and investors, regarding solar energy conversion systems. This has led to the development of methodologies for the generation of Typical Meteorological Years (TMY) datasets. The most used method for solar energy conversion systems was proposed in 1978 by the Sandia Laboratory (Hall et al., 1978) considering a specific weighted combination of different meteorological variables with notably global, diffuse horizontal and direct normal irradiances, air temperature, wind speed, relative humidity. In 2012, a new approach was proposed in the framework of the European project FP7 ENDORSE. It introduced the concept of "driver" that is defined by the user as an explicit function of the pyranometric and meteorological relevant variables to improve the representativeness of the TMY datasets with respect the specific solar energy conversion system of interest. The present study aims at comparing and benchmarking different TMY datasets considering a specific Concentrated-PV (CPV) system as the solar energy conversion system of interest. Using long-term (15+ years) time-series of high quality meteorological and pyranometric ground measurements, three types of TMY datasets generated by the following methods: the Sandia method, a simplified driver with DNI as the only representative variable and a more sophisticated driver. The latter takes into account the sensitivities of the CPV system with respect to the spectral distribution of the solar irradiance and wind speed. Different TMY datasets from the three methods have been generated considering different numbers of years in the historical dataset, ranging from 5 to 15 years. The comparisons and benchmarking of these TMY datasets are conducted considering the long-term time series of simulated CPV electric production as a reference. The results of this benchmarking clearly show that the Sandia method is not

Review of passive-blind detection in digital video forgery based on sensing and imaging techniques

Science.gov (United States)

Tao, Junjie; Jia, Lili; You, Ying

2016-01-01

Advances in digital video compression and IP communication technologies raised new issues and challenges concerning the integrity and authenticity of surveillance videos. It is so important that the system should ensure that once recorded, the video cannot be altered; ensuring the audit trail is intact for evidential purposes. This paper gives an overview of passive techniques of Digital Video Forensics which are based on intrinsic fingerprints inherent in digital surveillance videos. In this paper, we performed a thorough research of literatures relevant to video manipulation detection methods which accomplish blind authentications without referring to any auxiliary information. We presents review of various existing methods in literature, and much more work is needed to be done in this field of video forensics based on video data analysis and observation of the surveillance systems.

Revisiting video game ratings: Shift from content-centric to parent-centric approach

Directory of Open Access Journals (Sweden)

Jiow Hee Jhee

2017-01-01

Full Text Available The rapid adoption of video gaming among children has placed tremendous strain on parents’ ability to manage their children’s consumption. While parents refer online to video games ratings (VGR information to support their mediation efforts, there are many difficulties associated with such practice. This paper explores the popular VGR sites, and highlights the inadequacies of VGRs to capture the parents’ concerns, such as time displacement, social interactions, financial spending and various video game effects, beyond the widespread panics over content issues, that is subjective, ever-changing and irrelevant. As such, this paper argues for a shift from content-centric to a parent-centric approach in VGRs, that captures the evolving nature of video gaming, and support parents, the main users of VGRs, in their management of their young video gaming children. This paper proposes a Video Games Repository for Parents to represent that shift.

Accuracy of complete-arch model using an intraoral video scanner: An in vitro study.

Science.gov (United States)

Jeong, Il-Do; Lee, Jae-Jun; Jeon, Jin-Hun; Kim, Ji-Hwan; Kim, Hae-Young; Kim, Woong-Chul

2016-06-01

Information on the accuracy of intraoral video scanners for long-span areas is limited. The purpose of this in vitro study was to evaluate and compare the trueness and precision of an intraoral video scanner, an intraoral still image scanner, and a blue-light scanner for the production of digital impressions. Reference scan data were obtained by scanning a complete-arch model. An identical model was scanned 8 times using an intraoral video scanner (CEREC Omnicam; Sirona) and an intraoral still image scanner (CEREC Bluecam; Sirona), and stone casts made from conventional impressions of the same model were scanned 8 times with a blue-light scanner as a control (Identica Blue; Medit). Accuracy consists of trueness (the extent to which the scan data differ from the reference scan) and precision (the similarity of the data from multiple scans). To evaluate precision, 8 scans were superimposed using 3-dimensional analysis software; the reference scan data were then superimposed to determine the trueness. Differences were analyzed using 1-way ANOVA and post hoc Tukey HSD tests (α=.05). Trueness in the video scanner group was not significantly different from that in the control group. However, the video scanner group showed significantly lower values than those of the still image scanner group for all variables (P<.05), except in tolerance range. The root mean square, standard deviations, and mean negative precision values for the video scanner group were significantly higher than those for the other groups (P<.05). Digital impressions obtained by the intraoral video scanner showed better accuracy for long-span areas than those captured by the still image scanner. However, the video scanner was less accurate than the laboratory scanner. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

PROBLEM PENDIDIKAN VIDEO GAMES DALAM PERSPEKTIF TEORI SIMULACRA JEAN BAUDRILLARD

Directory of Open Access Journals (Sweden)

Siti Murtiningsih, Joko Siswanto, M. Mukhtasar Syamsudin

2013-05-01

Full Text Available Abstract: Education Problems of Video Games in the Perspective of Jean Baudrillard’s Theory of Simulacra. In the era of digital age, we are witnessing how video games penetrate children’s daily life and it is believed to have some impacts on their cognitive and affective processes. Referring to hermeneutical approach, the present library research seeks to answer the question whether video games create a real identity or simply forge false consciousness in children. In the first step, the data were collected from bibliographi­cal sources that related to data. In the second step, the data were analyzed to examine the pedagogical-philosophical properties of the video games. The results indicate that video games change the way children view the world. Video games present the world as hiper-reality. Bu putting aside the negative values and maximizing the positive ones, the understanding of hiper-reality allows for the inculcation of children. Abstrak: Problem Pendidikan Video Games dalam Perspectif Teori Simulacra Jean Baudrillard. Permainan video games diyakini berdampak positif sekaligus negatif pada proses kognitif dan afektif anak.-anak. Terutama, video games berpengaruh pada proses internalisasi nilai-nilai dan pembentukan identitas mereka. Teknologi virtual yang disajikan oleh video games, seperti didekati oleh teori simulacra Jean Baudrillard, menyuguhkan jebakan akan realitas palsu. Melalui riset pustaka dengan metode "filsafat her­meneutis", dianalisis data untuk membangun refleksi filsafat pendidikan atas permainan video games itu. Hasil penelitian ini menyatakan video games menyuguhkan sebuah hiper-realitas dari simulasi realitas, atau simulacra dalam teori Jean Baudrillard. Simulacra adalah dunia yang terbentuk dari salinan realitas, yang menjadi acuan melebihi realitas asli. Disimpulkan bahwa video games menjadi semacam “ruang konseptual”, yang dibentuk oleh simulacra. Dengan mengenali hakikat hiper-realitas, video games dapat

A procedure to validate and correct the {sup 13}C chemical shift calibration of RNA datasets

Energy Technology Data Exchange (ETDEWEB)

Aeschbacher, Thomas; Schubert, Mario, E-mail: schubert@mol.biol.ethz.ch; Allain, Frederic H.-T., E-mail: allain@mol.biol.ethz.ch [ETH Zuerich, Institute for Molecular Biology and Biophysics (Switzerland)

2012-02-15

Chemical shifts reflect the structural environment of a certain nucleus and can be used to extract structural and dynamic information. Proper calibration is indispensable to extract such information from chemical shifts. Whereas a variety of procedures exist to verify the chemical shift calibration for proteins, no such procedure is available for RNAs to date. We present here a procedure to analyze and correct the calibration of {sup 13}C NMR data of RNAs. Our procedure uses five {sup 13}C chemical shifts as a reference, each of them found in a narrow shift range in most datasets deposited in the Biological Magnetic Resonance Bank. In 49 datasets we could evaluate the {sup 13}C calibration and detect errors or inconsistencies in RNA {sup 13}C chemical shifts based on these chemical shift reference values. More than half of the datasets (27 out of those 49) were found to be improperly referenced or contained inconsistencies. This large inconsistency rate possibly explains that no clear structure-{sup 13}C chemical shift relationship has emerged for RNA so far. We were able to recalibrate or correct 17 datasets resulting in 39 usable {sup 13}C datasets. 6 new datasets from our lab were used to verify our method increasing the database to 45 usable datasets. We can now search for structure-chemical shift relationships with this improved list of {sup 13}C chemical shift data. This is demonstrated by a clear relationship between ribose {sup 13}C shifts and the sugar pucker, which can be used to predict a C2 Prime - or C3 Prime -endo conformation of the ribose with high accuracy. The improved quality of the chemical shift data allows statistical analysis with the potential to facilitate assignment procedures, and the extraction of restraints for structure calculations of RNA.

Content-based video retrieval by example video clip

Science.gov (United States)

Dimitrova, Nevenka; Abdel-Mottaleb, Mohamed

1997-01-01

This paper presents a novel approach for video retrieval from a large archive of MPEG or Motion JPEG compressed video clips. We introduce a retrieval algorithm that takes a video clip as a query and searches the database for clips with similar contents. Video clips are characterized by a sequence of representative frame signatures, which are constructed from DC coefficients and motion information (`DC+M' signatures). The similarity between two video clips is determined by using their respective signatures. This method facilitates retrieval of clips for the purpose of video editing, broadcast news retrieval, or copyright violation detection.

Proteomics dataset

DEFF Research Database (Denmark)

Bennike, Tue Bjerg; Carlsen, Thomas Gelsing; Ellingsen, Torkell

2017-01-01

The datasets presented in this article are related to the research articles entitled “Neutrophil Extracellular Traps in Ulcerative Colitis: A Proteome Analysis of Intestinal Biopsies” (Bennike et al., 2015 [1]), and “Proteome Analysis of Rheumatoid Arthritis Gut Mucosa” (Bennike et al., 2017 [2])...... been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001608 for ulcerative colitis and control samples, and PXD003082 for rheumatoid arthritis samples....

Immersive video

Science.gov (United States)

Moezzi, Saied; Katkere, Arun L.; Jain, Ramesh C.

1996-03-01

Interactive video and television viewers should have the power to control their viewing position. To make this a reality, we introduce the concept of Immersive Video, which employs computer vision and computer graphics technologies to provide remote users a sense of complete immersion when viewing an event. Immersive Video uses multiple videos of an event, captured from different perspectives, to generate a full 3D digital video of that event. That is accomplished by assimilating important information from each video stream into a comprehensive, dynamic, 3D model of the environment. Using this 3D digital video, interactive viewers can then move around the remote environment and observe the events taking place from any desired perspective. Our Immersive Video System currently provides interactive viewing and `walkthrus' of staged karate demonstrations, basketball games, dance performances, and typical campus scenes. In its full realization, Immersive Video will be a paradigm shift in visual communication which will revolutionize television and video media, and become an integral part of future telepresence and virtual reality systems.

Pornography classification: The hidden clues in video space-time.

Science.gov (United States)

Moreira, Daniel; Avila, Sandra; Perez, Mauricio; Moraes, Daniel; Testoni, Vanessa; Valle, Eduardo; Goldenstein, Siome; Rocha, Anderson

2016-11-01

As web technologies and social networks become part of the general public's life, the problem of automatically detecting pornography is into every parent's mind - nobody feels completely safe when their children go online. In this paper, we focus on video-pornography classification, a hard problem in which traditional methods often employ still-image techniques - labeling frames individually prior to a global decision. Frame-based approaches, however, ignore significant cogent information brought by motion. Here, we introduce a space-temporal interest point detector and descriptor called Temporal Robust Features (TRoF). TRoF was custom-tailored for efficient (low processing time and memory footprint) and effective (high classification accuracy and low false negative rate) motion description, particularly suited to the task at hand. We aggregate local information extracted by TRoF into a mid-level representation using Fisher Vectors, the state-of-the-art model of Bags of Visual Words (BoVW). We evaluate our original strategy, contrasting it both to commercial pornography detection solutions, and to BoVW solutions based upon other space-temporal features from the scientific literature. The performance is assessed using the Pornography-2k dataset, a new challenging pornographic benchmark, comprising 2000 web videos and 140h of video footage. The dataset is also a contribution of this work and is very assorted, including both professional and amateur content, and it depicts several genres of pornography, from cartoon to live action, with diverse behavior and ethnicity. The best approach, based on a dense application of TRoF, yields a classification error reduction of almost 79% when compared to the best commercial classifier. A sparse description relying on TRoF detector is also noteworthy, for yielding a classification error reduction of over 69%, with 19× less memory footprint than the dense solution, and yet can also be implemented to meet real-time requirements

Topographical effects of climate dataset and their impacts on the estimation of regional net primary productivity

Science.gov (United States)

Sun, L. Qing; Feng, Feng X.

2014-11-01

In this study, we first built and compared two different climate datasets for Wuling mountainous area in 2010, one of which considered topographical effects during the ANUSPLIN interpolation was referred as terrain-based climate dataset, while the other one did not was called ordinary climate dataset. Then, we quantified the topographical effects of climatic inputs on NPP estimation by inputting two different climate datasets to the same ecosystem model, the Boreal Ecosystem Productivity Simulator (BEPS), to evaluate the importance of considering relief when estimating NPP. Finally, we found the primary contributing variables to the topographical effects through a series of experiments given an overall accuracy of the model output for NPP. The results showed that: (1) The terrain-based climate dataset presented more reliable topographic information and had closer agreements with the station dataset than the ordinary climate dataset at successive time series of 365 days in terms of the daily mean values. (2) On average, ordinary climate dataset underestimated NPP by 12.5% compared with terrain-based climate dataset over the whole study area. (3) The primary climate variables contributing to the topographical effects of climatic inputs for Wuling mountainous area were temperatures, which suggest that it is necessary to correct temperature differences for estimating NPP accurately in such a complex terrain.

Video pedagogy

OpenAIRE

Länsitie, Janne; Stevenson, Blair; Männistö, Riku; Karjalainen, Tommi; Karjalainen, Asko

2016-01-01

The short film is an introduction to the concept of video pedagogy. The five categories of video pedagogy further elaborate how videos can be used as a part of instruction and learning process. Most pedagogical videos represent more than one category. A video itself doesn’t necessarily define the category – the ways in which the video is used as a part of pedagogical script are more defining factors. What five categories did you find? Did you agree with the categories, or are more...

Visualization of conserved structures by fusing highly variable datasets.

Science.gov (United States)

Silverstein, Jonathan C; Chhadia, Ankur; Dech, Fred

2002-01-01

Skill, effort, and time are required to identify and visualize anatomic structures in three-dimensions from radiological data. Fundamentally, automating these processes requires a technique that uses symbolic information not in the dynamic range of the voxel data. We were developing such a technique based on mutual information for automatic multi-modality image fusion (MIAMI Fuse, University of Michigan). This system previously demonstrated facility at fusing one voxel dataset with integrated symbolic structure information to a CT dataset (different scale and resolution) from the same person. The next step of development of our technique was aimed at accommodating the variability of anatomy from patient to patient by using warping to fuse our standard dataset to arbitrary patient CT datasets. A standard symbolic information dataset was created from the full color Visible Human Female by segmenting the liver parenchyma, portal veins, and hepatic veins and overwriting each set of voxels with a fixed color. Two arbitrarily selected patient CT scans of the abdomen were used for reference datasets. We used the warping functions in MIAMI Fuse to align the standard structure data to each patient scan. The key to successful fusion was the focused use of multiple warping control points that place themselves around the structure of interest automatically. The user assigns only a few initial control points to align the scans. Fusion 1 and 2 transformed the atlas with 27 points around the liver to CT1 and CT2 respectively. Fusion 3 transformed the atlas with 45 control points around the liver to CT1 and Fusion 4 transformed the atlas with 5 control points around the portal vein. The CT dataset is augmented with the transformed standard structure dataset, such that the warped structure masks are visualized in combination with the original patient dataset. This combined volume visualization is then rendered interactively in stereo on the ImmersaDesk in an immersive Virtual

A regression method for real-time video quality evaluation

NARCIS (Netherlands)

Torres Vega, M.; Mocanu, D.C.; Liotta, A.; Abdulrazak, B.; Pardede, E.; Steinbauer, M.; Khalil, I.; Anderst-Kotsis, G.

2016-01-01

No-Reference (NR) metrics provide a mechanism to assess video quality in an ever-growing wireless network. Their low computational complexity and functional characteristics make them the primary choice when it comes to realtime content management and mobile streaming control. Unfortunately, common

Correction of raindrop size distributions measured by Parsivel disdrometers, using a two-dimensional video disdrometer as a reference

Directory of Open Access Journals (Sweden)

T. H. Raupach

2015-01-01

Full Text Available The raindrop size distribution (DSD quantifies the microstructure of rainfall and is critical to studying precipitation processes. We present a method to improve the accuracy of DSD measurements from Parsivel (particle size and velocity disdrometers, using a two-dimensional video disdrometer (2DVD as a reference instrument. Parsivel disdrometers bin raindrops into velocity and equivolume diameter classes, but may misestimate the number of drops per class. In our correction method, drop velocities are corrected with reference to theoretical models of terminal drop velocity. We define a filter for raw disdrometer measurements to remove particles that are unlikely to be plausible raindrops. Drop concentrations are corrected such that on average the Parsivel concentrations match those recorded by a 2DVD. The correction can be trained on and applied to data from both generations of OTT Parsivel disdrometers, and indeed any disdrometer in general. The method was applied to data collected during field campaigns in Mediterranean France for a network of first- and second-generation Parsivel disdrometers, and on a first-generation Parsivel in Payerne, Switzerland. We compared the moments of the resulting DSDs to those of a collocated 2DVD, and the resulting DSD-derived rain rates to collocated rain gauges. The correction improved the accuracy of the moments of the Parsivel DSDs, and in the majority of cases the rain rate match with collocated rain gauges was improved. In addition, the correction was shown to be similar for two different climatologies, suggesting its general applicability.

Heterogeneity image patch index and its application to consumer video summarization.

Science.gov (United States)

Dang, Chinh T; Radha, Hayder

2014-06-01

Automatic video summarization is indispensable for fast browsing and efficient management of large video libraries. In this paper, we introduce an image feature that we refer to as heterogeneity image patch (HIP) index. The proposed HIP index provides a new entropy-based measure of the heterogeneity of patches within any picture. By evaluating this index for every frame in a video sequence, we generate a HIP curve for that sequence. We exploit the HIP curve in solving two categories of video summarization applications: key frame extraction and dynamic video skimming. Under the key frame extraction frame-work, a set of candidate key frames is selected from abundant video frames based on the HIP curve. Then, a proposed patch-based image dissimilarity measure is used to create affinity matrix of these candidates. Finally, a set of key frames is extracted from the affinity matrix using a min–max based algorithm. Under video skimming, we propose a method to measure the distance between a video and its skimmed representation. The video skimming problem is then mapped into an optimization framework and solved by minimizing a HIP-based distance for a set of extracted excerpts. The HIP framework is pixel-based and does not require semantic information or complex camera motion estimation. Our simulation results are based on experiments performed on consumer videos and are compared with state-of-the-art methods. It is shown that the HIP approach outperforms other leading methods, while maintaining low complexity.

X-ray computed tomography datasets for forensic analysis of vertebrate fossils

Science.gov (United States)

Rowe, Timothy B.; Luo, Zhe-Xi; Ketcham, Richard A.; Maisano, Jessica A.; Colbert, Matthew W.

2016-01-01

We describe X-ray computed tomography (CT) datasets from three specimens recovered from Early Cretaceous lakebeds of China that illustrate the forensic interpretation of CT imagery for paleontology. Fossil vertebrates from thinly bedded sediments often shatter upon discovery and are commonly repaired as amalgamated mosaics grouted to a solid backing slab of rock or plaster. Such methods are prone to inadvertent error and willful forgery, and once required potentially destructive methods to identify mistakes in reconstruction. CT is an efficient, nondestructive alternative that can disclose many clues about how a specimen was handled and repaired. These annotated datasets illustrate the power of CT in documenting specimen integrity and are intended as a reference in applying CT more broadly to evaluating the authenticity of comparable fossils. PMID:27272251

Computational Methods for Large Spatio-temporal Datasets and Functional Data Ranking

KAUST Repository

Huang, Huang

2017-07-16

This thesis focuses on two topics, computational methods for large spatial datasets and functional data ranking. Both are tackling the challenges of big and high-dimensional data. The first topic is motivated by the prohibitive computational burden in fitting Gaussian process models to large and irregularly spaced spatial datasets. Various approximation methods have been introduced to reduce the computational cost, but many rely on unrealistic assumptions about the process and retaining statistical efficiency remains an issue. We propose a new scheme to approximate the maximum likelihood estimator and the kriging predictor when the exact computation is infeasible. The proposed method provides different types of hierarchical low-rank approximations that are both computationally and statistically efficient. We explore the improvement of the approximation theoretically and investigate the performance by simulations. For real applications, we analyze a soil moisture dataset with 2 million measurements with the hierarchical low-rank approximation and apply the proposed fast kriging to fill gaps for satellite images. The second topic is motivated by rank-based outlier detection methods for functional data. Compared to magnitude outliers, it is more challenging to detect shape outliers as they are often masked among samples. We develop a new notion of functional data depth by taking the integration of a univariate depth function. Having a form of the integrated depth, it shares many desirable features. Furthermore, the novel formation leads to a useful decomposition for detecting both shape and magnitude outliers. Our simulation studies show the proposed outlier detection procedure outperforms competitors in various outlier models. We also illustrate our methodology using real datasets of curves, images, and video frames. Finally, we introduce the functional data ranking technique to spatio-temporal statistics for visualizing and assessing covariance properties, such as

Video microblogging

DEFF Research Database (Denmark)

Bornoe, Nis; Barkhuus, Louise

2010-01-01

Microblogging is a recently popular phenomenon and with the increasing trend for video cameras to be built into mobile phones, a new type of microblogging has entered the arena of electronic communication: video microblogging. In this study we examine video microblogging, which is the broadcasting...... of short videos. A series of semi-structured interviews offers an understanding of why and how video microblogging is used and what the users post and broadcast....

Examining in vivo tympanic membrane mobility using smart phone video-otoscopy and phase-based Eulerian video magnification

Science.gov (United States)

Janatka, Mirek; Ramdoo, Krishan S.; Tatla, Taran; Pachtrachai, Krittin; Elson, Daniel S.; Stoyanov, Danail

2017-03-01

The tympanic membrane (TM) is the bridging element between the pressure waves of sound in air and the ossicular chain. It allows for sound to be conducted into the inner ear, achieving the human sense of hearing. Otitis media with effusion (OME, commonly referred to as `glue ear') is a typical condition in infants that prevents the vibration of the TM and causes conductive hearing loss, this can lead to stunting early stage development if undiagnosed. Furthermore, OME is hard to identify in this age group; as they cannot respond to typical audiometry tests. Tympanometry allows for the mobility of the TM to be examined without patient response, but requires expensive apparatus and specialist training. By combining a smartphone equipped with a 240 frames per second video recording capability with an otoscopic clip-on accessory, this paper presents a novel application of Eulerian Video Magnification (EVM) to video-otology, that could provide assistance in diagnosing OME. We present preliminary results showing a spatio-temporal slice taken from an exaggerated video visualization of the TM being excited in vivo on a healthy ear. Our preliminary results demonstrate the potential for using such an approach for diagnosing OME under visual inspection as alternative to tympanometry, which could be used remotely and hence help diagnosis in a wider population pool.

NOAA Line Shapefile- Locations of Phantom S2 ROV Underwater Video Transects, US Virgin Islands, Project NF-05-05, 2005, UTM 20N WGS84

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a line shapefile showing the trackline of various Remotely Operated Vehicle (ROV) underwater video transects in the US Virgin Islands.NOAA's...

A Depth Video Sensor-Based Life-Logging Human Activity Recognition System for Elderly Care in Smart Indoor Environments

Directory of Open Access Journals (Sweden)

Ahmad Jalal

2014-07-01

Full Text Available Recent advancements in depth video sensors technologies have made human activity recognition (HAR realizable for elderly monitoring applications. Although conventional HAR utilizes RGB video sensors, HAR could be greatly improved with depth video sensors which produce depth or distance information. In this paper, a depth-based life logging HAR system is designed to recognize the daily activities of elderly people and turn these environments into an intelligent living space. Initially, a depth imaging sensor is used to capture depth silhouettes. Based on these silhouettes, human skeletons with joint information are produced which are further used for activity recognition and generating their life logs. The life-logging system is divided into two processes. Firstly, the training system includes data collection using a depth camera, feature extraction and training for each activity via Hidden Markov Models. Secondly, after training, the recognition engine starts to recognize the learned activities and produces life logs. The system was evaluated using life logging features against principal component and independent component features and achieved satisfactory recognition rates against the conventional approaches. Experiments conducted on the smart indoor activity datasets and the MSRDailyActivity3D dataset show promising results. The proposed system is directly applicable to any elderly monitoring system, such as monitoring healthcare problems for elderly people, or examining the indoor activities of people at home, office or hospital.

A depth video sensor-based life-logging human activity recognition system for elderly care in smart indoor environments.

Science.gov (United States)

Jalal, Ahmad; Kamal, Shaharyar; Kim, Daijin

2014-07-02

Recent advancements in depth video sensors technologies have made human activity recognition (HAR) realizable for elderly monitoring applications. Although conventional HAR utilizes RGB video sensors, HAR could be greatly improved with depth video sensors which produce depth or distance information. In this paper, a depth-based life logging HAR system is designed to recognize the daily activities of elderly people and turn these environments into an intelligent living space. Initially, a depth imaging sensor is used to capture depth silhouettes. Based on these silhouettes, human skeletons with joint information are produced which are further used for activity recognition and generating their life logs. The life-logging system is divided into two processes. Firstly, the training system includes data collection using a depth camera, feature extraction and training for each activity via Hidden Markov Models. Secondly, after training, the recognition engine starts to recognize the learned activities and produces life logs. The system was evaluated using life logging features against principal component and independent component features and achieved satisfactory recognition rates against the conventional approaches. Experiments conducted on the smart indoor activity datasets and the MSRDailyActivity3D dataset show promising results. The proposed system is directly applicable to any elderly monitoring system, such as monitoring healthcare problems for elderly people, or examining the indoor activities of people at home, office or hospital.

Comparing two remote video survey methods for spatial predictions of the distribution and environmental niche suitability of demersal fishes.

Science.gov (United States)

Galaiduk, Ronen; Radford, Ben T; Wilson, Shaun K; Harvey, Euan S

2017-12-15

Information on habitat associations from survey data, combined with spatial modelling, allow the development of more refined species distribution modelling which may identify areas of high conservation/fisheries value and consequentially improve conservation efforts. Generalised additive models were used to model the probability of occurrence of six focal species after surveys that utilised two remote underwater video sampling methods (i.e. baited and towed video). Models developed for the towed video method had consistently better predictive performance for all but one study species although only three models had a good to fair fit, and the rest were poor fits, highlighting the challenges associated with modelling habitat associations of marine species in highly homogenous, low relief environments. Models based on baited video dataset regularly included large-scale measures of structural complexity, suggesting fish attraction to a single focus point by bait. Conversely, models based on the towed video data often incorporated small-scale measures of habitat complexity and were more likely to reflect true species-habitat relationships. The cost associated with use of the towed video systems for surveying low-relief seascapes was also relatively low providing additional support for considering this method for marine spatial ecological modelling.

Predicting human activities in sequences of actions in RGB-D videos

Science.gov (United States)

Jardim, David; Nunes, Luís.; Dias, Miguel

2017-03-01

In our daily activities we perform prediction or anticipation when interacting with other humans or with objects. Prediction of human activity made by computers has several potential applications: surveillance systems, human computer interfaces, sports video analysis, human-robot-collaboration, games and health-care. We propose a system capable of recognizing and predicting human actions using supervised classifiers trained with automatically labeled data evaluated in our human activity RGB-D dataset (recorded with a Kinect sensor) and using only the position of the main skeleton joints to extract features. Using conditional random fields (CRFs) to model the sequential nature of actions in a sequence has been used before, but where other approaches try to predict an outcome or anticipate ahead in time (seconds), we try to predict what will be the next action of a subject. Our results show an activity prediction accuracy of 89.9% using an automatically labeled dataset.

RARD: The Related-Article Recommendation Dataset

OpenAIRE

Beel, Joeran; Carevic, Zeljko; Schaible, Johann; Neusch, Gabor

2017-01-01

Recommender-system datasets are used for recommender-system evaluations, training machine-learning algorithms, and exploring user behavior. While there are many datasets for recommender systems in the domains of movies, books, and music, there are rather few datasets from research-paper recommender systems. In this paper, we introduce RARD, the Related-Article Recommendation Dataset, from the digital library Sowiport and the recommendation-as-a-service provider Mr. DLib. The dataset contains ...

The effects of multiview depth video compression on multiview rendering

NARCIS (Netherlands)

Merkle, P.; Morvan, Y.; Smolic, A.; Farin, D.S.; Mueller, K.; With, de P.H.N.; Wiegang, T.

2009-01-01

This article investigates the interaction between different techniques for depth compression and view synthesis rendering with multiview video plus scene depth data. Two different approaches for depth coding are compared, namely H.264/MVC, using temporal and inter-view reference images for efficient

Dashboard Videos

Science.gov (United States)

Gleue, Alan D.; Depcik, Chris; Peltier, Ted

2012-01-01

Last school year, I had a web link emailed to me entitled "A Dashboard Physics Lesson." The link, created and posted by Dale Basier on his "Lab Out Loud" blog, illustrates video of a car's speedometer synchronized with video of the road. These two separate video streams are compiled into one video that students can watch and analyze. After seeing…

Multivendor Spectral-Domain Optical Coherence Tomography Dataset, Observer Annotation Performance Evaluation, and Standardized Evaluation Framework for Intraretinal Cystoid Fluid Segmentation

Directory of Open Access Journals (Sweden)

Jing Wu

2016-01-01

Full Text Available Development of image analysis and machine learning methods for segmentation of clinically significant pathology in retinal spectral-domain optical coherence tomography (SD-OCT, used in disease detection and prediction, is limited due to the availability of expertly annotated reference data. Retinal segmentation methods use datasets that either are not publicly available, come from only one device, or use different evaluation methodologies making them difficult to compare. Thus we present and evaluate a multiple expert annotated reference dataset for the problem of intraretinal cystoid fluid (IRF segmentation, a key indicator in exudative macular disease. In addition, a standardized framework for segmentation accuracy evaluation, applicable to other pathological structures, is presented. Integral to this work is the dataset used which must be fit for purpose for IRF segmentation algorithm training and testing. We describe here a multivendor dataset comprised of 30 scans. Each OCT scan for system training has been annotated by multiple graders using a proprietary system. Evaluation of the intergrader annotations shows a good correlation, thus making the reproducibly annotated scans suitable for the training and validation of image processing and machine learning based segmentation methods. The dataset will be made publicly available in the form of a segmentation Grand Challenge.

Video game addiction, ADHD symptomatology, and video game reinforcement.

Science.gov (United States)

Mathews, Christine L; Morrell, Holly E R; Molle, Jon E

2018-06-06

Up to 23% of people who play video games report symptoms of addiction. Individuals with attention deficit hyperactivity disorder (ADHD) may be at increased risk for video game addiction, especially when playing games with more reinforcing properties. The current study tested whether level of video game reinforcement (type of game) places individuals with greater ADHD symptom severity at higher risk for developing video game addiction. Adult video game players (N = 2,801; Mean age = 22.43, SD = 4.70; 93.30% male; 82.80% Caucasian) completed an online survey. Hierarchical multiple linear regression analyses were used to test type of game, ADHD symptom severity, and the interaction between type of game and ADHD symptomatology as predictors of video game addiction severity, after controlling for age, gender, and weekly time spent playing video games. ADHD symptom severity was positively associated with increased addiction severity (b = .73 and .68, ps .05. The relationship between ADHD symptom severity and addiction severity did not depend on the type of video game played or preferred most, ps > .05. Gamers who have greater ADHD symptom severity may be at greater risk for developing symptoms of video game addiction and its negative consequences, regardless of type of video game played or preferred most. Individuals who report ADHD symptomatology and also identify as gamers may benefit from psychoeducation about the potential risk for problematic play.

Isfahan MISP Dataset.

Science.gov (United States)

Kashefpur, Masoud; Kafieh, Rahele; Jorjandi, Sahar; Golmohammadi, Hadis; Khodabande, Zahra; Abbasi, Mohammadreza; Teifuri, Nilufar; Fakharzadeh, Ali Akbar; Kashefpoor, Maryam; Rabbani, Hossein

2017-01-01

An online depository was introduced to share clinical ground truth with the public and provide open access for researchers to evaluate their computer-aided algorithms. PHP was used for web programming and MySQL for database managing. The website was entitled "biosigdata.com." It was a fast, secure, and easy-to-use online database for medical signals and images. Freely registered users could download the datasets and could also share their own supplementary materials while maintaining their privacies (citation and fee). Commenting was also available for all datasets, and automatic sitemap and semi-automatic SEO indexing have been set for the site. A comprehensive list of available websites for medical datasets is also presented as a Supplementary (http://journalonweb.com/tempaccess/4800.584.JMSS_55_16I3253.pdf).

Crowdsourcing for reference correspondence generation in endoscopic images.

Science.gov (United States)

Maier-Hein, Lena; Mersmann, Sven; Kondermann, Daniel; Stock, Christian; Kenngott, Hannes Gotz; Sanchez, Alexandro; Wagner, Martin; Preukschas, Anas; Wekerle, Anna-Laura; Helfert, Stefanie; Bodenstedt, Sebastian; Speidel, Stefanie

2014-01-01

Computer-assisted minimally-invasive surgery (MIS) is often based on algorithms that require establishing correspondences between endoscopic images. However, reference annotations frequently required to train or validate a method are extremely difficult to obtain because they are typically made by a medical expert with very limited resources, and publicly available data sets are still far too small to capture the wide range of anatomical/scene variance. Crowdsourcing is a new trend that is based on outsourcing cognitive tasks to many anonymous untrained individuals from an online community. To our knowledge, this paper is the first to investigate the concept of crowdsourcing in the context of endoscopic video image annotation for computer-assisted MIS. According to our study on publicly available in vivo data with manual reference annotations, anonymous non-experts obtain a median annotation error of 2 px (n = 10,000). By applying cluster analysis to multiple annotations per correspondence, this error can be reduced to about 1 px, which is comparable to that obtained by medical experts (n = 500). We conclude that crowdsourcing is a viable method for generating high quality reference correspondences in endoscopic video images.

An enhanced topologically significant directed random walk in cancer classification using gene expression datasets

Directory of Open Access Journals (Sweden)

Choon Sen Seah

2017-12-01

Full Text Available Microarray technology has become one of the elementary tools for researchers to study the genome of organisms. As the complexity and heterogeneity of cancer is being increasingly appreciated through genomic analysis, cancerous classification is an emerging important trend. Significant directed random walk is proposed as one of the cancerous classification approach which have higher sensitivity of risk gene prediction and higher accuracy of cancer classification. In this paper, the methodology and material used for the experiment are presented. Tuning parameter selection method and weight as parameter are applied in proposed approach. Gene expression dataset is used as the input datasets while pathway dataset is used to build a directed graph, as reference datasets, to complete the bias process in random walk approach. In addition, we demonstrate that our approach can improve sensitive predictions with higher accuracy and biological meaningful classification result. Comparison result takes place between significant directed random walk and directed random walk to show the improvement in term of sensitivity of prediction and accuracy of cancer classification.

Enhancement system of nighttime infrared video image and visible video image

Science.gov (United States)

Wang, Yue; Piao, Yan

2016-11-01

Visibility of Nighttime video image has a great significance for military and medicine areas, but nighttime video image has so poor quality that we can't recognize the target and background. Thus we enhance the nighttime video image by fuse infrared video image and visible video image. According to the characteristics of infrared and visible images, we proposed improved sift algorithm andαβ weighted algorithm to fuse heterologous nighttime images. We would deduced a transfer matrix from improved sift algorithm. The transfer matrix would rapid register heterologous nighttime images. And theαβ weighted algorithm can be applied in any scene. In the video image fusion system, we used the transfer matrix to register every frame and then used αβ weighted method to fuse every frame, which reached the time requirement soft video. The fused video image not only retains the clear target information of infrared video image, but also retains the detail and color information of visible video image and the fused video image can fluency play.

Towards a Video Passive Content Fingerprinting Method for Partial-Copy Detection Robust against Non-Simulated Attacks.

Directory of Open Access Journals (Sweden)

Zobeida Jezabel Guzman-Zavaleta

Full Text Available Passive content fingerprinting is widely used for video content identification and monitoring. However, many challenges remain unsolved especially for partial-copies detection. The main challenge is to find the right balance between the computational cost of fingerprint extraction and fingerprint dimension, without compromising detection performance against various attacks (robustness. Fast video detection performance is desirable in several modern applications, for instance, in those where video detection involves the use of large video databases or in applications requiring real-time video detection of partial copies, a process whose difficulty increases when videos suffer severe transformations. In this context, conventional fingerprinting methods are not fully suitable to cope with the attacks and transformations mentioned before, either because the robustness of these methods is not enough or because their execution time is very high, where the time bottleneck is commonly found in the fingerprint extraction and matching operations. Motivated by these issues, in this work we propose a content fingerprinting method based on the extraction of a set of independent binary global and local fingerprints. Although these features are robust against common video transformations, their combination is more discriminant against severe video transformations such as signal processing attacks, geometric transformations and temporal and spatial desynchronization. Additionally, we use an efficient multilevel filtering system accelerating the processes of fingerprint extraction and matching. This multilevel filtering system helps to rapidly identify potential similar video copies upon which the fingerprint process is carried out only, thus saving computational time. We tested with datasets of real copied videos, and the results show how our method outperforms state-of-the-art methods regarding detection scores. Furthermore, the granularity of our method makes

Illustrating Geology With Customized Video in Introductory Geoscience Courses

Science.gov (United States)

Magloughlin, J. F.

2008-12-01

clear, and appropriate materials accompany the videos. Retention of primary concepts presented within videos is at least as high as ordinary lecture material, and student questions reference the videos more than any other matter. Use of the videos has created more variety in the course, a better connection to real world geology, and a more palatable experience for students who increasingly describe themselves as visual learners.

Canvas Pocket Reference Scripted Graphics for HTML5

CERN Document Server

Flanagan, David

2010-01-01

The Canvas element is a revolutionary feature of HTML5 that enables powerful graphics for rich Internet applications, and this pocket reference provides the essentials you need to put this element to work. If you have working knowledge of JavaScript, this book will help you create detailed, interactive, and animated graphics -- from charts to animations to video games -- whether you're a web designer or a programmer interested in graphics. Canvas Pocket Reference provides both a tutorial that covers all of the element's features with plenty of examples and a definitive reference to each of t

SnapVideo: Personalized Video Generation for a Sightseeing Trip.

Science.gov (United States)

Zhang, Luming; Jing, Peiguang; Su, Yuting; Zhang, Chao; Shaoz, Ling

2017-11-01

Leisure tourism is an indispensable activity in urban people's life. Due to the popularity of intelligent mobile devices, a large number of photos and videos are recorded during a trip. Therefore, the ability to vividly and interestingly display these media data is a useful technique. In this paper, we propose SnapVideo, a new method that intelligently converts a personal album describing of a trip into a comprehensive, aesthetically pleasing, and coherent video clip. The proposed framework contains three main components. The scenic spot identification model first personalizes the video clips based on multiple prespecified audience classes. We then search for some auxiliary related videos from YouTube 1 according to the selected photos. To comprehensively describe a scenery, the view generation module clusters the crawled video frames into a number of views. Finally, a probabilistic model is developed to fit the frames from multiple views into an aesthetically pleasing and coherent video clip, which optimally captures the semantics of a sightseeing trip. Extensive user studies demonstrated the competitiveness of our method from an aesthetic point of view. Moreover, quantitative analysis reflects that semantically important spots are well preserved in the final video clip. 1 https://www.youtube.com/.

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.

Algorithm for Video Summarization of Bronchoscopy Procedures

Directory of Open Access Journals (Sweden)

Leszczuk Mikołaj I

2011-12-01

Full Text Available Abstract Background The duration of bronchoscopy examinations varies considerably depending on the diagnostic and therapeutic procedures used. It can last more than 20 minutes if a complex diagnostic work-up is included. With wide access to videobronchoscopy, the whole procedure can be recorded as a video sequence. Common practice relies on an active attitude of the bronchoscopist who initiates the recording process and usually chooses to archive only selected views and sequences. However, it may be important to record the full bronchoscopy procedure as documentation when liability issues are at stake. Furthermore, an automatic recording of the whole procedure enables the bronchoscopist to focus solely on the performed procedures. Video recordings registered during bronchoscopies include a considerable number of frames of poor quality due to blurry or unfocused images. It seems that such frames are unavoidable due to the relatively tight endobronchial space, rapid movements of the respiratory tract due to breathing or coughing, and secretions which occur commonly in the bronchi, especially in patients suffering from pulmonary disorders. Methods The use of recorded bronchoscopy video sequences for diagnostic, reference and educational purposes could be considerably extended with efficient, flexible summarization algorithms. Thus, the authors developed a prototype system to create shortcuts (called summaries or abstracts of bronchoscopy video recordings. Such a system, based on models described in previously published papers, employs image analysis methods to exclude frames or sequences of limited diagnostic or education value. Results The algorithm for the selection or exclusion of specific frames or shots from video sequences recorded during bronchoscopy procedures is based on several criteria, including automatic detection of "non-informative", frames showing the branching of the airways and frames including pathological lesions. Conclusions

Video and accelerometer-based motion analysis for automated surgical skills assessment.

Science.gov (United States)

Zia, Aneeq; Sharma, Yachna; Bettadapura, Vinay; Sarin, Eric L; Essa, Irfan

2018-03-01

Basic surgical skills of suturing and knot tying are an essential part of medical training. Having an automated system for surgical skills assessment could help save experts time and improve training efficiency. There have been some recent attempts at automated surgical skills assessment using either video analysis or acceleration data. In this paper, we present a novel approach for automated assessment of OSATS-like surgical skills and provide an analysis of different features on multi-modal data (video and accelerometer data). We conduct a large study for basic surgical skill assessment on a dataset that contained video and accelerometer data for suturing and knot-tying tasks. We introduce "entropy-based" features-approximate entropy and cross-approximate entropy, which quantify the amount of predictability and regularity of fluctuations in time series data. The proposed features are compared to existing methods of Sequential Motion Texture, Discrete Cosine Transform and Discrete Fourier Transform, for surgical skills assessment. We report average performance of different features across all applicable OSATS-like criteria for suturing and knot-tying tasks. Our analysis shows that the proposed entropy-based features outperform previous state-of-the-art methods using video data, achieving average classification accuracies of 95.1 and 92.2% for suturing and knot tying, respectively. For accelerometer data, our method performs better for suturing achieving 86.8% average accuracy. We also show that fusion of video and acceleration features can improve overall performance for skill assessment. Automated surgical skills assessment can be achieved with high accuracy using the proposed entropy features. Such a system can significantly improve the efficiency of surgical training in medical schools and teaching hospitals.

Evaluation of video capture equipment for secondary image acquisition in the PACS.

Science.gov (United States)

Sukenobu, Yoshiharu; Sasagaki, Michihiro; Hirabuki, Norio; Naito, Hiroaki; Narumi, Yoshifumi; Inamura, Kiyonari

2002-01-01

There are many cases in which picture archiving and communication systems (PACS) are built with old-type existing modalities with no DICOM output. One of the methods for interfacing them to the PACS is to implement video capture (/ frame grabber) equipment. This equipment takes analog video signal output from medical imaging modalities, and amplitude of the video signal is A/D converted and supplied to the PACS. In this report, we measured and evaluated the accuracy at which this video capture equipment could capture the image. From the physical evaluation, we found the pixel values of an original image and its captured image were almost equal in gray level from 20%-90%. The change in the pixel values of a captured image was +/-3 on average. The change of gray level concentration was acceptable and had an average standard deviation of around 0.63. As for resolution, the degradation was observed at the highest physical level. In a subjective evaluation, the evaluation value of the CT image had a grade of 2.81 on the average (the same quality for a reference image was set to a grade of 3.0). Abnormalities in heads, chests, and abdomens were judged not to influence diagnostic accuracy. Some small differences were seen when comparing captured and reference images, but they are recognized as having no influence on the diagnoses.

Chemical elements in the environment: multi-element geochemical datasets from continental to national scale surveys on four continents

Science.gov (United States)

Caritat, Patrice de; Reimann, Clemens; Smith, David; Wang, Xueqiu

2017-01-01

During the last 10-20 years, Geological Surveys around the world have undertaken a major effort towards delivering fully harmonized and tightly quality-controlled low-density multi-element soil geochemical maps and datasets of vast regions including up to whole continents. Concentrations of between 45 and 60 elements commonly have been determined in a variety of different regolith types (e.g., sediment, soil). The multi-element datasets are published as complete geochemical atlases and made available to the general public. Several other geochemical datasets covering smaller areas but generally at a higher spatial density are also available. These datasets may, however, not be found by superficial internet-based searches because the elements are not mentioned individually either in the title or in the keyword lists of the original references. This publication attempts to increase the visibility and discoverability of these fundamental background datasets covering large areas up to whole continents.

The Lunar Source Disk: Old Lunar Datasets on a New CD-ROM

Science.gov (United States)

Hiesinger, H.

1998-01-01

datasets to a selected standard geometry in order to create an "image-cube"-like data pool for further interpretation. The starting point was a number of datasets on a CD-ROM published by the Lunar Consortium. The task of creating an uniform data pool was further complicated by some missing or wrong references and keys on the Lunar Consortium CD as well as erroneous reproduction of some datasets in the literature.

Augmented video viewing: transforming video consumption into an active experience

OpenAIRE

WIJNANTS, Maarten; Leën, Jeroen; QUAX, Peter; LAMOTTE, Wim

2014-01-01

Traditional video productions fail to cater to the interactivity standards that the current generation of digitally native customers have become accustomed to. This paper therefore advertises the \\activation" of the video consumption process. In particular, it proposes to enhance HTML5 video playback with interactive features in order to transform video viewing into a dynamic pastime. The objective is to enable the authoring of more captivating and rewarding video experiences for end-users. T...

No-reference analysis of decoded MPEG images for PSNR estimation and post-processing

DEFF Research Database (Denmark)

Forchhammer, Søren; Li, Huiying; Andersen, Jakob Dahl

2011-01-01

We propose no-reference analysis and processing of DCT (Discrete Cosine Transform) coded images based on estimation of selected MPEG parameters from the decoded video. The goal is to assess MPEG video quality and perform post-processing without access to neither the original stream nor the code...... stream. Solutions are presented for MPEG-2 video. A method to estimate the quantization parameters of DCT coded images and MPEG I-frames at the macro-block level is presented. The results of this analysis is used for deblocking and deringing artifact reduction and no-reference PSNR estimation without...... code stream access. An adaptive deringing method using texture classification is presented. On the test set, the quantization parameters in MPEG-2 I-frames are estimated with an overall accuracy of 99.9% and the PSNR is estimated with an overall average error of 0.3dB. The deringing and deblocking...

A method for generating large datasets of organ geometries for radiotherapy treatment planning studies

International Nuclear Information System (INIS)

Hu, Nan; Cerviño, Laura; Segars, Paul; Lewis, John; Shan, Jinlu; Jiang, Steve; Zheng, Xiaolin; Wang, Ge

2014-01-01

With the rapidly increasing application of adaptive radiotherapy, large datasets of organ geometries based on the patient’s anatomy are desired to support clinical application or research work, such as image segmentation, re-planning, and organ deformation analysis. Sometimes only limited datasets are available in clinical practice. In this study, we propose a new method to generate large datasets of organ geometries to be utilized in adaptive radiotherapy. Given a training dataset of organ shapes derived from daily cone-beam CT, we align them into a common coordinate frame and select one of the training surfaces as reference surface. A statistical shape model of organs was constructed, based on the establishment of point correspondence between surfaces and non-uniform rational B-spline (NURBS) representation. A principal component analysis is performed on the sampled surface points to capture the major variation modes of each organ. A set of principal components and their respective coefficients, which represent organ surface deformation, were obtained, and a statistical analysis of the coefficients was performed. New sets of statistically equivalent coefficients can be constructed and assigned to the principal components, resulting in a larger geometry dataset for the patient’s organs. These generated organ geometries are realistic and statistically representative

Open University Learning Analytics dataset.

Science.gov (United States)

Kuzilek, Jakub; Hlosta, Martin; Zdrahal, Zdenek

2017-11-28

Learning Analytics focuses on the collection and analysis of learners' data to improve their learning experience by providing informed guidance and to optimise learning materials. To support the research in this area we have developed a dataset, containing data from courses presented at the Open University (OU). What makes the dataset unique is the fact that it contains demographic data together with aggregated clickstream data of students' interactions in the Virtual Learning Environment (VLE). This enables the analysis of student behaviour, represented by their actions. The dataset contains the information about 22 courses, 32,593 students, their assessment results, and logs of their interactions with the VLE represented by daily summaries of student clicks (10,655,280 entries). The dataset is freely available at https://analyse.kmi.open.ac.uk/open_dataset under a CC-BY 4.0 license.

Occurrence of aspiration pneumonia in dysphagic children post video fluoroscopy

Directory of Open Access Journals (Sweden)

Lagos, Hellen Nataly Correia

2011-10-01

Full Text Available Introduction: The literature reports that when it comes of instrumental assessment of swallowing in children, undoubtedly, video fluoroscopy of swallow offers great advantages over the endoscopic study. Objective: Check the risk of aspiration pneumonia after the study of swallowing by video fluoroscopy, in children with dysphagia. Method: In a study of prospective cutting, participated 16 children aged between 6 months and 10 years, with an average of 5,2 years, referred for study of swallowing by video fluoroscopy. Were tested 4 consistencies, pudding, nectar, honey and liquid. The presences of signs and/or respiratory symptoms were evaluated pre and post study of deglutition by video fluoroscopy, through history and clinical exam. When necessary was asked chest x-ray. Results: Of 16 children, 5 didn't presented dysphagia. In 11 children the exam showed 4 with mild dysphagia, 2 moderate and 5 severe, as classification of OTT (1996 - Classification of severity of dysphagia to the video fluoroscopy. Of the 7 children who aspirated during the exam, only 1 presented respiratory symptoms after the deglutition study, but without signal of pneumonia to the physical examination. Conclusion: In the studied population there were no occurrences of aspiration pneumonia after the study of deglutition was performed by video fluoroscopy, despite the occurrence of aspiration during the exam in about 50% of cases.

Let the Game Begin: Ergodic as an Approach for Video Game Translation

Directory of Open Access Journals (Sweden)

Sf. Lukfianka Sanjaya Purnama, Sf. Luthfie Arguby Purnomo, Dyah Nugrahani

2017-01-01

Full Text Available This paper attempts to propose ergodic as an approach for video game translation. The word approach here refers to an approach for translation products and to an approach for the translation process. The steps to formulate ergodic as an approach are first, Aarseth’sergodic literature is reviewed to elicit a basis for comprehension toward its relationship with video games and video game translation Secondly, taking the translation of Electronic Arts’Need for Speed: Own the City, Midway’s Mortal Kombat: Unchained, and Konami’s Metal Gear Solid, ergodic based approach for video game translation is formulated. The formulation signifies that ergodic, as an approach for video game translation, revolves around the treatment of video games as a cybertext from which scriptons, textons, and traversal functions as the configurative mechanism influence the selection of translation strategies and the transferability of variables and traversal function, game aesthetics, and ludus and narrative of the games. The challenges countered when treating video games as a cybertext are the necessities for the translators to convey anamorphosis, mechanical and narrative hidden meaning of the analyzed frame, to consider the textonomy of the games, and at the same time to concern on GILT (Globalization, Internationalization, Localization, and Translation.

Dataset concerning the analytical approximation of the Ae3 temperature

Directory of Open Access Journals (Sweden)

B.L. Ennis

2017-02-01

The dataset includes the terms of the function and the values for the polynomial coefficients for major alloying elements in steel. A short description of the approximation method used to derive and validate the coefficients has also been included. For discussion and application of this model, please refer to the full length article entitled “The role of aluminium in chemical and phase segregation in a TRIP-assisted dual phase steel” 10.1016/j.actamat.2016.05.046 (Ennis et al., 2016 [1].

NOAA Line Shapefile- Locations of Phantom S2 ROV Underwater Video Transects, US Virgin Islands, Project NF-05-05, 2005, UTM 20N WGS84 (NCEI Accession 0131860)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a line shapefile showing the trackline of various Remotely Operated Vehicle (ROV) underwater video transects in the US Virgin Islands.NOAA's...

ORBDA: An openEHR benchmark dataset for performance assessment of electronic health record servers.

Directory of Open Access Journals (Sweden)

Douglas Teodoro

Full Text Available The openEHR specifications are designed to support implementation of flexible and interoperable Electronic Health Record (EHR systems. Despite the increasing number of solutions based on the openEHR specifications, it is difficult to find publicly available healthcare datasets in the openEHR format that can be used to test, compare and validate different data persistence mechanisms for openEHR. To foster research on openEHR servers, we present the openEHR Benchmark Dataset, ORBDA, a very large healthcare benchmark dataset encoded using the openEHR formalism. To construct ORBDA, we extracted and cleaned a de-identified dataset from the Brazilian National Healthcare System (SUS containing hospitalisation and high complexity procedures information and formalised it using a set of openEHR archetypes and templates. Then, we implemented a tool to enrich the raw relational data and convert it into the openEHR model using the openEHR Java reference model library. The ORBDA dataset is available in composition, versioned composition and EHR openEHR representations in XML and JSON formats. In total, the dataset contains more than 150 million composition records. We describe the dataset and provide means to access it. Additionally, we demonstrate the usage of ORBDA for evaluating inserting throughput and query latency performances of some NoSQL database management systems. We believe that ORBDA is a valuable asset for assessing storage models for openEHR-based information systems during the software engineering process. It may also be a suitable component in future standardised benchmarking of available openEHR storage platforms.

ORBDA: An openEHR benchmark dataset for performance assessment of electronic health record servers

Science.gov (United States)

Sundvall, Erik; João Junior, Mario; Ruch, Patrick; Miranda Freire, Sergio

2018-01-01

The openEHR specifications are designed to support implementation of flexible and interoperable Electronic Health Record (EHR) systems. Despite the increasing number of solutions based on the openEHR specifications, it is difficult to find publicly available healthcare datasets in the openEHR format that can be used to test, compare and validate different data persistence mechanisms for openEHR. To foster research on openEHR servers, we present the openEHR Benchmark Dataset, ORBDA, a very large healthcare benchmark dataset encoded using the openEHR formalism. To construct ORBDA, we extracted and cleaned a de-identified dataset from the Brazilian National Healthcare System (SUS) containing hospitalisation and high complexity procedures information and formalised it using a set of openEHR archetypes and templates. Then, we implemented a tool to enrich the raw relational data and convert it into the openEHR model using the openEHR Java reference model library. The ORBDA dataset is available in composition, versioned composition and EHR openEHR representations in XML and JSON formats. In total, the dataset contains more than 150 million composition records. We describe the dataset and provide means to access it. Additionally, we demonstrate the usage of ORBDA for evaluating inserting throughput and query latency performances of some NoSQL database management systems. We believe that ORBDA is a valuable asset for assessing storage models for openEHR-based information systems during the software engineering process. It may also be a suitable component in future standardised benchmarking of available openEHR storage platforms. PMID:29293556

ORBDA: An openEHR benchmark dataset for performance assessment of electronic health record servers.

Science.gov (United States)

Teodoro, Douglas; Sundvall, Erik; João Junior, Mario; Ruch, Patrick; Miranda Freire, Sergio

2018-01-01

The openEHR specifications are designed to support implementation of flexible and interoperable Electronic Health Record (EHR) systems. Despite the increasing number of solutions based on the openEHR specifications, it is difficult to find publicly available healthcare datasets in the openEHR format that can be used to test, compare and validate different data persistence mechanisms for openEHR. To foster research on openEHR servers, we present the openEHR Benchmark Dataset, ORBDA, a very large healthcare benchmark dataset encoded using the openEHR formalism. To construct ORBDA, we extracted and cleaned a de-identified dataset from the Brazilian National Healthcare System (SUS) containing hospitalisation and high complexity procedures information and formalised it using a set of openEHR archetypes and templates. Then, we implemented a tool to enrich the raw relational data and convert it into the openEHR model using the openEHR Java reference model library. The ORBDA dataset is available in composition, versioned composition and EHR openEHR representations in XML and JSON formats. In total, the dataset contains more than 150 million composition records. We describe the dataset and provide means to access it. Additionally, we demonstrate the usage of ORBDA for evaluating inserting throughput and query latency performances of some NoSQL database management systems. We believe that ORBDA is a valuable asset for assessing storage models for openEHR-based information systems during the software engineering process. It may also be a suitable component in future standardised benchmarking of available openEHR storage platforms.

Multi-Task Video Captioning with Video and Entailment Generation

OpenAIRE

Pasunuru, Ramakanth; Bansal, Mohit

2017-01-01

Video captioning, the task of describing the content of a video, has seen some promising improvements in recent years with sequence-to-sequence models, but accurately learning the temporal and logical dynamics involved in the task still remains a challenge, especially given the lack of sufficient annotated data. We improve video captioning by sharing knowledge with two related directed-generation tasks: a temporally-directed unsupervised video prediction task to learn richer context-aware vid...

Streaming Video--The Wave of the Video Future!

Science.gov (United States)

Brown, Laura

2004-01-01

Videos and DVDs give the teachers more flexibility than slide projectors, filmstrips, and 16mm films but teachers and students are excited about a new technology called streaming. Streaming allows the educators to view videos on demand via the Internet, which works through the transfer of digital media like video, and voice data that is received…

A video authentication technique

International Nuclear Information System (INIS)

Johnson, C.S.

1987-01-01

Unattended video surveillance systems are particularly vulnerable to the substitution of false video images into the cable that connects the camera to the video recorder. New technology has made it practical to insert a solid state video memory into the video cable, freeze a video image from the camera, and hold this image as long as desired. Various techniques, such as line supervision and sync detection, have been used to detect video cable tampering. The video authentication technique described in this paper uses the actual video image from the camera as the basis for detecting any image substitution made during the transmission of the video image to the recorder. The technique, designed for unattended video systems, can be used for any video transmission system where a two-way digital data link can be established. The technique uses similar microprocessor circuitry at the video camera and at the video recorder to select sample points in the video image for comparison. The gray scale value of these points is compared at the recorder controller and if the values agree within limits, the image is authenticated. If a significantly different image was substituted, the comparison would fail at a number of points and the video image would not be authenticated. The video authentication system can run as a stand-alone system or at the request of another system

Forest restoration: a global dataset for biodiversity and vegetation structure.

Science.gov (United States)

Crouzeilles, Renato; Ferreira, Mariana S; Curran, Michael

2016-08-01

Restoration initiatives are becoming increasingly applied around the world. Billions of dollars have been spent on ecological restoration research and initiatives, but restoration outcomes differ widely among these initiatives in part due to variable socioeconomic and ecological contexts. Here, we present the most comprehensive dataset gathered to date on forest restoration. It encompasses 269 primary studies across 221 study landscapes in 53 countries and contains 4,645 quantitative comparisons between reference ecosystems (e.g., old-growth forest) and degraded or restored ecosystems for five taxonomic groups (mammals, birds, invertebrates, herpetofauna, and plants) and five measures of vegetation structure reflecting different ecological processes (cover, density, height, biomass, and litter). We selected studies that (1) were conducted in forest ecosystems; (2) had multiple replicate sampling sites to measure indicators of biodiversity and/or vegetation structure in reference and restored and/or degraded ecosystems; and (3) used less-disturbed forests as a reference to the ecosystem under study. We recorded (1) latitude and longitude; (2) study year; (3) country; (4) biogeographic realm; (5) past disturbance type; (6) current disturbance type; (7) forest conversion class; (8) restoration activity; (9) time that a system has been disturbed; (10) time elapsed since restoration started; (11) ecological metric used to assess biodiversity; and (12) quantitative value of the ecological metric of biodiversity and/or vegetation structure for reference and restored and/or degraded ecosystems. These were the most common data available in the selected studies. We also estimated forest cover and configuration in each study landscape using a recently developed 1 km consensus land cover dataset. We measured forest configuration as the (1) mean size of all forest patches; (2) size of the largest forest patch; and (3) edge:area ratio of forest patches. Global analyses of the

A Variational Approach to Video Registration with Subspace Constraints.

Science.gov (United States)

Garg, Ravi; Roussos, Anastasios; Agapito, Lourdes

2013-01-01

This paper addresses the problem of non-rigid video registration, or the computation of optical flow from a reference frame to each of the subsequent images in a sequence, when the camera views deformable objects. We exploit the high correlation between 2D trajectories of different points on the same non-rigid surface by assuming that the displacement of any point throughout the sequence can be expressed in a compact way as a linear combination of a low-rank motion basis. This subspace constraint effectively acts as a trajectory regularization term leading to temporally consistent optical flow. We formulate it as a robust soft constraint within a variational framework by penalizing flow fields that lie outside the low-rank manifold. The resulting energy functional can be decoupled into the optimization of the brightness constancy and spatial regularization terms, leading to an efficient optimization scheme. Additionally, we propose a novel optimization scheme for the case of vector valued images, based on the dualization of the data term. This allows us to extend our approach to deal with colour images which results in significant improvements on the registration results. Finally, we provide a new benchmark dataset, based on motion capture data of a flag waving in the wind, with dense ground truth optical flow for evaluation of multi-frame optical flow algorithms for non-rigid surfaces. Our experiments show that our proposed approach outperforms state of the art optical flow and dense non-rigid registration algorithms.

A Reference Database for Circular Dichroism Spectroscopy Covering Fold and Secondary Structure Space

International Nuclear Information System (INIS)

Lees, J.; Miles, A.; Wien, F.; Wallace, B.

2006-01-01

Circular Dichroism (CD) spectroscopy is a long-established technique for studying protein secondary structures in solution. Empirical analyses of CD data rely on the availability of reference datasets comprised of far-UV CD spectra of proteins whose crystal structures have been determined. This article reports on the creation of a new reference dataset which effectively covers both secondary structure and fold space, and uses the higher information content available in synchrotron radiation circular dichroism (SRCD) spectra to more accurately predict secondary structure than has been possible with existing reference datasets. It also examines the effects of wavelength range, structural redundancy and different means of categorizing secondary structures on the accuracy of the analyses. In addition, it describes a novel use of hierarchical cluster analyses to identify protein relatedness based on spectral properties alone. The databases are shown to be applicable in both conventional CD and SRCD spectroscopic analyses of proteins. Hence, by combining new bioinformatics and biophysical methods, a database has been produced that should have wide applicability as a tool for structural molecular biology

The LivePhoto Physics videos and video analysis site

Science.gov (United States)

Abbott, David

2009-09-01

The LivePhoto site is similar to an archive of short films for video analysis. Some videos have Flash tools for analyzing the video embedded in the movie. Most of the videos address mechanics topics with titles like Rolling Pencil (check this one out for pedagogy and content knowledge—nicely done!), Juggler, Yo-yo, Puck and Bar (this one is an inelastic collision with rotation), but there are a few titles in other areas (E&M, waves, thermo, etc.).

Sensitivity analysis of reference evapotranspiration to sensor accuracy

Science.gov (United States)

Meteorological sensor networks are often used across agricultural regions to calculate the ASCE Standardized Reference ET Equation, and inaccuracies in individual sensors can lead to inaccuracies in ET estimates. Multiyear datasets from the semi-arid Colorado Agricultural Meteorological (CoAgMet) an...

Ranking Highlights in Personal Videos by Analyzing Edited Videos.

Science.gov (United States)

Sun, Min; Farhadi, Ali; Chen, Tseng-Hung; Seitz, Steve

2016-11-01

We present a fully automatic system for ranking domain-specific highlights in unconstrained personal videos by analyzing online edited videos. A novel latent linear ranking model is proposed to handle noisy training data harvested online. Specifically, given a targeted domain such as "surfing," our system mines the YouTube database to find pairs of raw and their corresponding edited videos. Leveraging the assumption that an edited video is more likely to contain highlights than the trimmed parts of the raw video, we obtain pair-wise ranking constraints to train our model. The learning task is challenging due to the amount of noise and variation in the mined data. Hence, a latent loss function is incorporated to mitigate the issues caused by the noise. We efficiently learn the latent model on a large number of videos (about 870 min in total) using a novel EM-like procedure. Our latent ranking model outperforms its classification counterpart and is fairly competitive compared with a fully supervised ranking system that requires labels from Amazon Mechanical Turk. We further show that a state-of-the-art audio feature mel-frequency cepstral coefficients is inferior to a state-of-the-art visual feature. By combining both audio-visual features, we obtain the best performance in dog activity, surfing, skating, and viral video domains. Finally, we show that impressive highlights can be detected without additional human supervision for seven domains (i.e., skating, surfing, skiing, gymnastics, parkour, dog activity, and viral video) in unconstrained personal videos.

Video processing for human perceptual visual quality-oriented video coding.

Science.gov (United States)

Oh, Hyungsuk; Kim, Wonha

2013-04-01

We have developed a video processing method that achieves human perceptual visual quality-oriented video coding. The patterns of moving objects are modeled by considering the limited human capacity for spatial-temporal resolution and the visual sensory memory together, and an online moving pattern classifier is devised by using the Hedge algorithm. The moving pattern classifier is embedded in the existing visual saliency with the purpose of providing a human perceptual video quality saliency model. In order to apply the developed saliency model to video coding, the conventional foveation filtering method is extended. The proposed foveation filter can smooth and enhance the video signals locally, in conformance with the developed saliency model, without causing any artifacts. The performance evaluation results confirm that the proposed video processing method shows reliable improvements in the perceptual quality for various sequences and at various bandwidths, compared to existing saliency-based video coding methods.

Integrated remotely sensed datasets for disaster management

OpenAIRE

McCarthy, Tim; Farrell, Ronan; Curtis, Andrew; Fotheringham, A. Stewart

2008-01-01

Video imagery can be acquired from aerial, terrestrial and marine based platforms and has been exploited for a range of remote sensing applications over the past two decades. Examples include coastal surveys using aerial video, routecorridor infrastructures surveys using vehicle mounted video cameras, aerial surveys over forestry and agriculture, underwater habitat mapping and disaster management. Many of these video systems are based on interlaced, television standards such as North...

Deep Spatial-Temporal Joint Feature Representation for Video Object Detection.

Science.gov (United States)

Zhao, Baojun; Zhao, Boya; Tang, Linbo; Han, Yuqi; Wang, Wenzheng

2018-03-04

With the development of deep neural networks, many object detection frameworks have shown great success in the fields of smart surveillance, self-driving cars, and facial recognition. However, the data sources are usually videos, and the object detection frameworks are mostly established on still images and only use the spatial information, which means that the feature consistency cannot be ensured because the training procedure loses temporal information. To address these problems, we propose a single, fully-convolutional neural network-based object detection framework that involves temporal information by using Siamese networks. In the training procedure, first, the prediction network combines the multiscale feature map to handle objects of various sizes. Second, we introduce a correlation loss by using the Siamese network, which provides neighboring frame features. This correlation loss represents object co-occurrences across time to aid the consistent feature generation. Since the correlation loss should use the information of the track ID and detection label, our video object detection network has been evaluated on the large-scale ImageNet VID dataset where it achieves a 69.5% mean average precision (mAP).

Physics and Video Analysis

Science.gov (United States)

Allain, Rhett

2016-05-01

We currently live in a world filled with videos. There are videos on YouTube, feature movies and even videos recorded with our own cameras and smartphones. These videos present an excellent opportunity to not only explore physical concepts, but also inspire others to investigate physics ideas. With video analysis, we can explore the fantasy world in science-fiction films. We can also look at online videos to determine if they are genuine or fake. Video analysis can be used in the introductory physics lab and it can even be used to explore the make-believe physics embedded in video games. This book covers the basic ideas behind video analysis along with the fundamental physics principles used in video analysis. The book also includes several examples of the unique situations in which video analysis can be used.

Video games

OpenAIRE

Kolář, Vojtěch

2012-01-01

This thesis is based on a detailed analysis of various topics related to the question of whether video games can be art. In the first place it analyzes the current academic discussion on this subject and confronts different opinions of both supporters and objectors of the idea, that video games can be a full-fledged art form. The second point of this paper is to analyze the properties, that are inherent to video games, in order to find the reason, why cultural elite considers video games as i...

Integration of Neuroimaging and Microarray Datasets  through Mapping and Model-Theoretic Semantic Decomposition of Unstructured Phenotypes

Directory of Open Access Journals (Sweden)

Spiro P. Pantazatos

2009-06-01

Full Text Available An approach towards heterogeneous neuroscience dataset integration is proposed that uses Natural Language Processing (NLP and a knowledge-based phenotype organizer system (PhenOS to link ontology-anchored terms to underlying data from each database, and then maps these terms based on a computable model of disease (SNOMED CT®. The approach was implemented using sample datasets from fMRIDC, GEO, The Whole Brain Atlas and Neuronames, and allowed for complex queries such as “List all disorders with a finding site of brain region X, and then find the semantically related references in all participating databases based on the ontological model of the disease or its anatomical and morphological attributes”. Precision of the NLP-derived coding of the unstructured phenotypes in each dataset was 88% (n = 50, and precision of the semantic mapping between these terms across datasets was 98% (n = 100. To our knowledge, this is the first example of the use of both semantic decomposition of disease relationships and hierarchical information found in ontologies to integrate heterogeneous phenotypes across clinical and molecular datasets.

Interobserver variability of patient positioning using four different CT datasets for image registration in lung stereotactic body radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Oechsner, Markus [Technical University of Munich, Department of Radiation Oncology, Klinikum rechts der Isar, Muenchen (Germany); Technical University of Munich, Zentrum fuer Stereotaxie und personalisierte Hochpraezisionsstrahlentherapie (StereotakTUM), Munich (Germany); Chizzali, Barbara; Devecka, Michal; Muench, Stefan [Technical University of Munich, Department of Radiation Oncology, Klinikum rechts der Isar, Muenchen (Germany); Combs, Stephanie Elisabeth; Wilkens, Jan Jakob; Duma, Marciana Nona [Technical University of Munich, Department of Radiation Oncology, Klinikum rechts der Isar, Muenchen (Germany); Technical University of Munich, Zentrum fuer Stereotaxie und personalisierte Hochpraezisionsstrahlentherapie (StereotakTUM), Munich (Germany); Helmholtz Zentrum Muenchen, Institute of Innovative Radiotherapy (iRT), Munich (Germany)

2017-10-15

To assess the impact of different reference CT datasets on manual image registration with free-breathing three-dimensional (3D) cone beam CTs (FB-CBCT) for patient positioning by several observers. For 48 patients with lung lesions, manual image registration with FB-CBCTs was performed by four observers. A slow planning CT (PCT), average intensity projection (AIP), maximum intensity projection (MIP), and midventilation CT (MidV) were used as reference images. Couch shift differences between the four reference CT datasets for each observer as well as shift differences between the observers for the same reference CT dataset were determined. Statistical analyses were performed and correlations between the registration differences and the 3D tumor motion and the CBCT score were calculated. The mean 3D shift difference between different reference CT datasets was the smallest for AIPvsMIP (range 1.1-2.2 mm) and the largest for MidVvsPCT (2.8-3.5 mm) with differences >10 mm. The 3D shifts showed partially significant correlations to 3D tumor motion and CBCT score. The interobserver comparison for the same reference CTs resulted in the smallest ∇3D mean differences and mean ∇3D standard deviation for ∇AIP (1.5 ± 0.7 mm, 0.7 ± 0.4 mm). The maximal 3D shift difference between observers was 10.4 mm (∇MidV). Both 3D tumor motion and mean CBCT score correlated with the shift differences (R{sub s} = 0.336-0.740). The applied reference CT dataset impacts image registration and causes interobserver variabilities. The 3D tumor motion and CBCT quality affect shift differences. The smallest differences were found for AIP which might be the most appropriate CT dataset for image registration with FB-CBCT. (orig.) [German] Untersuchung des Einflusses verschiedener Referenz-CT-Datensaetze auf die manuelle Bildregistrierung mit dreidimensionaler (3D) ConeBeam-Computertomographie in freier Atmung (FB-CBCT) zur Patientenpositionierung durch verschiedene Observer. Bei 48 Patienten

DETERMINING OPTIMAL CUBE FOR 3D-DCT BASED VIDEO COMPRESSION FOR DIFFERENT MOTION LEVELS

Directory of Open Access Journals (Sweden)

J. Augustin Jacob

2012-11-01

Full Text Available This paper proposes new three dimensional discrete cosine transform (3D-DCT based video compression algorithm that will select the optimal cube size based on the motion content of the video sequence. It is determined by finding normalized pixel difference (NPD values, and by categorizing the cubes as “low” or “high” motion cube suitable cube size of dimension either [16×16×8] or[8×8×8] is chosen instead of fixed cube algorithm. To evaluate the performance of the proposed algorithm test sequence with different motion levels are chosen. By doing rate vs. distortion analysis the level of compression that can be achieved and the quality of reconstructed video sequence are determined and compared against fixed cube size algorithm. Peak signal to noise ratio (PSNR is taken to measure the video quality. Experimental result shows that varying the cube size with reference to the motion content of video frames gives better performance in terms of compression ratio and video quality.

Role of Video Games in Improving Health-Related Outcomes

Science.gov (United States)

Primack, Brian A.; Carroll, Mary V.; McNamara, Megan; Klem, Mary Lou; King, Brandy; Rich, Michael O.; Chan, Chun W.; Nayak, Smita

2012-01-01

Context Video games represent a multibillion-dollar industry in the U.S. Although video gaming has been associated with many negative health consequences, it may also be useful for therapeutic purposes. The goal of this study was to determine whether video games may be useful in improving health outcomes. Evidence acquisition Literature searches were performed in February 2010 in six databases: the Center on Media and Child Health Database of Research, MEDLINE, CINAHL, PsycINFO, EMBASE, and the Cochrane Central Register of Controlled Trials. Reference lists were hand-searched to identify additional studies. Only RCTs that tested the effect of video games on a positive, clinically relevant health consequence were included. Study selection criteria were strictly defined and applied by two researchers working independently. Study background information (e.g., location, funding source), sample data (e.g., number of study participants, demographics), intervention and control details, outcomes data, and quality measures were abstracted independently by two researchers. Evidence synthesis Of 1452 articles retrieved using the current search strategy, 38 met all criteria for inclusion. Eligible studies used video games to provide physical therapy, psychological therapy, improved disease self-management, health education, distraction from discomfort, increased physical activity, and skills training for clinicians. Among the 38 studies, a total of 195 health outcomes were examined. Video games improved 69% of psychological therapy outcomes, 59% of physical therapy outcomes, 50% of physical activity outcomes, 46% of clinician skills outcomes, 42% of health education outcomes, 42% of pain distraction outcomes, and 37% of disease self-management outcomes. Study quality was generally poor; for example, two thirds (66%) of studies had follow-up periods of video games to improve health outcomes, particularly in the areas of psychological therapy and physical therapy. RCTs with

Mridangam stroke dataset

OpenAIRE

CompMusic

2014-01-01

The audio examples were recorded from a professional Carnatic percussionist in a semi-anechoic studio conditions by Akshay Anantapadmanabhan using SM-58 microphones and an H4n ZOOM recorder. The audio was sampled at 44.1 kHz and stored as 16 bit wav files. The dataset can be used for training models for each Mridangam stroke. /n/nA detailed description of the Mridangam and its strokes can be found in the paper below. A part of the dataset was used in the following paper. /nAkshay Anantapadman...

Rare Disease Video Portal

OpenAIRE

Sánchez Bocanegra, Carlos Luis

2011-01-01

Rare Disease Video Portal (RD Video) is a portal web where contains videos from Youtube including all details from 12 channels of Youtube. Rare Disease Video Portal (RD Video) es un portal web que contiene los vídeos de Youtube incluyendo todos los detalles de 12 canales de Youtube. Rare Disease Video Portal (RD Video) és un portal web que conté els vídeos de Youtube i que inclou tots els detalls de 12 Canals de Youtube.

Medical students' perceptions of video-linked lectures and video-streaming

Directory of Open Access Journals (Sweden)

Karen Mattick

2010-12-01

Full Text Available Video-linked lectures allow healthcare students across multiple sites, and between university and hospital bases, to come together for the purposes of shared teaching. Recording and streaming video-linked lectures allows students to view them at a later date and provides an additional resource to support student learning. As part of a UK Higher Education Academy-funded Pathfinder project, this study explored medical students' perceptions of video-linked lectures and video-streaming, and their impact on learning. The methodology involved semi-structured interviews with 20 undergraduate medical students across four sites and five year groups. Several key themes emerged from the analysis. Students generally preferred live lectures at the home site and saw interaction between sites as a major challenge. Students reported that their attendance at live lectures was not affected by the availability of streamed lectures and tended to be influenced more by the topic and speaker than the technical arrangements. These findings will inform other educators interested in employing similar video technologies in their teaching.Keywords: video-linked lecture; video-streaming; student perceptions; decisionmaking; cross-campus teaching.

Automated Indexing and Search of Video Data in Large Collections with inVideo

Directory of Open Access Journals (Sweden)

Shuangbao Paul Wang

2017-08-01

Full Text Available In this paper, we present a novel system, inVideo, for automatically indexing and searching videos based on the keywords spoken in the audio track and the visual content of the video frames. Using the highly efficient video indexing engine we developed, inVideo is able to analyze videos using machine learning and pattern recognition without the need for initial viewing by a human. The time-stamped commenting and tagging features refine the accuracy of search results. The cloud-based implementation makes it possible to conduct elastic search, augmented search, and data analytics. Our research shows that inVideo presents an efficient tool in processing and analyzing videos and increasing interactions in video-based online learning environment. Data from a cybersecurity program with more than 500 students show that applying inVideo to current video material, interactions between student-student and student-faculty increased significantly across 24 sections program-wide.

2008 TIGER/Line Nationwide Dataset

Data.gov (United States)

California Natural Resource Agency — This dataset contains a nationwide build of the 2008 TIGER/Line datasets from the US Census Bureau downloaded in April 2009. The TIGER/Line Shapefiles are an extract...

NEI You Tube Videos: Amblyopia

Medline Plus

Full Text Available ... YouTube Videos » NEI YouTube Videos: Amblyopia Listen NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration ... Retinopathy of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded video for NEI YouTube Videos: ...

Guerrilla Video: A New Protocol for Producing Classroom Video

Science.gov (United States)

Fadde, Peter; Rich, Peter

2010-01-01

Contemporary changes in pedagogy point to the need for a higher level of video production value in most classroom video, replacing the default video protocol of an unattended camera in the back of the classroom. The rich and complex environment of today's classroom can be captured more fully using the higher level, but still easily manageable,…

Design of an audio advertisement dataset

Science.gov (United States)

Fu, Yutao; Liu, Jihong; Zhang, Qi; Geng, Yuting

2015-12-01

Since more and more advertisements swarm into radios, it is necessary to establish an audio advertising dataset which could be used to analyze and classify the advertisement. A method of how to establish a complete audio advertising dataset is presented in this paper. The dataset is divided into four different kinds of advertisements. Each advertisement's sample is given in *.wav file format, and annotated with a txt file which contains its file name, sampling frequency, channel number, broadcasting time and its class. The classifying rationality of the advertisements in this dataset is proved by clustering the different advertisements based on Principal Component Analysis (PCA). The experimental results show that this audio advertisement dataset offers a reliable set of samples for correlative audio advertisement experimental studies.

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.

Topical video object discovery from key frames by modeling word co-occurrence prior.

Science.gov (United States)

Zhao, Gangqiang; Yuan, Junsong; Hua, Gang; Yang, Jiong

2015-12-01

A topical video object refers to an object, that is, frequently highlighted in a video. It could be, e.g., the product logo and the leading actor/actress in a TV commercial. We propose a topic model that incorporates a word co-occurrence prior for efficient discovery of topical video objects from a set of key frames. Previous work using topic models, such as latent Dirichelet allocation (LDA), for video object discovery often takes a bag-of-visual-words representation, which ignored important co-occurrence information among the local features. We show that such data driven co-occurrence information from bottom-up can conveniently be incorporated in LDA with a Gaussian Markov prior, which combines top-down probabilistic topic modeling with bottom-up priors in a unified model. Our experiments on challenging videos demonstrate that the proposed approach can discover different types of topical objects despite variations in scale, view-point, color and lighting changes, or even partial occlusions. The efficacy of the co-occurrence prior is clearly demonstrated when compared with topic models without such priors.

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.

Presence in Video-Mediated Interactions: Case Studies at CSIRO

Science.gov (United States)

Alem, Leila

Although telepresence and a sense of connectedness with others are frequently mentioned in media space studies, as far as we know, none of these studies report attempts at assessing this critical aspect of user experience. While some attempts have been made to measure presence in virtual reality or augmented reality, (a comprehensive review of existing measures is available in Baren and Ijsselsteijn [2004]), very little work has been reported in measuring presence in video-mediated collaboration systems. Traditional studies of video-mediated collaboration have mostly focused their evaluation on measures of task performance and user satisfaction. Videoconferencing systems can be seen as a type of media space; they rely on technologies of audio, video, and computing put together to create an environment extending the embodied mind. This chapter reports on a set of video-mediated collaboration studies conducted at CSIRO in which different aspects of presence are being investigated. The first study reports the sense of physical presence a specialist doctor experiences when engaged in a remote consultation of a patient using the virtual critical care unit (Alem et al., 2006). The Viccu system is an “always-on” system connecting two hospitals (Li et al., 2006). The presence measure focuses on the extent to which users of videoconferencing systems feel physically present in the remote location. The second study reports the sense of social presence users experience when playing a game of charades with remote partners using a video conference link (Kougianous et al., 2006). In this study the presence measure focuses on the extent to which users feel connected with their remote partners. The third study reports the sense of copresence users experience when building collaboratively a piece of Lego toy (Melo and Alem, 2007). The sense of copresence is the extent to which users feel present with their remote partner. In this final study the sense of copresence is

Game over: Asian Americans and video game representation [symposium

Directory of Open Access Journals (Sweden)

Thien-bao Thuc Phi

2009-03-01

Full Text Available Even video games by Asian creators tend to depict primarily white characters or reference Asian stereotypes such as kung fu fighters or yakuza thugs. Games depicting the Vietnam war are particularly troubling for Asian players expected to identify with white characters. As the game industry continues to expand, its representation of Asians and Asian Americans must change.

A Dataset and Benchmarks for Segmentation and Recognition of Gestures in Robotic Surgery.

Science.gov (United States)

Ahmidi, Narges; Tao, Lingling; Sefati, Shahin; Gao, Yixin; Lea, Colin; Haro, Benjamin Bejar; Zappella, Luca; Khudanpur, Sanjeev; Vidal, Rene; Hager, Gregory D

2017-09-01

State-of-the-art techniques for surgical data analysis report promising results for automated skill assessment and action recognition. The contributions of many of these techniques, however, are limited to study-specific data and validation metrics, making assessment of progress across the field extremely challenging. In this paper, we address two major problems for surgical data analysis: First, lack of uniform-shared datasets and benchmarks, and second, lack of consistent validation processes. We address the former by presenting the JHU-ISI Gesture and Skill Assessment Working Set (JIGSAWS), a public dataset that we have created to support comparative research benchmarking. JIGSAWS contains synchronized video and kinematic data from multiple performances of robotic surgical tasks by operators of varying skill. We address the latter by presenting a well-documented evaluation methodology and reporting results for six techniques for automated segmentation and classification of time-series data on JIGSAWS. These techniques comprise four temporal approaches for joint segmentation and classification: hidden Markov model, sparse hidden Markov model (HMM), Markov semi-Markov conditional random field, and skip-chain conditional random field; and two feature-based ones that aim to classify fixed segments: bag of spatiotemporal features and linear dynamical systems. Most methods recognize gesture activities with approximately 80% overall accuracy under both leave-one-super-trial-out and leave-one-user-out cross-validation settings. Current methods show promising results on this shared dataset, but room for significant progress remains, particularly for consistent prediction of gesture activities across different surgeons. The results reported in this paper provide the first systematic and uniform evaluation of surgical activity recognition techniques on the benchmark database.

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.

The GTZAN dataset

DEFF Research Database (Denmark)

Sturm, Bob L.

2013-01-01

The GTZAN dataset appears in at least 100 published works, and is the most-used public dataset for evaluation in machine listening research for music genre recognition (MGR). Our recent work, however, shows GTZAN has several faults (repetitions, mislabelings, and distortions), which challenge...... of GTZAN, and provide a catalog of its faults. We review how GTZAN has been used in MGR research, and find few indications that its faults have been known and considered. Finally, we rigorously study the effects of its faults on evaluating five different MGR systems. The lesson is not to banish GTZAN...

Video Design Games

DEFF Research Database (Denmark)

Smith, Rachel Charlotte; Christensen, Kasper Skov; Iversen, Ole Sejer

We introduce Video Design Games to train educators in teaching design. The Video Design Game is a workshop format consisting of three rounds in which participants observe, reflect and generalize based on video snippets from their own practice. The paper reports on a Video Design Game workshop...... in which 25 educators as part of a digital fabrication and design program were able to critically reflect on their teaching practice....

Flip Video for Dummies

CERN Document Server

Hutsko, Joe

2010-01-01

The full-color guide to shooting great video with the Flip Video camera. The inexpensive Flip Video camera is currently one of the hottest must-have gadgets. It's portable and connects easily to any computer to transfer video you shoot onto your PC or Mac. Although the Flip Video camera comes with a quick-start guide, it lacks a how-to manual, and this full-color book fills that void! Packed with full-color screen shots throughout, Flip Video For Dummies shows you how to shoot the best possible footage in a variety of situations. You'll learn how to transfer video to your computer and then edi

Combining Video, Audio and Lexical Indicators of Affect in Spontaneous Conversation via Particle Filtering.

Science.gov (United States)

Savran, Arman; Cao, Houwei; Shah, Miraj; Nenkova, Ani; Verma, Ragini

2012-01-01

We present experiments on fusing facial video, audio and lexical indicators for affect estimation during dyadic conversations. We use temporal statistics of texture descriptors extracted from facial video, a combination of various acoustic features, and lexical features to create regression based affect estimators for each modality. The single modality regressors are then combined using particle filtering, by treating these independent regression outputs as measurements of the affect states in a Bayesian filtering framework, where previous observations provide prediction about the current state by means of learned affect dynamics. Tested on the Audio-visual Emotion Recognition Challenge dataset, our single modality estimators achieve substantially higher scores than the official baseline method for every dimension of affect. Our filtering-based multi-modality fusion achieves correlation performance of 0.344 (baseline: 0.136) and 0.280 (baseline: 0.096) for the fully continuous and word level sub challenges, respectively.

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.

A Fisher Kernel Approach for Multiple Instance Based Object Retrieval in Video Surveillance

Directory of Open Access Journals (Sweden)

MIRONICA, I.

2015-11-01

Full Text Available This paper presents an automated surveillance system that exploits the Fisher Kernel representation in the context of multiple-instance object retrieval task. The proposed algorithm has the main purpose of tracking a list of persons in several video sources, using only few training examples. In the first step, the Fisher Kernel representation describes a set of features as the derivative with respect to the log-likelihood of the generative probability distribution that models the feature distribution. Then, we learn the generative probability distribution over all features extracted from a reduced set of relevant frames. The proposed approach shows significant improvements and we demonstrate that Fisher kernels are well suited for this task. We demonstrate the generality of our approach in terms of features by conducting an extensive evaluation with a broad range of keypoints features. Also, we evaluate our method on two standard video surveillance datasets attaining superior results comparing to state-of-the-art object recognition algorithms.

Parallel Framework for Dimensionality Reduction of Large-Scale Datasets

Directory of Open Access Journals (Sweden)

Sai Kiranmayee Samudrala

2015-01-01

Full Text Available Dimensionality reduction refers to a set of mathematical techniques used to reduce complexity of the original high-dimensional data, while preserving its selected properties. Improvements in simulation strategies and experimental data collection methods are resulting in a deluge of heterogeneous and high-dimensional data, which often makes dimensionality reduction the only viable way to gain qualitative and quantitative understanding of the data. However, existing dimensionality reduction software often does not scale to datasets arising in real-life applications, which may consist of thousands of points with millions of dimensions. In this paper, we propose a parallel framework for dimensionality reduction of large-scale data. We identify key components underlying the spectral dimensionality reduction techniques, and propose their efficient parallel implementation. We show that the resulting framework can be used to process datasets consisting of millions of points when executed on a 16,000-core cluster, which is beyond the reach of currently available methods. To further demonstrate applicability of our framework we perform dimensionality reduction of 75,000 images representing morphology evolution during manufacturing of organic solar cells in order to identify how processing parameters affect morphology evolution.

Designing Effective Video-Based Modeling Examples Using Gaze and Gesture Cues

NARCIS (Netherlands)

Ouwehand, Kim; van Gog, Tamara|info:eu-repo/dai/nl/294304975; Paas, Fred

2015-01-01

Research suggests that learners will likely spend a substantial amount of time looking at the model's face when it is visible in a video-based modeling example. Consequently, in this study we hypothesized that learners might not attend timely to the task areas the model is referring to, unless their

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.

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.

Automatic Emotional State Detection using Facial Expression Dynamic in Videos

Directory of Open Access Journals (Sweden)

Hongying Meng

2014-11-01

Full Text Available In this paper, an automatic emotion detection system is built for a computer or machine to detect the emotional state from facial expressions in human computer communication. Firstly, dynamic motion features are extracted from facial expression videos and then advanced machine learning methods for classification and regression are used to predict the emotional states. The system is evaluated on two publicly available datasets, i.e. GEMEP_FERA and AVEC2013, and satisfied performances are achieved in comparison with the baseline results provided. With this emotional state detection capability, a machine can read the facial expression of its user automatically. This technique can be integrated into applications such as smart robots, interactive games and smart surveillance systems.

77 FR 48102 - Closed Captioning and Video Description of Video Programming

Science.gov (United States)

2012-08-13

... Captioning and Video Description of Video Programming AGENCY: Federal Communications Commission. [[Page 48103... show that providing captions on their programming would be economically burdensome. DATES: Effective...) establishing requirements for closed captioning on video programming to ensure access by persons with hearing...

Low-complexity JPEG-based progressive video codec for wireless video transmission

DEFF Research Database (Denmark)

Ukhanova, Ann; Forchhammer, Søren

2010-01-01

This paper discusses the question of video codec enhancement for wireless video transmission of high definition video data taking into account constraints on memory and complexity. Starting from parameter adjustment for JPEG2000 compression algorithm used for wireless transmission and achieving...

Deep Spatial-Temporal Joint Feature Representation for Video Object Detection

Directory of Open Access Journals (Sweden)

Baojun Zhao

2018-03-01

Full Text Available With the development of deep neural networks, many object detection frameworks have shown great success in the fields of smart surveillance, self-driving cars, and facial recognition. However, the data sources are usually videos, and the object detection frameworks are mostly established on still images and only use the spatial information, which means that the feature consistency cannot be ensured because the training procedure loses temporal information. To address these problems, we propose a single, fully-convolutional neural network-based object detection framework that involves temporal information by using Siamese networks. In the training procedure, first, the prediction network combines the multiscale feature map to handle objects of various sizes. Second, we introduce a correlation loss by using the Siamese network, which provides neighboring frame features. This correlation loss represents object co-occurrences across time to aid the consistent feature generation. Since the correlation loss should use the information of the track ID and detection label, our video object detection network has been evaluated on the large-scale ImageNet VID dataset where it achieves a 69.5% mean average precision (mAP.

Video quality measure for mobile IPTV service

Science.gov (United States)

Kim, Wonjun; Kim, Changick

2008-08-01

Mobile IPTV is a multimedia service based on wireless networks with interactivity and mobility. Under mobile IPTV scenarios, people can watch various contents whenever they want and even deliver their request to service providers through the network. However, the frequent change of the wireless channel bandwidth may hinder the quality of service. In this paper, we propose an objective video quality measure (VQM) for mobile IPTV services, which is focused on the jitter measurement. Jitter is the result of frame repetition during the delay and one of the most severe impairments in the video transmission via mobile channels. We first employ YUV color space to compute the duration and occurrences of jitter and the motion activity. Then the VQM is modeled by the combination of these three factors and the result of subjective assessment. Since the proposed VQM is based on no-reference (NR) model, it can be applied for real-time applications. Experimental results show that the proposed VQM highly correlates to subjective evaluation.

Effective Educational Videos: Principles and Guidelines for Maximizing Student Learning from Video Content

Science.gov (United States)

Brame, Cynthia J.

2016-01-01

Educational videos have become an important part of higher education, providing an important content-delivery tool in many flipped, blended, and online classes. Effective use of video as an educational tool is enhanced when instructors consider three elements: how to manage cognitive load of the video; how to maximize student engagement with the video; and how to promote active learning from the video. This essay reviews literature relevant to each of these principles and suggests practical ways instructors can use these principles when using video as an educational tool. PMID:27789532

The centroidal algorithm in molecular similarity and diversity calculations on confidential datasets

Science.gov (United States)

Trepalin, Sergey; Osadchiy, Nikolay

2005-09-01

Chemical structure provides exhaustive description of a compound, but it is often proprietary and thus an impediment in the exchange of information. For example, structure disclosure is often needed for the selection of most similar or dissimilar compounds. Authors propose a centroidal algorithm based on structural fragments (screens) that can be efficiently used for the similarity and diversity selections without disclosing structures from the reference set. For an increased security purposes, authors recommend that such set contains at least some tens of structures. Analysis of reverse engineering feasibility showed that the problem difficulty grows with decrease of the screen's radius. The algorithm is illustrated with concrete calculations on known steroidal, quinoline, and quinazoline drugs. We also investigate a problem of scaffold identification in combinatorial library dataset. The results show that relatively small screens of radius equal to 2 bond lengths perform well in the similarity sorting, while radius 4 screens yield better results in diversity sorting. The software implementation of the algorithm taking SDF file with a reference set generates screens of various radii which are subsequently used for the similarity and diversity sorting of external SDFs. Since the reverse engineering of the reference set molecules from their screens has the same difficulty as the RSA asymmetric encryption algorithm, generated screens can be stored openly without further encryption. This approach ensures an end user transfers only a set of structural fragments and no other data. Like other algorithms of encryption, the centroid algorithm cannot give 100% guarantee of protecting a chemical structure from dataset, but probability of initial structure identification is very small-order of 10-40 in typical cases.

Towards Robust Face Recognition from Video

International Nuclear Information System (INIS)

Price, JR

2001-01-01

A novel, template-based method for face recognition is presented. The goals of the proposed method are to integrate multiple observations for improved robustness and to provide auxiliary confidence data for subsequent use in an automated video surveillance system. The proposed framework consists of a parallel system of classifiers, referred to as observers, where each observer is trained on one face region. The observer outputs are combined to yield the final recognition result. Three of the four confounding factors-expression, illumination, and decoration-are specifically addressed in this paper. The extension of the proposed approach to address the fourth confounding factor-pose-is straightforward and well supported in previous work. A further contribution of the proposed approach is the computation of a revealing confidence measure. This confidence measure will aid the subsequent application of the proposed method to video surveillance scenarios. Results are reported for a database comprising 676 images of 160 subjects under a variety of challenging circumstances. These results indicate significant performance improvements over previous methods and demonstrate the usefulness of the confidence data

Editorial: Datasets for Learning Analytics

NARCIS (Netherlands)

Dietze, Stefan; George, Siemens; Davide, Taibi; Drachsler, Hendrik

2018-01-01

The European LinkedUp and LACE (Learning Analytics Community Exchange) project have been responsible for setting up a series of data challenges at the LAK conferences 2013 and 2014 around the LAK dataset. The LAK datasets consists of a rich collection of full text publications in the domain of

Performance Analysis of Video Transmission Using Sequential Distortion Minimization Method for Digital Video Broadcasting Terrestrial

Directory of Open Access Journals (Sweden)

Novita Astin

2016-12-01

Full Text Available This paper presents about the transmission of Digital Video Broadcasting system with streaming video resolution 640x480 on different IQ rate and modulation. In the video transmission, distortion often occurs, so the received video has bad quality. Key frames selection algorithm is flexibel on a change of video, but on these methods, the temporal information of a video sequence is omitted. To minimize distortion between the original video and received video, we aimed at adding methodology using sequential distortion minimization algorithm. Its aim was to create a new video, better than original video without significant loss of content between the original video and received video, fixed sequentially. The reliability of video transmission was observed based on a constellation diagram, with the best result on IQ rate 2 Mhz and modulation 8 QAM. The best video transmission was also investigated using SEDIM (Sequential Distortion Minimization Method and without SEDIM. The experimental result showed that the PSNR (Peak Signal to Noise Ratio average of video transmission using SEDIM was an increase from 19,855 dB to 48,386 dB and SSIM (Structural Similarity average increase 10,49%. The experimental results and comparison of proposed method obtained a good performance. USRP board was used as RF front-end on 2,2 GHz.

The Geometry of Finite Equilibrium Datasets

DEFF Research Database (Denmark)

Balasko, Yves; Tvede, Mich

We investigate the geometry of finite datasets defined by equilibrium prices, income distributions, and total resources. We show that the equilibrium condition imposes no restrictions if total resources are collinear, a property that is robust to small perturbations. We also show that the set...... of equilibrium datasets is pathconnected when the equilibrium condition does impose restrictions on datasets, as for example when total resources are widely non collinear....

High Definition Video Streaming Using H.264 Video Compression

OpenAIRE

Bechqito, Yassine

2009-01-01

This thesis presents high definition video streaming using H.264 codec implementation. The experiment carried out in this study was done for an offline streaming video but a model for live high definition streaming is introduced, as well. Prior to the actual experiment, this study describes digital media streaming. Also, the different technologies involved in video streaming are covered. These include streaming architecture and a brief overview on H.264 codec as well as high definition t...

SHIP CLASSIFICATION FROM MULTISPECTRAL VIDEOS

Directory of Open Access Journals (Sweden)

Frederique Robert-Inacio

2012-05-01

Full Text Available Surveillance of a seaport can be achieved by different means: radar, sonar, cameras, radio communications and so on. Such a surveillance aims, on the one hand, to manage cargo and tanker traffic, and, on the other hand, to prevent terrorist attacks in sensitive areas. In this paper an application to video-surveillance of a seaport entrance is presented, and more particularly, the different steps enabling to classify mobile shapes. This classification is based on a parameter measuring the similarity degree between the shape under study and a set of reference shapes. The classification result describes the considered mobile in terms of shape and speed.

Online video examination

DEFF Research Database (Denmark)

Qvist, Palle

have large influence on their own teaching, learning and curriculum. The programme offers streamed videos in combination with other learning resources. It is a concept which offers video as pure presentation - video lectures - but also as an instructional tool which gives the students the possibility...... to construct their knowledge, collaboration and communication. In its first years the programme has used Skype video communication for collaboration and communication within and between groups, group members and their facilitators. Also exams have been mediated with the help of Skype and have for all students......, examiners and external examiners been a challenge and opportunity and has brought new knowledge and experience. This paper brings results from a questionnaire focusing on how the students experience the video examination....

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.

High-Performance Motion Estimation for Image Sensors with Video Compression

Directory of Open Access Journals (Sweden)

Weizhi Xu

2015-08-01

Full Text Available It is important to reduce the time cost of video compression for image sensors in video sensor network. Motion estimation (ME is the most time-consuming part in video compression. Previous work on ME exploited intra-frame data reuse in a reference frame to improve the time efficiency but neglected inter-frame data reuse. We propose a novel inter-frame data reuse scheme which can exploit both intra-frame and inter-frame data reuse for ME in video compression (VC-ME. Pixels of reconstructed frames are kept on-chip until they are used by the next current frame to avoid off-chip memory access. On-chip buffers with smart schedules of data access are designed to perform the new data reuse scheme. Three levels of the proposed inter-frame data reuse scheme are presented and analyzed. They give different choices with tradeoff between off-chip bandwidth requirement and on-chip memory size. All three levels have better data reuse efficiency than their intra-frame counterparts, so off-chip memory traffic is reduced effectively. Comparing the new inter-frame data reuse scheme with the traditional intra-frame data reuse scheme, the memory traffic can be reduced by 50% for VC-ME.

Industrial-Strength Streaming Video.

Science.gov (United States)

Avgerakis, George; Waring, Becky

1997-01-01

Corporate training, financial services, entertainment, and education are among the top applications for streaming video servers, which send video to the desktop without downloading the whole file to the hard disk, saving time and eliminating copyrights questions. Examines streaming video technology, lists ten tips for better net video, and ranks…

Practical image and video processing using MATLAB

CERN Document Server

Marques, Oge

2011-01-01

"The book provides a practical introduction to the most important topics in image and video processing using MATLAB (and its Image Processing Toolbox) as a tool to demonstrate the most important techniques and algorithms. The contents are presented in a clear, technically accurate, objective way, with just enough mathematical detail. Most of the chapters are supported by figures, examples, illustrative problems, MATLAB scripts, suggestions for further reading, bibliographical references, useful Web sites, and exercises and computer projects to extend the understanding of their contents"--

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.

A Novel Quantum Video Steganography Protocol with Large Payload Based on MCQI Quantum Video

Science.gov (United States)

Qu, Zhiguo; Chen, Siyi; Ji, Sai

2017-11-01

As one of important multimedia forms in quantum network, quantum video attracts more and more attention of experts and scholars in the world. A secure quantum video steganography protocol with large payload based on the video strip encoding method called as MCQI (Multi-Channel Quantum Images) is proposed in this paper. The new protocol randomly embeds the secret information with the form of quantum video into quantum carrier video on the basis of unique features of video frames. It exploits to embed quantum video as secret information for covert communication. As a result, its capacity are greatly expanded compared with the previous quantum steganography achievements. Meanwhile, the new protocol also achieves good security and imperceptibility by virtue of the randomization of embedding positions and efficient use of redundant frames. Furthermore, the receiver enables to extract secret information from stego video without retaining the original carrier video, and restore the original quantum video as a follow. The simulation and experiment results prove that the algorithm not only has good imperceptibility, high security, but also has large payload.

Social Properties of Mobile Video

Science.gov (United States)

Mitchell, April Slayden; O'Hara, Kenton; Vorbau, Alex

Mobile video is now an everyday possibility with a wide array of commercially available devices, services, and content. These new technologies have created dramatic shifts in the way video-based media can be produced, consumed, and delivered by people beyond the familiar behaviors associated with fixed TV and video technologies. Such technology revolutions change the way users behave and change their expectations in regards to their mobile video experiences. Building upon earlier studies of mobile video, this paper reports on a study using diary techniques and ethnographic interviews to better understand how people are using commercially available mobile video technologies in their everyday lives. Drawing on reported episodes of mobile video behavior, the study identifies the social motivations and values underpinning these behaviors that help characterize mobile video consumption beyond the simplistic notion of viewing video only to kill time. This paper also discusses the significance of user-generated content and the usage of video in social communities through the description of two mobile video technology services that allow users to create and share content. Implications for adoption and design of mobile video technologies and services are discussed as well.

A comprehensive dataset of genes with a loss-of-function mutant phenotype in Arabidopsis.

Science.gov (United States)

Lloyd, Johnny; Meinke, David

2012-03-01

Despite the widespread use of Arabidopsis (Arabidopsis thaliana) as a model plant, a curated dataset of Arabidopsis genes with mutant phenotypes remains to be established. A preliminary list published nine years ago in Plant Physiology is outdated, and genome-wide phenotype information remains difficult to obtain. We describe here a comprehensive dataset of 2,400 genes with a loss-of-function mutant phenotype in Arabidopsis. Phenotype descriptions were gathered primarily from manual curation of the scientific literature. Genes were placed into prioritized groups (essential, morphological, cellular-biochemical, and conditional) based on the documented phenotypes of putative knockout alleles. Phenotype classes (e.g. vegetative, reproductive, and timing, for the morphological group) and subsets (e.g. flowering time, senescence, circadian rhythms, and miscellaneous, for the timing class) were also established. Gene identities were classified as confirmed (through molecular complementation or multiple alleles) or not confirmed. Relationships between mutant phenotype and protein function, genetic redundancy, protein connectivity, and subcellular protein localization were explored. A complementary dataset of 401 genes that exhibit a mutant phenotype only when disrupted in combination with a putative paralog was also compiled. The importance of these genes in confirming functional redundancy and enhancing the value of single gene datasets is discussed. With further input and curation from the Arabidopsis community, these datasets should help to address a variety of important biological questions, provide a foundation for exploring the relationship between genotype and phenotype in angiosperms, enhance the utility of Arabidopsis as a reference plant, and facilitate comparative studies with model genetic organisms.

Video Podcasts

DEFF Research Database (Denmark)

Nortvig, Anne Mette; Sørensen, Birgitte Holm

2016-01-01

This project’s aim was to support and facilitate master’s students’ preparation and collaboration by making video podcasts of short lectures available on YouTube prior to students’ first face-to-face seminar. The empirical material stems from group interviews, from statistical data created through...... YouTube analytics and from surveys answered by students after the seminar. The project sought to explore how video podcasts support learning and reflection online and how students use and reflect on the integration of online activities in the videos. Findings showed that students engaged actively...

Video games.

Science.gov (United States)

Funk, Jeanne B

2005-06-01

The video game industry insists that it is doing everything possible to provide information about the content of games so that parents can make informed choices; however, surveys indicate that ratings may not reflect consumer views of the nature of the content. This article describes some of the currently popular video games, as well as developments that are on the horizon, and discusses the status of research on the positive and negative impacts of playing video games. Recommendations are made to help parents ensure that children play games that are consistent with their values.

Crowd-Sourced Amputee Gait Data: A Feasibility Study Using YouTube Videos of Unilateral Trans-Femoral Gait.

Directory of Open Access Journals (Sweden)

James Gardiner

Full Text Available Collecting large datasets of amputee gait data is notoriously difficult. Additionally, collecting data on less prevalent amputations or on gait activities other than level walking and running on hard surfaces is rarely attempted. However, with the wealth of user-generated content on the Internet, the scope for collecting amputee gait data from alternative sources other than traditional gait labs is intriguing. Here we investigate the potential of YouTube videos to provide gait data on amputee walking. We use an example dataset of trans-femoral amputees level walking at self-selected speeds to collect temporal gait parameters and calculate gait asymmetry. We compare our YouTube data with typical literature values, and show that our methodology produces results that are highly comparable to data collected in a traditional manner. The similarity between the results of our novel methodology and literature values lends confidence to our technique. Nevertheless, clear challenges with the collection and interpretation of crowd-sourced gait data remain, including long term access to datasets, and a lack of validity and reliability studies in this area.

Crowd-Sourced Amputee Gait Data: A Feasibility Study Using YouTube Videos of Unilateral Trans-Femoral Gait.

Science.gov (United States)

Gardiner, James; Gunarathne, Nuwan; Howard, David; Kenney, Laurence

2016-01-01

Collecting large datasets of amputee gait data is notoriously difficult. Additionally, collecting data on less prevalent amputations or on gait activities other than level walking and running on hard surfaces is rarely attempted. However, with the wealth of user-generated content on the Internet, the scope for collecting amputee gait data from alternative sources other than traditional gait labs is intriguing. Here we investigate the potential of YouTube videos to provide gait data on amputee walking. We use an example dataset of trans-femoral amputees level walking at self-selected speeds to collect temporal gait parameters and calculate gait asymmetry. We compare our YouTube data with typical literature values, and show that our methodology produces results that are highly comparable to data collected in a traditional manner. The similarity between the results of our novel methodology and literature values lends confidence to our technique. Nevertheless, clear challenges with the collection and interpretation of crowd-sourced gait data remain, including long term access to datasets, and a lack of validity and reliability studies in this area.

Improving Classroom Learning by Collaboratively Observing Human Tutoring Videos while Problem Solving

Science.gov (United States)

Craig, Scotty D.; Chi, Michelene T. H.; VanLehn, Kurt

2009-01-01

Collaboratively observing tutoring is a promising method for observational learning (also referred to as vicarious learning). This method was tested in the Pittsburgh Science of Learning Center's Physics LearnLab, where students were introduced to physics topics by observing videos while problem solving in Andes, a physics tutoring system.…

No Reference Prediction of Quality Metrics for H.264 Compressed Infrared Image Sequences for UAV Applications

DEFF Research Database (Denmark)

Hossain, Kabir; Mantel, Claire; Forchhammer, Søren

2018-01-01

The framework for this research work is the acquisition of Infrared (IR) images from Unmanned Aerial Vehicles (UAV). In this paper we consider the No-Reference (NR) prediction of Full Reference Quality Metrics for Infrared (IR) video sequences which are compressed and thus distorted by an H.264...

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.

Statistical Analysis of Video Frame Size Distribution Originating from Scalable Video Codec (SVC

Directory of Open Access Journals (Sweden)

Sima Ahmadpour

2017-01-01

Full Text Available Designing an effective and high performance network requires an accurate characterization and modeling of network traffic. The modeling of video frame sizes is normally applied in simulation studies and mathematical analysis and generating streams for testing and compliance purposes. Besides, video traffic assumed as a major source of multimedia traffic in future heterogeneous network. Therefore, the statistical distribution of video data can be used as the inputs for performance modeling of networks. The finding of this paper comprises the theoretical definition of distribution which seems to be relevant to the video trace in terms of its statistical properties and finds the best distribution using both the graphical method and the hypothesis test. The data set used in this article consists of layered video traces generating from Scalable Video Codec (SVC video compression technique of three different movies.

An Annotated Dataset of 14 Meat Images

DEFF Research Database (Denmark)

Stegmann, Mikkel Bille

2002-01-01

This note describes a dataset consisting of 14 annotated images of meat. Points of correspondence are placed on each image. As such, the dataset can be readily used for building statistical models of shape. Further, format specifications and terms of use are given.......This note describes a dataset consisting of 14 annotated images of meat. Points of correspondence are placed on each image. As such, the dataset can be readily used for building statistical models of shape. Further, format specifications and terms of use are given....

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...

Violent Video Games and the Supreme Court: Lessons for the Scientific Community in the Wake of Brown v. Entertainment Merchants Association

Science.gov (United States)

Ferguson, Christopher J.

2013-01-01

In June 2011 the U.S. Supreme Court ruled that video games enjoy full free speech protections and that the regulation of violent game sales to minors is unconstitutional. The Supreme Court also referred to psychological research on violent video games as "unpersuasive" and noted that such research contains many methodological flaws.…

Development of P4140 video data wall projector; Video data wall projector

Energy Technology Data Exchange (ETDEWEB)

Watanabe, H.; Inoue, H. [Toshiba Corp., Tokyo (Japan)

1998-12-01

The P4140 is a 3 cathode-ray tube (CRT) video data wall projector for super video graphics array (SVGA) signals. It is used as an image display unit, providing a large screen when several sets are put together. A high-quality picture has been realized by higher resolution and improved color uniformity technology. A new convergence adjustment system has also been developed through the optimal combination of digital and analog technologies. This video data wall installation has been greatly enhanced by the automation of cubes and cube performance settings. The P4140 video data wall projector can be used for displaying not only data but video as well. (author)

Intelligent video surveillance systems

CERN Document Server

Dufour, Jean-Yves

2012-01-01

Belonging to the wider academic field of computer vision, video analytics has aroused a phenomenal surge of interest since the current millennium. Video analytics is intended to solve the problem of the incapability of exploiting video streams in real time for the purpose of detection or anticipation. It involves analyzing the videos using algorithms that detect and track objects of interest over time and that indicate the presence of events or suspect behavior involving these objects.The aims of this book are to highlight the operational attempts of video analytics, to identify possi

Video Vectorization via Tetrahedral Remeshing.

Science.gov (United States)

Wang, Chuan; Zhu, Jie; Guo, Yanwen; Wang, Wenping

2017-02-09

We present a video vectorization method that generates a video in vector representation from an input video in raster representation. A vector-based video representation offers the benefits of vector graphics, such as compactness and scalability. The vector video we generate is represented by a simplified tetrahedral control mesh over the spatial-temporal video volume, with color attributes defined at the mesh vertices. We present novel techniques for simplification and subdivision of a tetrahedral mesh to achieve high simplification ratio while preserving features and ensuring color fidelity. From an input raster video, our method is capable of generating a compact video in vector representation that allows a faithful reconstruction with low reconstruction errors.

Comparison of recent SnIa datasets

International Nuclear Information System (INIS)

Sanchez, J.C. Bueno; Perivolaropoulos, L.; Nesseris, S.

2009-01-01

We rank the six latest Type Ia supernova (SnIa) datasets (Constitution (C), Union (U), ESSENCE (Davis) (E), Gold06 (G), SNLS 1yr (S) and SDSS-II (D)) in the context of the Chevalier-Polarski-Linder (CPL) parametrization w(a) = w 0 +w 1 (1−a), according to their Figure of Merit (FoM), their consistency with the cosmological constant (ΛCDM), their consistency with standard rulers (Cosmic Microwave Background (CMB) and Baryon Acoustic Oscillations (BAO)) and their mutual consistency. We find a significant improvement of the FoM (defined as the inverse area of the 95.4% parameter contour) with the number of SnIa of these datasets ((C) highest FoM, (U), (G), (D), (E), (S) lowest FoM). Standard rulers (CMB+BAO) have a better FoM by about a factor of 3, compared to the highest FoM SnIa dataset (C). We also find that the ranking sequence based on consistency with ΛCDM is identical with the corresponding ranking based on consistency with standard rulers ((S) most consistent, (D), (C), (E), (U), (G) least consistent). The ranking sequence of the datasets however changes when we consider the consistency with an expansion history corresponding to evolving dark energy (w 0 ,w 1 ) = (−1.4,2) crossing the phantom divide line w = −1 (it is practically reversed to (G), (U), (E), (S), (D), (C)). The SALT2 and MLCS2k2 fitters are also compared and some peculiar features of the SDSS-II dataset when standardized with the MLCS2k2 fitter are pointed out. Finally, we construct a statistic to estimate the internal consistency of a collection of SnIa datasets. We find that even though there is good consistency among most samples taken from the above datasets, this consistency decreases significantly when the Gold06 (G) dataset is included in the sample

SIMADL: Simulated Activities of Daily Living Dataset

Directory of Open Access Journals (Sweden)

Talal Alshammari

2018-04-01

Full Text Available With the realisation of the Internet of Things (IoT paradigm, the analysis of the Activities of Daily Living (ADLs, in a smart home environment, is becoming an active research domain. The existence of representative datasets is a key requirement to advance the research in smart home design. Such datasets are an integral part of the visualisation of new smart home concepts as well as the validation and evaluation of emerging machine learning models. Machine learning techniques that can learn ADLs from sensor readings are used to classify, predict and detect anomalous patterns. Such techniques require data that represent relevant smart home scenarios, for training, testing and validation. However, the development of such machine learning techniques is limited by the lack of real smart home datasets, due to the excessive cost of building real smart homes. This paper provides two datasets for classification and anomaly detection. The datasets are generated using OpenSHS, (Open Smart Home Simulator, which is a simulation software for dataset generation. OpenSHS records the daily activities of a participant within a virtual environment. Seven participants simulated their ADLs for different contexts, e.g., weekdays, weekends, mornings and evenings. Eighty-four files in total were generated, representing approximately 63 days worth of activities. Forty-two files of classification of ADLs were simulated in the classification dataset and the other forty-two files are for anomaly detection problems in which anomalous patterns were simulated and injected into the anomaly detection dataset.

The NOAA Dataset Identifier Project

Science.gov (United States)

de la Beaujardiere, J.; Mccullough, H.; Casey, K. S.

2013-12-01

The US National Oceanic and Atmospheric Administration (NOAA) initiated a project in 2013 to assign persistent identifiers to datasets archived at NOAA and to create informational landing pages about those datasets. The goals of this project are to enable the citation of datasets used in products and results in order to help provide credit to data producers, to support traceability and reproducibility, and to enable tracking of data usage and impact. A secondary goal is to encourage the submission of datasets for long-term preservation, because only archived datasets will be eligible for a NOAA-issued identifier. A team was formed with representatives from the National Geophysical, Oceanographic, and Climatic Data Centers (NGDC, NODC, NCDC) to resolve questions including which identifier scheme to use (answer: Digital Object Identifier - DOI), whether or not to embed semantics in identifiers (no), the level of granularity at which to assign identifiers (as coarsely as reasonable), how to handle ongoing time-series data (do not break into chunks), creation mechanism for the landing page (stylesheet from formal metadata record preferred), and others. Decisions made and implementation experience gained will inform the writing of a Data Citation Procedural Directive to be issued by the Environmental Data Management Committee in 2014. Several identifiers have been issued as of July 2013, with more on the way. NOAA is now reporting the number as a metric to federal Open Government initiatives. This paper will provide further details and status of the project.

Pedestrian detection in video surveillance using fully convolutional YOLO neural network

Science.gov (United States)

Molchanov, V. V.; Vishnyakov, B. V.; Vizilter, Y. V.; Vishnyakova, O. V.; Knyaz, V. A.

2017-06-01

More than 80% of video surveillance systems are used for monitoring people. Old human detection algorithms, based on background and foreground modelling, could not even deal with a group of people, to say nothing of a crowd. Recent robust and highly effective pedestrian detection algorithms are a new milestone of video surveillance systems. Based on modern approaches in deep learning, these algorithms produce very discriminative features that can be used for getting robust inference in real visual scenes. They deal with such tasks as distinguishing different persons in a group, overcome problem with sufficient enclosures of human bodies by the foreground, detect various poses of people. In our work we use a new approach which enables to combine detection and classification tasks into one challenge using convolution neural networks. As a start point we choose YOLO CNN, whose authors propose a very efficient way of combining mentioned above tasks by learning a single neural network. This approach showed competitive results with state-of-the-art models such as FAST R-CNN, significantly overcoming them in speed, which allows us to apply it in real time video surveillance and other video monitoring systems. Despite all advantages it suffers from some known drawbacks, related to the fully-connected layers that obstruct applying the CNN to images with different resolution. Also it limits the ability to distinguish small close human figures in groups which is crucial for our tasks since we work with rather low quality images which often include dense small groups of people. In this work we gradually change network architecture to overcome mentioned above problems, train it on a complex pedestrian dataset and finally get the CNN detecting small pedestrians in real scenes.

[Research on developping the spectral dataset for Dunhuang typical colors based on color constancy].

Science.gov (United States)

Liu, Qiang; Wan, Xiao-Xia; Liu, Zhen; Li, Chan; Liang, Jin-Xing

2013-11-01

The present paper aims at developping a method to reasonably set up the typical spectral color dataset for different kinds of Chinese cultural heritage in color rendering process. The world famous wall paintings dating from more than 1700 years ago in Dunhuang Mogao Grottoes was taken as typical case in this research. In order to maintain the color constancy during the color rendering workflow of Dunhuang culture relics, a chromatic adaptation based method for developping the spectral dataset of typical colors for those wall paintings was proposed from the view point of human vision perception ability. Under the help and guidance of researchers in the art-research institution and protection-research institution of Dunhuang Academy and according to the existing research achievement of Dunhuang Research in the past years, 48 typical known Dunhuang pigments were chosen and 240 representative color samples were made with reflective spectral ranging from 360 to 750 nm was acquired by a spectrometer. In order to find the typical colors of the above mentioned color samples, the original dataset was devided into several subgroups by clustering analysis. The grouping number, together with the most typical samples for each subgroup which made up the firstly built typical color dataset, was determined by wilcoxon signed rank test according to the color inconstancy index comprehensively calculated under 6 typical illuminating conditions. Considering the completeness of gamut of Dunhuang wall paintings, 8 complementary colors was determined and finally the typical spectral color dataset was built up which contains 100 representative spectral colors. The analytical calculating results show that the median color inconstancy index of the built dataset in 99% confidence level by wilcoxon signed rank test was 3.28 and the 100 colors are distributing in the whole gamut uniformly, which ensures that this dataset can provide reasonable reference for choosing the color with highest

Control Measure Dataset

Data.gov (United States)

U.S. Environmental Protection Agency — The EPA Control Measure Dataset is a collection of documents describing air pollution control available to regulated facilities for the control and abatement of air...

Low-latency video transmission over high-speed WPANs based on low-power video compression

DEFF Research Database (Denmark)

Belyaev, Evgeny; Turlikov, Andrey; Ukhanova, Ann

2010-01-01

This paper presents latency-constrained video transmission over high-speed wireless personal area networks (WPANs). Low-power video compression is proposed as an alternative to uncompressed video transmission. A video source rate control based on MINMAX quality criteria is introduced. Practical...

Video Self-Modeling

Science.gov (United States)

Buggey, Tom; Ogle, Lindsey

2012-01-01

Video self-modeling (VSM) first appeared on the psychology and education stage in the early 1970s. The practical applications of VSM were limited by lack of access to tools for editing video, which is necessary for almost all self-modeling videos. Thus, VSM remained in the research domain until the advent of camcorders and VCR/DVD players and,…

Video dosimetry: evaluation of X-radiation dose by video fluoroscopic image

International Nuclear Information System (INIS)

Nova, Joao Luiz Leocadio da; Lopes, Ricardo Tadeu

1996-01-01

A new methodology to evaluate the entrance surface dose on patients under radiodiagnosis is presented. A phantom is used in video fluoroscopic procedures in on line video signal system. The images are obtained from a Siemens Polymat 50 and are digitalized. The results show that the entrance surface dose can be obtained in real time from video imaging

A content analysis of smoking fetish videos on YouTube: regulatory implications for tobacco control.

Science.gov (United States)

Kim, Kyongseok; Paek, Hye-Jin; Lynn, Jordan

2010-03-01

This study examined the prevalence, accessibility, and characteristics of eroticized smoking portrayal, also referred to as smoking fetish, on YouTube. The analysis of 200 smoking fetish videos revealed that the smoking fetish videos are prevalent and accessible to adolescents on the website. They featured explicit smoking behavior by sexy, young, and healthy females, with the content corresponding to PG-13 and R movie ratings. We discuss a potential impact of the prosmoking image on youth according to social cognitive theory, and implications for tobacco control.

Akademisk video

DEFF Research Database (Denmark)

Frølunde, Lisbeth

2017-01-01

Dette kapitel har fokus på metodiske problemstillinger, der opstår i forhold til at bruge (digital) video i forbindelse med forskningskommunikation, ikke mindst online. Video har længe været benyttet i forskningen til dataindsamling og forskningskommunikation. Med digitaliseringen og internettet ...

Dual energy X-Ray absorptiometry body composition reference values from NHANES.

Directory of Open Access Journals (Sweden)

Thomas L Kelly

Full Text Available In 2008 the National Center for Health Statistics released a dual energy x-ray absorptiometry (DXA whole body dataset from the NHANES population-based sample acquired with modern fan beam scanners in 15 counties across the United States from 1999 through 2004. The NHANES dataset was partitioned by gender and ethnicity and DXA whole body measures of %fat, fat mass/height(2, lean mass/height(2, appendicular lean mass/height(2, %fat trunk/%fat legs ratio, trunk/limb fat mass ratio of fat, bone mineral content (BMC and bone mineral density (BMD were analyzed to provide reference values for subjects 8 to 85 years old. DXA reference values for adults were normalized to age; reference values for children included total and sub-total whole body results and were normalized to age, height, or lean mass. We developed an obesity classification scheme by using estabbody mass index (BMI classification thresholds and prevalences in young adults to generate matching classification thresholds for Fat Mass Index (FMI; fat mass/height(2. These reference values should be helpful in the evaluation of a variety of adult and childhood abnormalities involving fat, lean, and bone, for establishing entry criteria into clinical trials, and for other medical, research, and epidemiological uses.

VBR video traffic models

CERN Document Server

Tanwir, Savera

2014-01-01

There has been a phenomenal growth in video applications over the past few years. An accurate traffic model of Variable Bit Rate (VBR) video is necessary for performance evaluation of a network design and for generating synthetic traffic that can be used for benchmarking a network. A large number of models for VBR video traffic have been proposed in the literature for different types of video in the past 20 years. Here, the authors have classified and surveyed these models and have also evaluated the models for H.264 AVC and MVC encoded video and discussed their findings.

Gaming to see: action video gaming is associated with enhanced processing of masked stimuli.

Science.gov (United States)

Pohl, Carsten; Kunde, Wilfried; Ganz, Thomas; Conzelmann, Annette; Pauli, Paul; Kiesel, Andrea

2014-01-01

Recent research revealed that action video game players outperform non-players in a wide range of attentional, perceptual and cognitive tasks. Here we tested if expertise in action video games is related to differences regarding the potential of shortly presented stimuli to bias behavior. In a response priming paradigm, participants classified four animal pictures functioning as targets as being smaller or larger than a reference frame. Before each target, one of the same four animal pictures was presented as a masked prime to influence participants' responses in a congruent or incongruent way. Masked primes induced congruence effects, that is, faster responses for congruent compared to incongruent conditions, indicating processing of hardly visible primes. Results also suggested that action video game players showed a larger congruence effect than non-players for 20 ms primes, whereas there was no group difference for 60 ms primes. In addition, there was a tendency for action video game players to detect masked primes for some prime durations better than non-players. Thus, action video game expertise may be accompanied by faster and more efficient processing of shortly presented visual stimuli.

Gaming to see: Action Video Gaming is associated with enhanced processing of masked stimuli

Directory of Open Access Journals (Sweden)

Carsten ePohl

2014-02-01

Full Text Available Recent research revealed that action video game players outperform non-players in a wide range of attentional, perceptual and cognitive tasks. Here we tested if expertise in action video games is related to differences regarding the potential of shortly presented stimuli to bias behaviour. In a response priming paradigm, participants classified four animal pictures functioning as targets as being smaller or larger than a reference frame. Before each target, one of the same four animal pictures was presented as a masked prime to influence participants’ responses in a congruent or incongruent way. Masked primes induced congruence effects, that is, faster responses for congruent compared to incongruent conditions, indicating processing of hardly visible primes. Results also suggested that action video game players showed a larger congruence effect than non-players for 20 ms primes, whereas there was no group difference for 60 ms primes. In addition, there was a tendency for action video game players to detect masked primes for some prime durations better than non-players. Thus, action video game expertise may be accompanied by faster and more efficient processing of shortly presented visual stimuli.

Video Games as a Multifaceted Medium: A Review of Quantitative Social Science Research on Video Games and a Typology of Video Game Research Approaches

Directory of Open Access Journals (Sweden)

James D. Ivory

2013-01-01

Full Text Available Although there is a vast and useful body of quantitative social science research dealing with the social role and impact of video games, it is difficult to compare studies dealing with various dimensions of video games because they are informed by different perspectives and assumptions, employ different methodologies, and address different problems. Studies focusing on different social dimensions of video games can produce varied findings about games’ social function that are often difficult to reconcile— or even contradictory. Research is also often categorized by topic area, rendering a comprehensive view of video games’ social role across topic areas difficult. This interpretive review presents a novel typology of four identified approaches that categorize much of the quantitative social science video game research conducted to date: “video games as stimulus,” “video games as avocation,” “video games as skill,” and “video games as social environment.” This typology is useful because it provides an organizational structure within which the large and growing number of studies on video games can be categorized, guiding comparisons between studies on different research topics and aiding a more comprehensive understanding of video games’ social role. Categorizing the different approaches to video game research provides a useful heuristic for those critiquing and expanding that research, as well as an understandable entry point for scholars new to video game research. Further, and perhaps more importantly, the typology indicates when topics should be explored using different approaches than usual to shed new light on the topic areas. Lastly, the typology exposes the conceptual disconnects between the different approaches to video game research, allowing researchers to consider new ways to bridge gaps between the different approaches’ strengths and limitations with novel methods.

Datasets collected in general practice: an international comparison using the example of obesity.

Science.gov (United States)

Sturgiss, Elizabeth; van Boven, Kees

2018-06-04

International datasets from general practice enable the comparison of how conditions are managed within consultations in different primary healthcare settings. The Australian Bettering the Evaluation and Care of Health (BEACH) and TransHIS from the Netherlands collect in-consultation general practice data that have been used extensively to inform local policy and practice. Obesity is a global health issue with different countries applying varying approaches to management. The objective of the present paper is to compare the primary care management of obesity in Australia and the Netherlands using data collected from consultations. Despite the different prevalence in obesity in the two countries, the number of patients per 1000 patient-years seen with obesity is similar. Patients in Australia with obesity are referred to allied health practitioners more often than Dutch patients. Without quality general practice data, primary care researchers will not have data about the management of conditions within consultations. We use obesity to highlight the strengths of these general practice data sources and to compare their differences. What is known about the topic? Australia had one of the longest-running consecutive datasets about general practice activity in the world, but it has recently lost government funding. The Netherlands has a longitudinal general practice dataset of information collected within consultations since 1985. What does this paper add? We discuss the benefits of general practice-collected data in two countries. Using obesity as a case example, we compare management in general practice between Australia and the Netherlands. This type of analysis should start all international collaborations of primary care management of any health condition. Having a national general practice dataset allows international comparisons of the management of conditions with primary care. Without a current, quality general practice dataset, primary care researchers will not

Crew Resource Management (CRM video storytelling project: a team-based learning activity

Directory of Open Access Journals (Sweden)

Ma, Maggie Jiao

2011-01-01

Full Text Available This Crew Resource Management (CRM video storytelling project asks students to work in a team (4-5 people per team to create (write and produce a video story. The story should demonstrate lacking and ill practices of CRM knowledge and skills, or positive skills used to create a successful scenario in aviation (e. g. , flight training, commercial aviation, airport management. The activity is composed of two parts: (1 creating a video story of CRM in aviation, and (2 delivering a group presentation. Each tem creates a 5-8 minute long video clip of its story. The story must be originally created by the team to educate pilot and/or aviation management students on good practices of CRM in aviation. Accidents and incidents can be used as a reference to inspire ideas. However, this project is not to re-create any previous CRM accidents/incidents. The video story needs to be self-contained and address two or more aspects of CRM specified in the Federal Aviation Administration’s Advisory Circular 120-51. The presentation must include the use of PowerPoint or similar software and additional multimedia visual aids. The presentation itself will last no more than 17 minutes in length; including the actual video story (each group has additional 3 minutes to set up prior to the presentation. During the presentation following the video each team will discuss the CRM problems (or invite audience to identify CRM problems and explain what CRM practices were performed, and should have been performed. This presentation also should describe how each team worked together in order to complete this project (i. e. , good and bad CRM practiced

Markerless registration for image guided surgery. Preoperative image, intraoperative video image, and patient

International Nuclear Information System (INIS)

Kihara, Tomohiko; Tanaka, Yuko

1998-01-01

Real-time and volumetric acquisition of X-ray CT, MR, and SPECT is the latest trend of the medical imaging devices. A clinical challenge is to use these multi-modality volumetric information complementary on patient in the entire diagnostic and surgical processes. The intraoperative image and patient integration intents to establish a common reference frame by image in diagnostic and surgical processes. This provides a quantitative measure during surgery, for which we have been relied mostly on doctors' skills and experiences. The intraoperative image and patient integration involves various technologies, however, we think one of the most important elements is the development of markerless registration, which should be efficient and applicable to the preoperative multi-modality data sets, intraoperative image, and patient. We developed a registration system which integrates preoperative multi-modality images, intraoperative video image, and patient. It consists of a real-time registration of video camera for intraoperative use, a markerless surface sampling matching of patient and image, our previous works of markerless multi-modality image registration of X-ray CT, MR, and SPECT, and an image synthesis on video image. We think these techniques can be used in many applications which involve video camera like devices such as video camera, microscope, and image Intensifier. (author)

The value of an educational video before consultation with a radiation oncologist.

Science.gov (United States)

Matsuyama, Robin K; Lyckholm, Laurie J; Molisani, Anthony; Moghanaki, Drew

2013-06-01

This study aims to assess the efficacy of a radiation therapy (RT) education video for patients referred for treatment. The investigators produced a 23-min guide to radiation therapy DVD, combining didactic material and patient narratives. Patients (n=32) had not yet received their initial consultation. Baseline awareness about cancer and treatment was assessed by surveys including the rapid estimate of adult literacy in medicine. Knowledge about RT was assessed before and after viewing the video with a separate 21 question survey. Differences in benefit for sociodemographic subgroups including age, gender, ethnicity, income, education, and health literacy level were explored. Baseline assessments identified 78 % of patients regardless of sociodemographic status had "little" to "no" basic knowledge of RT. The mean number of correct responses in the 21 question survey assessing how RT works improved from 9.8 to 11.1 after watching the video (peducation (p=0.002). Patient satisfaction with the video was high. Knowledge among cancer patients regarding RT is poor, regardless of sociodemographic factors. This pilot study demonstrates the utility of a brief video to universally improve patient awareness about RT. While patients may ultimately learn about RT during their course of treatment, we advocate for any tools that can improve patient knowledge at the time of initial consultation as this is typically the time they are asked to acknowledge informed consent for treatment.

Playing Video Games While Using or Feeling the Effects of Substances: Associations with Substance Use Problems

Directory of Open Access Journals (Sweden)

Geoffrey L. Ream

2011-10-01

Full Text Available This study tested the hypothesis that playing video games while using or feeling the effects of a substance—referred to herein as “concurrent use”—is related to substance use problems after controlling for substance use frequency, video gaming as an enthusiastic hobby, and demographic factors. Data were drawn from a nationally representative online survey of adult video gamers conducted by Knowledge Networks, valid n = 2,885. Problem video game playing behavior was operationalized using Tejeiro Salguero and Bersabé Morán’s 2002 problem video game play (PVP measure, and measures for substance use problems were taken from the National Survey of Drug Use and Health (NSDUH. Separate structural equation modeling analyses were conducted for users of caffeine, tobacco, alcohol, and marijuana. In all four models, concurrent use was directly associated with substance use problems, but not with PVP. Video gaming as an enthusiastic hobby was associated with substance use problems via two indirect paths: through PVP for all substances, and through concurrent use for caffeine, tobacco, and alcohol only. Results illustrate the potential for “drug interaction” between self-reinforcing behaviors and addictive substances, with implications for the development of problem use.

Playing Video Games While Using or Feeling the Effects of Substances: Associations with Substance Use Problems

Science.gov (United States)

Ream, Geoffrey L.; Elliott, Luther C.; Dunlap, Eloise

2011-01-01

This study tested the hypothesis that playing video games while using or feeling the effects of a substance—referred to herein as “concurrent use”—is related to substance use problems after controlling for substance use frequency, video gaming as an enthusiastic hobby, and demographic factors. Data were drawn from a nationally representative online survey of adult video gamers conducted by Knowledge Networks, valid n = 2,885. Problem video game playing behavior was operationalized using Tejeiro Salguero and Bersabé Morán’s 2002 problem video game play (PVP) measure, and measures for substance use problems were taken from the National Survey of Drug Use and Health (NSDUH). Separate structural equation modeling analyses were conducted for users of caffeine, tobacco, alcohol, and marijuana. In all four models, concurrent use was directly associated with substance use problems, but not with PVP. Video gaming as an enthusiastic hobby was associated with substance use problems via two indirect paths: through PVP for all substances, and through concurrent use for caffeine, tobacco, and alcohol only. Results illustrate the potential for “drug interaction” between self-reinforcing behaviors and addictive substances, with implications for the development of problem use. PMID:22073023

Playing video games while using or feeling the effects of substances: associations with substance use problems.

Science.gov (United States)

Ream, Geoffrey L; Elliott, Luther C; Dunlap, Eloise

2011-10-01

This study tested the hypothesis that playing video games while using or feeling the effects of a substance--referred to herein as "concurrent use"-is related to substance use problems after controlling for substance use frequency, video gaming as an enthusiastic hobby, and demographic factors. Data were drawn from a nationally representative online survey of adult video gamers conducted by Knowledge Networks, valid n = 2,885. Problem video game playing behavior was operationalized using Tejeiro Salguero and Bersabé Morán's 2002 problem video game play (PVP) measure, and measures for substance use problems were taken from the National Survey of Drug Use and Health (NSDUH). Separate structural equation modeling analyses were conducted for users of caffeine, tobacco, alcohol, and marijuana. In all four models, concurrent use was directly associated with substance use problems, but not with PVP. Video gaming as an enthusiastic hobby was associated with substance use problems via two indirect paths: through PVP for all substances, and through concurrent use for caffeine, tobacco, and alcohol only. Results illustrate the potential for "drug interaction" between self-reinforcing behaviors and addictive substances, with implications for the development of problem use.

RGBD Video Based Human Hand Trajectory Tracking and Gesture Recognition System

Directory of Open Access Journals (Sweden)

Weihua Liu

2015-01-01

Full Text Available The task of human hand trajectory tracking and gesture trajectory recognition based on synchronized color and depth video is considered. Toward this end, in the facet of hand tracking, a joint observation model with the hand cues of skin saliency, motion and depth is integrated into particle filter in order to move particles to local peak in the likelihood. The proposed hand tracking method, namely, salient skin, motion, and depth based particle filter (SSMD-PF, is capable of improving the tracking accuracy considerably, in the context of the signer performing the gesture toward the camera device and in front of moving, cluttered backgrounds. In the facet of gesture recognition, a shape-order context descriptor on the basis of shape context is introduced, which can describe the gesture in spatiotemporal domain. The efficient shape-order context descriptor can reveal the shape relationship and embed gesture sequence order information into descriptor. Moreover, the shape-order context leads to a robust score for gesture invariant. Our approach is complemented with experimental results on the settings of the challenging hand-signed digits datasets and American sign language dataset, which corroborate the performance of the novel techniques.

Digital Video in Research

DEFF Research Database (Denmark)

Frølunde, Lisbeth

2012-01-01

Is video becoming “the new black” in academia, if so, what are the challenges? The integration of video in research methodology (for collection, analysis) is well-known, but the use of “academic video” for dissemination is relatively new (Eriksson and Sørensen). The focus of this paper is academic......). In the video, I appear (along with other researchers) and two Danish film directors, and excerpts from their film. My challenges included how to edit the academic video and organize the collaborative effort. I consider video editing as a semiotic, transformative process of “reassembling” voices....... In the discussion, I review academic video in terms of relevance and implications for research practice. The theoretical background is social constructivist, combining social semiotics (Kress, van Leeuwen, McCloud), visual anthropology (Banks, Pink) and dialogic theory (Bakhtin). The Bakhtinian notion of “voices...

Publishing datasets with eSciDoc and panMetaDocs

Science.gov (United States)

Ulbricht, D.; Klump, J.; Bertelmann, R.

2012-04-01

publishing scientific datasets as electronic data supplements to research papers. Publication of research manuscripts has an already well established workflow that shares junctures with other processes and involves several parties in the process of dataset publication. Activities of the author, the reviewer, the print publisher and the data publisher have to be coordinated into a common data publication workflow. The case of data publication at GFZ Potsdam displays some specifics, e.g. the DOIDB webservice. The DOIDB is a proxy service at GFZ for the DataCite [4] DOI registration and its metadata store. DOIDB provides a local summary of the dataset DOIs registered through GFZ as a publication agent. An additional use case for the DOIDB is its function to enrich the datacite metadata with additional custom attributes, like a geographic reference in a DIF record. These attributes are at the moment not available in the datacite metadata schema but would be valuable elements for the compilation of data catalogues in the earth sciences and for dissemination of catalogue data via OAI-PMH. [1] http://www.escidoc.org , eSciDoc, FIZ Karlruhe, Germany [2] http://panmetadocs.sf.net , panMetaDocs, GFZ Potsdam, Germany [3] http://metaworks.pangaea.de , panMetaWorks, Dr. R. Huber, MARUM, Univ. Bremen, Germany [4] http://www.datacite.org

NEI You Tube Videos: Amblyopia

Medline Plus

Full Text Available ... search for current job openings visit HHS USAJobs Home >> NEI YouTube Videos >> NEI YouTube Videos: Amblyopia Listen NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration Amblyopia Animations Blindness Cataract ...

Joining the Video-Game Literacy Club: A Reluctant Mother Tries to Join the "Flow"

Science.gov (United States)

Norton-Meier, Lori

2005-01-01

The author discusses the influence of video games and other technologies on modern family life, drawing on her own experiences. The implications of digital and other "new" and multiple literacies are described, with reference particularly to the work of Patrick Shannon and James Paul Gee.

Talking Video in 'Everyday Life'

DEFF Research Database (Denmark)

McIlvenny, Paul

For better or worse, video technologies have made their way into many domains of social life, for example in the domain of therapeutics. Techniques such as Marte Meo, Video Interaction Guidance (ViG), Video-Enhanced Reflection on Communication, Video Home Training and Video intervention....../prevention (VIP) all promote the use of video as a therapeutic tool. This paper focuses on media therapeutics and the various in situ uses of video technologies in the mass media for therapeutic purposes. Reality TV parenting programmes such as Supernanny, Little Angels, The House of Tiny Tearaways, Honey, We...... observation and instruction (directives) relayed across different spaces; 2) the use of recorded video by participants to visualise, spatialise and localise talk and action that is distant in time and/or space; 3) the translating, stretching and cutting of social experience in and through the situated use...

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.

NEI You Tube Videos: Amblyopia

Medline Plus

Full Text Available ... search for current job openings visit HHS USAJobs Home » NEI YouTube Videos » NEI YouTube Videos: Amblyopia Listen NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration Amblyopia Animations Blindness Cataract ...

Videos for Science Communication and Nature Interpretation: The TIB|AV-Portal as Resource.

Science.gov (United States)

Marín Arraiza, Paloma; Plank, Margret; Löwe, Peter

2016-04-01

Scientific audiovisual media such as videos of research, interactive displays or computer animations has become an important part of scientific communication and education. Dynamic phenomena can be described better by audiovisual media than by words and pictures. For this reason, scientific videos help us to understand and discuss environmental phenomena more efficiently. Moreover, the creation of scientific videos is easier than ever, thanks to mobile devices and open source editing software. Video-clips, webinars or even the interactive part of a PICO are formats of scientific audiovisual media used in the Geosciences. This type of media translates the location-referenced Science Communication such as environmental interpretation into computed-based Science Communication. A new way of Science Communication is video abstracting. A video abstract is a three- to five-minute video statement that provides background information about a research paper. It also gives authors the opportunity to present their research activities to a wider audience. Since this kind of media have become an important part of scientific communication there is a need for reliable infrastructures which are capable of managing the digital assets researchers generate. Using the reference of the usecase of video abstracts this paper gives an overview over the activities by the German National Library of Science and Technology (TIB) regarding publishing and linking audiovisual media in a scientifically sound way. The German National Library of Science and Technology (TIB) in cooperation with the Hasso Plattner Institute (HPI) developed a web-based portal (av.tib.eu) that optimises access to scientific videos in the fields of science and technology. Videos from the realms of science and technology can easily be uploaded onto the TIB|AV Portal. Within a short period of time the videos are assigned a digital object identifier (DOI). This enables them to be referenced, cited, and linked (e.g. to the

Age, Gender, and Fine-Grained Ethnicity Prediction using Convolutional Neural Networks for the East Asian Face Dataset

Energy Technology Data Exchange (ETDEWEB)

Srinivas, Nisha [ORNL; Rose, Derek C [ORNL; Bolme, David S [ORNL; Mahalingam, Gayathri [ORNL; Atwal, Harleen [ORNL; Ricanek, Karl [ORNL

2017-01-01

This paper examines the difficulty associated with performing machine-based automatic demographic prediction on a sub-population of Asian faces. We introduce the Wild East Asian Face dataset (WEAFD), a new and unique dataset to the research community. This dataset consists primarily of labeled face images of individuals from East Asian countries, including Vietnam, Burma, Thailand, China, Korea, Japan, Indonesia, and Malaysia. East Asian turk annotators were uniquely used to judge the age and fine grain ethnicity attributes to reduce the impact of the other race effect and improve quality of annotations. We focus on predicting age, gender and fine-grained ethnicity of an individual by providing baseline results with a convolutional neural network (CNN). Finegrained ethnicity prediction refers to predicting ethnicity of an individual by country or sub-region (Chinese, Japanese, Korean, etc.) of the East Asian continent. Performance for two CNN architectures is presented, highlighting the difficulty of these tasks and showcasing potential design considerations that ease network optimization by promoting region based feature extraction.

A framework for automatic creation of gold-standard rigid 3D-2D registration datasets.

Science.gov (United States)

Madan, Hennadii; Pernuš, Franjo; Likar, Boštjan; Špiclin, Žiga

2017-02-01

Advanced image-guided medical procedures incorporate 2D intra-interventional information into pre-interventional 3D image and plan of the procedure through 3D/2D image registration (32R). To enter clinical use, and even for publication purposes, novel and existing 32R methods have to be rigorously validated. The performance of a 32R method can be estimated by comparing it to an accurate reference or gold standard method (usually based on fiducial markers) on the same set of images (gold standard dataset). Objective validation and comparison of methods are possible only if evaluation methodology is standardized, and the gold standard  dataset is made publicly available. Currently, very few such datasets exist and only one contains images of multiple patients acquired during a procedure. To encourage the creation of gold standard 32R datasets, we propose an automatic framework. The framework is based on rigid registration of fiducial markers. The main novelty is spatial grouping of fiducial markers on the carrier device, which enables automatic marker localization and identification across the 3D and 2D images. The proposed framework was demonstrated on clinical angiograms of 20 patients. Rigid 32R computed by the framework was more accurate than that obtained manually, with the respective target registration error below 0.027 mm compared to 0.040 mm. The framework is applicable for gold standard setup on any rigid anatomy, provided that the acquired images contain spatially grouped fiducial markers. The gold standard datasets and software will be made publicly available.

Airborne Video Surveillance

National Research Council Canada - National Science Library

Blask, Steven

2002-01-01

The DARPA Airborne Video Surveillance (AVS) program was established to develop and promote technologies to make airborne video more useful, providing capabilities that achieve a UAV force multiplier...

Reflections on academic video

Directory of Open Access Journals (Sweden)

Thommy Eriksson

2012-11-01

Full Text Available As academics we study, research and teach audiovisual media, yet rarely disseminate and mediate through it. Today, developments in production technologies have enabled academic researchers to create videos and mediate audiovisually. In academia it is taken for granted that everyone can write a text. Is it now time to assume that everyone can make a video essay? Using the online journal of academic videos Audiovisual Thinking and the videos published in it as a case study, this article seeks to reflect on the emergence and legacy of academic audiovisual dissemination. Anchoring academic video and audiovisual dissemination of knowledge in two critical traditions, documentary theory and semiotics, we will argue that academic video is in fact already present in a variety of academic disciplines, and that academic audiovisual essays are bringing trends and developments that have long been part of academic discourse to their logical conclusion.

Informal Physics Learning from Video Games: A Case Study Using Gameplay Videos

Science.gov (United States)

Croxton, DeVaughn; Kortemeyer, Gerd

2018-01-01

Researching informal gameplay can be challenging, since as soon as a formal study design is imposed, it becomes neither casual nor self-motivated. As a case study of a non-invasive design, we analyze publicly posted gameplay videos to assess the effectiveness of a physics educational video game on special relativity. These videos offer unique…

Performance evaluation of tile-based Fisher Ratio analysis using a benchmark yeast metabolome dataset.

Science.gov (United States)

Watson, Nathanial E; Parsons, Brendon A; Synovec, Robert E

2016-08-12

Performance of tile-based Fisher Ratio (F-ratio) data analysis, recently developed for discovery-based studies using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS), is evaluated with a metabolomics dataset that had been previously analyzed in great detail, but while taking a brute force approach. The previously analyzed data (referred to herein as the benchmark dataset) were intracellular extracts from Saccharomyces cerevisiae (yeast), either metabolizing glucose (repressed) or ethanol (derepressed), which define the two classes in the discovery-based analysis to find metabolites that are statistically different in concentration between the two classes. Beneficially, this previously analyzed dataset provides a concrete means to validate the tile-based F-ratio software. Herein, we demonstrate and validate the significant benefits of applying tile-based F-ratio analysis. The yeast metabolomics data are analyzed more rapidly in about one week versus one year for the prior studies with this dataset. Furthermore, a null distribution analysis is implemented to statistically determine an adequate F-ratio threshold, whereby the variables with F-ratio values below the threshold can be ignored as not class distinguishing, which provides the analyst with confidence when analyzing the hit table. Forty-six of the fifty-four benchmarked changing metabolites were discovered by the new methodology while consistently excluding all but one of the benchmarked nineteen false positive metabolites previously identified. Copyright © 2016 Elsevier B.V. All rights reserved.

Technical note: Space-time analysis of rainfall extremes in Italy: clues from a reconciled dataset

Science.gov (United States)

Libertino, Andrea; Ganora, Daniele; Claps, Pierluigi

2018-05-01

Like other Mediterranean areas, Italy is prone to the development of events with significant rainfall intensity, lasting for several hours. The main triggering mechanisms of these events are quite well known, but the aim of developing rainstorm hazard maps compatible with their actual probability of occurrence is still far from being reached. A systematic frequency analysis of these occasional highly intense events would require a complete countrywide dataset of sub-daily rainfall records, but this kind of information was still lacking for the Italian territory. In this work several sources of data are gathered, for assembling the first comprehensive and updated dataset of extreme rainfall of short duration in Italy. The resulting dataset, referred to as the Italian Rainfall Extreme Dataset (I-RED), includes the annual maximum rainfalls recorded in 1 to 24 consecutive hours from more than 4500 stations across the country, spanning the period between 1916 and 2014. A detailed description of the spatial and temporal coverage of the I-RED is presented, together with an exploratory statistical analysis aimed at providing preliminary information on the climatology of extreme rainfall at the national scale. Due to some legal restrictions, the database can be provided only under certain conditions. Taking into account the potentialities emerging from the analysis, a description of the ongoing and planned future work activities on the database is provided.

360-degree interactive video application for Cultural Heritage Education

OpenAIRE

Argyriou, L.; Economou, D.; Bouki, V.

2017-01-01

There is a growing interest nowadays of using immersive technologies to promote Cultural Heritage (CH), engage and educate visitors, tourists and citizens. Such examples refer mainly to the use of Virtual Reality (VR) technology or focus on the enhancement of the real world by superimposing digital artefacts, so called Augmented Reality (AR) applications. A new medium that has been introduced lately as an innovative form of experiencing immersion is the 360-degree video, imposing further rese...

Fluxnet Synthesis Dataset Collaboration Infrastructure

Energy Technology Data Exchange (ETDEWEB)

Agarwal, Deborah A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Humphrey, Marty [Univ. of Virginia, Charlottesville, VA (United States); van Ingen, Catharine [Microsoft. San Francisco, CA (United States); Beekwilder, Norm [Univ. of Virginia, Charlottesville, VA (United States); Goode, Monte [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jackson, Keith [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Rodriguez, Matt [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Weber, Robin [Univ. of California, Berkeley, CA (United States)

2008-02-06

The Fluxnet synthesis dataset originally compiled for the La Thuile workshop contained approximately 600 site years. Since the workshop, several additional site years have been added and the dataset now contains over 920 site years from over 240 sites. A data refresh update is expected to increase those numbers in the next few months. The ancillary data describing the sites continues to evolve as well. There are on the order of 120 site contacts and 60proposals have been approved to use thedata. These proposals involve around 120 researchers. The size and complexity of the dataset and collaboration has led to a new approach to providing access to the data and collaboration support and the support team attended the workshop and worked closely with the attendees and the Fluxnet project office to define the requirements for the support infrastructure. As a result of this effort, a new website (http://www.fluxdata.org) has been created to provide access to the Fluxnet synthesis dataset. This new web site is based on a scientific data server which enables browsing of the data on-line, data download, and version tracking. We leverage database and data analysis tools such as OLAP data cubes and web reports to enable browser and Excel pivot table access to the data.

A new video programme

CERN Multimedia

CERN video productions

2011-01-01

"What's new @ CERN?", a new monthly video programme, will be broadcast on the Monday of every month on webcast.cern.ch. Aimed at the general public, the programme will cover the latest CERN news, with guests and explanatory features. Tune in on Monday 3 October at 4 pm (CET) to see the programme in English, and then at 4:20 pm (CET) for the French version.   var flash_video_player=get_video_player_path(); insert_player_for_external('Video/Public/Movies/2011/CERN-MOVIE-2011-129/CERN-MOVIE-2011-129-0753-kbps-640x360-25-fps-audio-64-kbps-44-kHz-stereo', 'mms://mediastream.cern.ch/MediaArchive/Video/Public/Movies/2011/CERN-MOVIE-2011-129/CERN-MOVIE-2011-129-Multirate-200-to-753-kbps-640x360-25-fps.wmv', 'false', 480, 360, 'https://mediastream.cern.ch/MediaArchive/Video/Public/Movies/2011/CERN-MOVIE-2011-129/CERN-MOVIE-2011-129-posterframe-640x360-at-10-percent.jpg', '1383406', true, 'Video/Public/Movies/2011/CERN-MOVIE-2011-129/CERN-MOVIE-2011-129-0600-kbps-maxH-360-25-fps-...

Self-Recognition in Live Videos by Young Children: Does Video Training Help?

Science.gov (United States)

Demir, Defne; Skouteris, Helen

2010-01-01

The overall aim of the experiment reported here was to establish whether self-recognition in live video can be facilitated when live video training is provided to children aged 2-2.5 years. While the majority of children failed the test of live self-recognition prior to video training, more than half exhibited live self-recognition post video…

Simulation of Smart Home Activity Datasets

Directory of Open Access Journals (Sweden)

Jonathan Synnott

2015-06-01

Full Text Available A globally ageing population is resulting in an increased prevalence of chronic conditions which affect older adults. Such conditions require long-term care and management to maximize quality of life, placing an increasing strain on healthcare resources. Intelligent environments such as smart homes facilitate long-term monitoring of activities in the home through the use of sensor technology. Access to sensor datasets is necessary for the development of novel activity monitoring and recognition approaches. Access to such datasets is limited due to issues such as sensor cost, availability and deployment time. The use of simulated environments and sensors may address these issues and facilitate the generation of comprehensive datasets. This paper provides a review of existing approaches for the generation of simulated smart home activity datasets, including model-based approaches and interactive approaches which implement virtual sensors, environments and avatars. The paper also provides recommendation for future work in intelligent environment simulation.

Simulation of Smart Home Activity Datasets.

Science.gov (United States)

Synnott, Jonathan; Nugent, Chris; Jeffers, Paul

2015-06-16

A globally ageing population is resulting in an increased prevalence of chronic conditions which affect older adults. Such conditions require long-term care and management to maximize quality of life, placing an increasing strain on healthcare resources. Intelligent environments such as smart homes facilitate long-term monitoring of activities in the home through the use of sensor technology. Access to sensor datasets is necessary for the development of novel activity monitoring and recognition approaches. Access to such datasets is limited due to issues such as sensor cost, availability and deployment time. The use of simulated environments and sensors may address these issues and facilitate the generation of comprehensive datasets. This paper provides a review of existing approaches for the generation of simulated smart home activity datasets, including model-based approaches and interactive approaches which implement virtual sensors, environments and avatars. The paper also provides recommendation for future work in intelligent environment simulation.

Video Toroid Cavity Imager

Energy Technology Data Exchange (ETDEWEB)

Gerald, Rex E. II; Sanchez, Jairo; Rathke, Jerome W.

2004-08-10

A video toroid cavity imager for in situ measurement of electrochemical properties of an electrolytic material sample includes a cylindrical toroid cavity resonator containing the sample and employs NMR and video imaging for providing high-resolution spectral and visual information of molecular characteristics of the sample on a real-time basis. A large magnetic field is applied to the sample under controlled temperature and pressure conditions to simultaneously provide NMR spectroscopy and video imaging capabilities for investigating electrochemical transformations of materials or the evolution of long-range molecular aggregation during cooling of hydrocarbon melts. The video toroid cavity imager includes a miniature commercial video camera with an adjustable lens, a modified compression coin cell imager with a fiat circular principal detector element, and a sample mounted on a transparent circular glass disk, and provides NMR information as well as a video image of a sample, such as a polymer film, with micrometer resolution.

A Framework for Video Modeling

NARCIS (Netherlands)

Petkovic, M.; Jonker, Willem

In recent years, research in video databases has increased greatly, but relatively little work has been done in the area of semantic content-based retrieval. In this paper, we present a framework for video modelling with emphasis on semantic content of video data. The video data model presented

Video library for video imaging detection at intersection stop lines.

Science.gov (United States)

2010-04-01

The objective of this activity was to record video that could be used for controlled : evaluation of video image vehicle detection system (VIVDS) products and software upgrades to : existing products based on a list of conditions that might be diffic...

Solar Integration National Dataset Toolkit | Grid Modernization | NREL

Science.gov (United States)

Solar Integration National Dataset Toolkit Solar Integration National Dataset Toolkit NREL is working on a Solar Integration National Dataset (SIND) Toolkit to enable researchers to perform U.S . regional solar generation integration studies. It will provide modeled, coherent subhourly solar power data

The Children's Video Marketplace.

Science.gov (United States)

Ducey, Richard V.

This report examines a growing submarket, the children's video marketplace, which comprises broadcast, cable, and video programming for children 2 to 11 years old. A description of the tremendous growth in the availability and distribution of children's programming is presented, the economics of the children's video marketplace are briefly…

Role of video games in improving health-related outcomes: a systematic review.

Science.gov (United States)

Primack, Brian A; Carroll, Mary V; McNamara, Megan; Klem, Mary Lou; King, Brandy; Rich, Michael; Chan, Chun W; Nayak, Smita

2012-06-01

Video games represent a multibillion-dollar industry in the U.S. Although video gaming has been associated with many negative health consequences, it also may be useful for therapeutic purposes. The goal of this study was to determine whether video games may be useful in improving health outcomes. Literature searches were performed in February 2010 in six databases: the Center on Media and Child Health Database of Research, MEDLINE, CINAHL, PsycINFO, EMBASE, and the Cochrane Central Register of Controlled Trials. Reference lists were hand-searched to identify additional studies. Only RCTs that tested the effect of video games on a positive, clinically relevant health consequence were included. Study selection criteria were strictly defined and applied by two researchers working independently. Study background information (e.g., location, funding source); sample data (e.g., number of study participants, demographics); intervention and control details; outcomes data; and quality measures were abstracted independently by two researchers. Of 1452 articles retrieved using the current search strategy, 38 met all criteria for inclusion. Eligible studies used video games to provide physical therapy, psychological therapy, improved disease self-management, health education, distraction from discomfort, increased physical activity, and skills training for clinicians. Among the 38 studies, a total of 195 health outcomes were examined. Video games improved 69% of psychological therapy outcomes, 59% of physical therapy outcomes, 50% of physical activity outcomes, 46% of clinician skills outcomes, 42% of health education outcomes, 42% of pain distraction outcomes, and 37% of disease self-management outcomes. Study quality was generally poor; for example, two thirds (66%) of studies had follow-up periods of video games to improve health outcomes, particularly in the areas of psychological therapy and physical therapy. RCTs with appropriate rigor will help build evidence in this

Toward enhancing the distributed video coder under a multiview video codec framework

Science.gov (United States)

Lee, Shih-Chieh; Chen, Jiann-Jone; Tsai, Yao-Hong; Chen, Chin-Hua

2016-11-01

The advance of video coding technology enables multiview video (MVV) or three-dimensional television (3-D TV) display for users with or without glasses. For mobile devices or wireless applications, a distributed video coder (DVC) can be utilized to shift the encoder complexity to decoder under the MVV coding framework, denoted as multiview distributed video coding (MDVC). We proposed to exploit both inter- and intraview video correlations to enhance side information (SI) and improve the MDVC performance: (1) based on the multiview motion estimation (MVME) framework, a categorized block matching prediction with fidelity weights (COMPETE) was proposed to yield a high quality SI frame for better DVC reconstructed images. (2) The block transform coefficient properties, i.e., DCs and ACs, were exploited to design the priority rate control for the turbo code, such that the DVC decoding can be carried out with fewest parity bits. In comparison, the proposed COMPETE method demonstrated lower time complexity, while presenting better reconstructed video quality. Simulations show that the proposed COMPETE can reduce the time complexity of MVME to 1.29 to 2.56 times smaller, as compared to previous hybrid MVME methods, while the image peak signal to noise ratios (PSNRs) of a decoded video can be improved 0.2 to 3.5 dB, as compared to H.264/AVC intracoding.

NEI You Tube Videos: Amblyopia

Medline Plus

Full Text Available ... Amaurosis Low Vision Refractive Errors Retinopathy of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded video for NEI YouTube Videos: Amblyopia NEI Home Contact Us A-Z Site Map NEI on Social Media Information in Spanish (Información en español) Website, ...

Wind Integration National Dataset Toolkit | Grid Modernization | NREL

Science.gov (United States)

Integration National Dataset Toolkit Wind Integration National Dataset Toolkit The Wind Integration National Dataset (WIND) Toolkit is an update and expansion of the Eastern Wind Integration Data Set and Western Wind Integration Data Set. It supports the next generation of wind integration studies. WIND

The energy expenditure of an activity-promoting video game compared to sedentary video games and TV watching.

Science.gov (United States)

Mitre, Naim; Foster, Randal C; Lanningham-Foster, Lorraine; Levine, James A

2011-01-01

In the present study we investigated the effect of television watching and the use of activity-promoting video games on energy expenditure in obese and lean children. Energy expenditure and physical activity were measured while participants were watching television, playing a video game on a traditional sedentary video game console, and while playing the same video game on an activity-promoting video game console. Energy expenditure was significantly greater than television watching and playing video games on a sedentary video game console when children played the video game on the activity-promoting console. When examining movement with accelerometry, children moved significantly more when playing the video game on the Nintendo Wii console. Activity-promoting video games have shown to increase movement, and be an important tool to raise energy expenditure by 50% when compared to sedentary activities of daily living.

Fast compressed domain motion detection in H.264 video streams for video surveillance applications

DEFF Research Database (Denmark)

Szczerba, Krzysztof; Forchhammer, Søren; Støttrup-Andersen, Jesper

2009-01-01

This paper presents a novel approach to fast motion detection in H.264/MPEG-4 advanced video coding (AVC) compressed video streams for IP video surveillance systems. The goal is to develop algorithms which may be useful in a real-life industrial perspective by facilitating the processing of large...... on motion vectors embedded in the video stream without requiring a full decoding and reconstruction of video frames. To improve the robustness to noise, a confidence measure based on temporal and spatial clues is introduced to increase the probability of correct detection. The algorithm was tested on indoor...

Construction of Polarimetric Radar-Based Reference Rain Maps for the Iowa Flood Studies Campaign

Science.gov (United States)

Petersen, Walt; Krajewski, Witek; Wolff, David; Gatlin, Patrick

2015-04-01

The Global Precipitation Measurement (GPM) Mission Iowa Flood Studies (IFloodS) campaign was conducted in central and northeastern Iowa during the months of April-June, 2013. Specific science objectives for IFloodS included quantification of uncertainties in satellite and ground-based estimates of precipitation, 4-D characterization of precipitation physical processes and associated parameters (e.g., size distributions, water contents, types, structure etc.), assessment of the impact of precipitation estimation uncertainty and physical processes on hydrologic predictive skill, and refinement of field observations and data analysis approaches as they pertain to future GPM integrated hydrologic validation and related field studies. In addition to field campaign archival of raw and processed satellite data (including precipitation products), key ground-based platforms such as the NASA NPOL S-band and D3R Ka/Ku-band dual-polarimetric radars, University of Iowa X-band dual-polarimetric radars, a large network of paired rain gauge platforms, and a large network of 2D Video and Parsivel disdrometers were deployed. In something of a canonical approach, the radar (NPOL in particular), gauge and disdrometer observational assets were deployed to create a consistent high-quality distributed (time and space sampling) radar-based ground "reference" rainfall dataset, with known uncertainties, that could be used for assessing the satellite-based precipitation products at a range of space/time scales. Subsequently, the impact of uncertainties in the satellite products could be evaluated relative to the ground-benchmark in coupled weather, land-surface and distributed hydrologic modeling frameworks as related to flood prediction. Relative to establishing the ground-based "benchmark", numerous avenues were pursued in the making and verification of IFloodS "reference" dual-polarimetric radar-based rain maps, and this study documents the process and results as they pertain specifically

Construction of Polarimetric Radar-Based Reference Rain Maps for the Iowa Flood Studies Campaign

Science.gov (United States)

Petersen, Walter; Wolff, David; Krajewski, Witek; Gatlin, Patrick

2015-01-01

The Global Precipitation Measurement (GPM) Mission Iowa Flood Studies (IFloodS) campaign was conducted in central and northeastern Iowa during the months of April-June, 2013. Specific science objectives for IFloodS included quantification of uncertainties in satellite and ground-based estimates of precipitation, 4-D characterization of precipitation physical processes and associated parameters (e.g., size distributions, water contents, types, structure etc.), assessment of the impact of precipitation estimation uncertainty and physical processes on hydrologic predictive skill, and refinement of field observations and data analysis approaches as they pertain to future GPM integrated hydrologic validation and related field studies. In addition to field campaign archival of raw and processed satellite data (including precipitation products), key ground-based platforms such as the NASA NPOL S-band and D3R Ka/Ku-band dual-polarimetric radars, University of Iowa X-band dual-polarimetric radars, a large network of paired rain gauge platforms, and a large network of 2D Video and Parsivel disdrometers were deployed. In something of a canonical approach, the radar (NPOL in particular), gauge and disdrometer observational assets were deployed to create a consistent high-quality distributed (time and space sampling) radar-based ground "reference" rainfall dataset, with known uncertainties, that could be used for assessing the satellite-based precipitation products at a range of space/time scales. Subsequently, the impact of uncertainties in the satellite products could be evaluated relative to the ground-benchmark in coupled weather, land-surface and distributed hydrologic modeling frameworks as related to flood prediction. Relative to establishing the ground-based "benchmark", numerous avenues were pursued in the making and verification of IFloodS "reference" dual-polarimetric radar-based rain maps, and this study documents the process and results as they pertain specifically

Sound for digital video

CERN Document Server

Holman, Tomlinson

2013-01-01

Achieve professional quality sound on a limited budget! Harness all new, Hollywood style audio techniques to bring your independent film and video productions to the next level.In Sound for Digital Video, Second Edition industry experts Tomlinson Holman and Arthur Baum give you the tools and knowledge to apply recent advances in audio capture, video recording, editing workflow, and mixing to your own film or video with stunning results. This fresh edition is chockfull of techniques, tricks, and workflow secrets that you can apply to your own projects from preproduction

Automatic tracking of cells for video microscopy in patch clamp experiments.

Science.gov (United States)

Peixoto, Helton M; Munguba, Hermany; Cruz, Rossana M S; Guerreiro, Ana M G; Leao, Richardson N

2014-06-20

Visualisation of neurons labeled with fluorescent proteins or compounds generally require exposure to intense light for a relatively long period of time, often leading to bleaching of the fluorescent probe and photodamage of the tissue. Here we created a technique to drastically shorten light exposure and improve the targeting of fluorescent labeled cells that is specially useful for patch-clamp recordings. We applied image tracking and mask overlay to reduce the time of fluorescence exposure and minimise mistakes when identifying neurons. Neurons are first identified according to visual criteria (e.g. fluorescence protein expression, shape, viability etc.) and a transmission microscopy image Differential Interference Contrast (DIC) or Dodt contrast containing the cell used as a reference for the tracking algorithm. A fluorescence image can also be acquired later to be used as a mask (that can be overlaid on the target during live transmission video). As patch-clamp experiments require translating the microscope stage, we used pattern matching to track reference neurons in order to move the fluorescence mask to match the new position of the objective in relation to the sample. For the image processing we used the Open Source Computer Vision (OpenCV) library, including the Speeded-Up Robust Features (SURF) for tracking cells. The dataset of images (n = 720) was analyzed under normal conditions of acquisition and with influence of noise (defocusing and brightness). We validated the method in dissociated neuronal cultures and fresh brain slices expressing Enhanced Yellow Fluorescent Protein (eYFP) or Tandem Dimer Tomato (tdTomato) proteins, which considerably decreased the exposure to fluorescence excitation, thereby minimising photodamage. We also show that the neuron tracking can be used in differential interference contrast or Dodt contrast microscopy. The techniques of digital image processing used in this work are an important addition to the set of microscopy

Mobile Video in Everyday Social Interactions

Science.gov (United States)

Reponen, Erika; Lehikoinen, Jaakko; Impiö, Jussi

Video recording has become a spontaneous everyday activity for many people, thanks to the video capabilities of modern mobile phones. Internet connectivity of mobile phones enables fluent sharing of captured material even real-time, which makes video an up-and-coming everyday interaction medium. In this article we discuss the effect of the video camera in the social environment, everyday life situations, mainly based on a study where four groups of people used digital video cameras in their normal settings. We also reflect on another study of ours, relating to real-time mobile video communication and discuss future views. The aim of our research is to understand the possibilities in the domain of mobile video. Live and delayed sharing seem to have their special characteristics, live video being used as a virtual window between places whereas delayed video usage has more scope for good-quality content. While this novel way of interacting via mobile video enables new social patterns, it also raises new concerns for privacy and trust between participating persons in all roles, largely due to the widely spreading possibilities of videos. Video in a social situation affects cameramen (who record), targets (who are recorded), passers-by (who are unintentionally in the situation), and the audience (who follow the videos or recording situations) but also the other way around, the participants affect the video by their varying and evolving personal and communicational motivations for recording.

Gamifying Video Object Segmentation.

Science.gov (United States)

Spampinato, Concetto; Palazzo, Simone; Giordano, Daniela

2017-10-01

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

Effect of MP4 Therapy Videos on Adherence to Voice Therapy Home Practice in Children With Dysphonia.

Science.gov (United States)

Braden, Maia N; van Leer, Eva

2017-01-01

Voice disorders in children are often treated with behavioral voice therapy, which requires home practice of exercises. Previous studies with adults demonstrated increased practice frequency when patients were given videos of a clinician and patient performing therapy tasks. The purpose of this study was to determine whether videos of practice exercises would increase adherence to therapy in children. The study used a randomized double crossover research design. Twenty-eight patients, aged 6-18, referred for voice therapy were included in the study. Two conditions were alternated on a weekly basis: standard-of-care therapy and standard-of-care therapy with video models added. Participants recorded practice frequency and participated in semi-structured interviews, which were analyzed for themes. Participants practiced an average of 1.79 times per day without videos and 1.72 with videos (P = 0.743), indicating no significant difference between conditions. There was also no age group effect (P = 0.314). Qualitative analysis of interview responses established the following themes: (1) I knew how to do my exercises, (2) I didn't like seeing/hearing myself, (3) Videos helped me remember to practice, (4) I didn't like the video player itself, (5) The videos didn't make a difference with practice, and (6) Practicing was no fun. Video models of therapy tasks do not appear to influence adherence to home practice frequency in children with voice disorders, in contrast to findings in adults. Videos were found useful by several participants as reminders to practice. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

XbD Video 2, Taxonomy of Experience (ToE) [Online

DEFF Research Database (Denmark)

2013-01-01

This is the second video in the Experience-based Designing series: It describes the Taxonomy of Experience, a structural way of looking at human experiences of almost any kind.This hierarchical model is useful to researchers and decision makers as a general method or tool for guiding the collection......, processing and categorisation of field data about an everyday experience. Researchers using this model often referred to the process as 'doing a ToE'...

A New Outlier Detection Method for Multidimensional Datasets

KAUST Repository

Abdel Messih, Mario A.

2012-07-01

This study develops a novel hybrid method for outlier detection (HMOD) that combines the idea of distance based and density based methods. The proposed method has two main advantages over most of the other outlier detection methods. The first advantage is that it works well on both dense and sparse datasets. The second advantage is that, unlike most other outlier detection methods that require careful parameter setting and prior knowledge of the data, HMOD is not very sensitive to small changes in parameter values within certain parameter ranges. The only required parameter to set is the number of nearest neighbors. In addition, we made a fully parallelized implementation of HMOD that made it very efficient in applications. Moreover, we proposed a new way of using the outlier detection for redundancy reduction in datasets where the confidence level that evaluates how accurate the less redundant dataset can be used to represent the original dataset can be specified by users. HMOD is evaluated on synthetic datasets (dense and mixed “dense and sparse”) and a bioinformatics problem of redundancy reduction of dataset of position weight matrices (PWMs) of transcription factor binding sites. In addition, in the process of assessing the performance of our redundancy reduction method, we developed a simple tool that can be used to evaluate the confidence level of reduced dataset representing the original dataset. The evaluation of the results shows that our method can be used in a wide range of problems.

Computer-based video analysis identifies infants with absence of fidgety movements.

Science.gov (United States)

Støen, Ragnhild; Songstad, Nils Thomas; Silberg, Inger Elisabeth; Fjørtoft, Toril; Jensenius, Alexander Refsum; Adde, Lars

2017-10-01

BackgroundAbsence of fidgety movements (FMs) at 3 months' corrected age is a strong predictor of cerebral palsy (CP) in high-risk infants. This study evaluates the association between computer-based video analysis and the temporal organization of FMs assessed with the General Movement Assessment (GMA).MethodsInfants were eligible for this prospective cohort study if referred to a high-risk follow-up program in a participating hospital. Video recordings taken at 10-15 weeks post term age were used for GMA and computer-based analysis. The variation of the spatial center of motion, derived from differences between subsequent video frames, was used for quantitative analysis.ResultsOf 241 recordings from 150 infants, 48 (24.1%) were classified with absence of FMs or sporadic FMs using the GMA. The variation of the spatial center of motion (C SD ) during a recording was significantly lower in infants with normal (0.320; 95% confidence interval (CI) 0.309, 0.330) vs. absence of or sporadic (0.380; 95% CI 0.361, 0.398) FMs (P<0.001). A triage model with C SD thresholds chosen for sensitivity of 90% and specificity of 80% gave a 40% referral rate for GMA.ConclusionQuantitative video analysis during the FMs' period can be used to triage infants at high risk of CP to early intervention or observational GMA.

Making of a solar spectral irradiance dataset I: observations, uncertainties, and methods

Directory of Open Access Journals (Sweden)

Schöll Micha

2016-01-01

Full Text Available Context. Changes in the spectral solar irradiance (SSI are a key driver of the variability of the Earth’s environment, strongly affecting the upper atmosphere, but also impacting climate. However, its measurements have been sparse and of different quality. The “First European Comprehensive Solar Irradiance Data Exploitation project” (SOLID aims at merging the complete set of European irradiance data, complemented by archive data that include data from non-European missions. Aims. As part of SOLID, we present all available space-based SSI measurements, reference spectra, and relevant proxies in a unified format with regular temporal re-gridding, interpolation, gap-filling as well as associated uncertainty estimations. Methods. We apply a coherent methodology to all available SSI datasets. Our pipeline approach consists of the pre-processing of the data, the interpolation of missing data by utilizing the spectral coherency of SSI, the temporal re-gridding of the data, an instrumental outlier detection routine, and a proxy-based interpolation for missing and flagged values. In particular, to detect instrumental outliers, we combine an autoregressive model with proxy data. We independently estimate the precision and stability of each individual dataset and flag all changes due to processing in an accompanying quality mask. Results. We present a unified database of solar activity records with accompanying meta-data and uncertainties. Conclusions. This dataset can be used for further investigations of the long-term trend of solar activity and the construction of a homogeneous SSI record.

Experimental video signals distribution MMF network based on IEEE 802.11 standard

Science.gov (United States)

Kowalczyk, Marcin; Maksymiuk, Lukasz; Siuzdak, Jerzy

2014-11-01

The article was focused on presentation the achievements in a scope of experimental research on transmission of digital video streams in the frame of specially realized for this purpose ROF (Radio over Fiber) network. Its construction was based on the merge of wireless IEEE 802.11 network, popularly referred as Wi-Fi, with a passive optical network PON based on multimode fibers MMF. The proposed approach can constitute interesting proposal in area of solutions in the scope of the systems monitoring extensive, within which is required covering of a large area with ensuring of a relatively high degree of immunity on the interferences transmitted signals from video IP cameras to the monitoring center and a high configuration flexibility (easily change the deployment of cameras) of such network.

CONTEXT-BASED URBAN TERRAIN RECONSTRUCTION FROM UAV-VIDEOS FOR GEOINFORMATION APPLICATIONS

Directory of Open Access Journals (Sweden)

D. Bulatov

2012-09-01

Full Text Available Urban terrain reconstruction has many applications in areas of civil engineering, urban planning, surveillance and defense research. Therefore the needs of covering ad-hoc demand and performing a close-range urban terrain reconstruction with miniaturized and relatively inexpensive sensor platforms are constantly growing. Using (miniaturized unmanned aerial vehicles, (MUAVs, represents one of the most attractive alternatives to conventional large-scale aerial imagery. We cover in this paper a four-step procedure of obtaining georeferenced 3D urban models from video sequences. The four steps of the procedure – orientation, dense reconstruction, urban terrain modeling and geo-referencing – are robust, straight-forward, and nearly fully-automatic. The two last steps – namely, urban terrain modeling from almost-nadir videos and co-registration of models 6ndash; represent the main contribution of this work and will therefore be covered with more detail. The essential substeps of the third step include digital terrain model (DTM extraction, segregation of buildings from vegetation, as well as instantiation of building and tree models. The last step is subdivided into quasi- intrasensorial registration of Euclidean reconstructions and intersensorial registration with a geo-referenced orthophoto. Finally, we present reconstruction results from a real data-set and outline ideas for future work.

NP-PAH Interaction Dataset

Data.gov (United States)

U.S. Environmental Protection Agency — Dataset presents concentrations of organic pollutants, such as polyaromatic hydrocarbon compounds, in water samples. Water samples of known volume and concentration...

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.

A dataset on tail risk of commodities markets.

Science.gov (United States)

Powell, Robert J; Vo, Duc H; Pham, Thach N; Singh, Abhay K

2017-12-01

This article contains the datasets related to the research article "The long and short of commodity tails and their relationship to Asian equity markets"(Powell et al., 2017) [1]. The datasets contain the daily prices (and price movements) of 24 different commodities decomposed from the S&P GSCI index and the daily prices (and price movements) of three share market indices including World, Asia, and South East Asia for the period 2004-2015. Then, the dataset is divided into annual periods, showing the worst 5% of price movements for each year. The datasets are convenient to examine the tail risk of different commodities as measured by Conditional Value at Risk (CVaR) as well as their changes over periods. The datasets can also be used to investigate the association between commodity markets and share markets.

Spreading the cult body on YouTube: A case study of "Telephone" derivative videos

Directory of Open Access Journals (Sweden)

Agnese Vellar

2012-03-01

Full Text Available This case study of spreadability analyzes the Lady Gaga music video "Telephone," which has been appropriated and reworked by YouTube users sharing derivative works online. What properties of the music video stimulate user appropriation? What hybrid audiovisual forms are emerging from its reworking by users? In order to answer these questions, between January and August 2010, I conducted participant observation on Lady Gaga's official social network profiles and collected 70 "Telephone" derivative videos on YouTube. I identified three main categories of video creativity: (1 music (which includes covers, "me singing" videos, music mashups, and choreography; (2 parody (in which YouTube users and comedians humorously imitate Gaga, creating spoofs; and (3 fashion (in which makeup artists and amateurs appropriate the star's image to create makeup and hair tutorials. "Telephone" has become spreadable because it integrates dance music and choreography, costume changes, cinematic references, and product placements that work as textual hooks meaningful to different target markets: live music, dance, chick, and postmodern cinematic cultures. In particular, Gaga is a cult body that explicitly incorporates previous cinematic and pop music icons. Users are stimulated to reenact Gaga's cult body online. On YouTube, spreadability is thus strictly related to the appropriation of cult bodies. Fans, comedians, independent musicians, fashionistas, and pop stars construct their own cult bodies by deliberately borrowing characteristics from previous media icons and reenacting them in online videos in order to fulfill their expressive and professional needs.

ASSESSMENT OF BOTTOM-OF-ATMOSPHERE REFLECTANCE IN LIDAR DATA AS REFERENCE FOR HYPERSPECTRAL IMAGERY

Directory of Open Access Journals (Sweden)

A. Roncat

2017-09-01

Full Text Available While airborne lidar has confirmed its leading role in delivering high-resolution 3D topographic information during the last decade, its radiometric potential has not yet been fully exploited. However, with the increasing availability of commercial lidar systems which (a make use of full-waveform information and (b operate at several wavelengths simultaneously, this potential is increasing as well. Radiometric calibration of the full-waveform information mentioned before allows for the derivation of physical target surface parameters such as the backscatter coefficient and a diffuse reflectance value at bottom of atmosphere (BOA, i.e. the target surface. With lidar being an active remote sensing technique, these parameters can be derived from lidar data itself, accompanied by the measurement or estimation of reference data for diffuse reflectance. In contrast to this, such a radiometric calibration for passive hyperspectral imagery (HSI requires the knowledge and/or estimation of much more unknowns. However, in case of corresponding wavelength(s radiometrically calibrated lidar datasets can deliver an areawide reference for BOA reflectance. This paper presents criteria to check where the assumption of diffuse BOA reflectance behaviour is fulfilled and how these criteria are assessed in lidar data; the assessment is illustrated by an extended lidar dataset. Moreover, for this lidar dataset and an HSI dataset recorded over the same area, the corresponding reflectance values are compared for different surface types.

Medical video server construction.

Science.gov (United States)

Dańda, Jacek; Juszkiewicz, Krzysztof; Leszczuk, Mikołaj; Loziak, Krzysztof; Papir, Zdzisław; Sikora, Marek; Watza, Rafal

2003-01-01

The paper discusses two implementation options for a Digital Video Library, a repository used for archiving, accessing, and browsing of video medical records. Two crucial issues to be decided on are a video compression format and a video streaming platform. The paper presents numerous decision factors that have to be taken into account. The compression formats being compared are DICOM as a format representative for medical applications, both MPEGs, and several new formats targeted for an IP networking. The comparison includes transmission rates supported, compression rates, and at least options for controlling a compression process. The second part of the paper presents the ISDN technique as a solution for provisioning of tele-consultation services between medical parties that are accessing resources uploaded to a digital video library. There are several backbone techniques (like corporate LANs/WANs, leased lines or even radio/satellite links) available, however, the availability of network resources for hospitals was the prevailing choice criterion pointing to ISDN solutions. Another way to provide access to the Digital Video Library is based on radio frequency domain solutions. The paper describes possibilities of both, wireless and cellular network's data transmission service to be used as a medical video server transport layer. For the cellular net-work based solution two communication techniques are used: Circuit Switched Data and Packet Switched Data.

Image processing of integrated video image obtained with a charged-particle imaging video monitor system

International Nuclear Information System (INIS)

Iida, Takao; Nakajima, Takehiro

1988-01-01

A new type of charged-particle imaging video monitor system was constructed for video imaging of the distributions of alpha-emitting and low-energy beta-emitting nuclides. The system can display not only the scintillation image due to radiation on the video monitor but also the integrated video image becoming gradually clearer on another video monitor. The distortion of the image is about 5% and the spatial resolution is about 2 line pairs (lp)mm -1 . The integrated image is transferred to a personal computer and image processing is performed qualitatively and quantitatively. (author)

NEI You Tube Videos: Amblyopia

Medline Plus

Full Text Available ... YouTube Videos: Amblyopia Embedded video for NEI YouTube Videos: Amblyopia ... *PDF files require the free Adobe® Reader® software for viewing. This website is maintained by the ...

Smart Streaming for Online Video Services

OpenAIRE

Chen, Liang; Zhou, Yipeng; Chiu, Dah Ming

2013-01-01

Bandwidth consumption is a significant concern for online video service providers. Practical video streaming systems usually use some form of HTTP streaming (progressive download) to let users download the video at a faster rate than the video bitrate. Since users may quit before viewing the complete video, however, much of the downloaded video will be "wasted". To the extent that users' departure behavior can be predicted, we develop smart streaming that can be used to improve user QoE with ...

Video outside versus video inside the web: do media setting and image size have an impact on the emotion-evoking potential of video?

NARCIS (Netherlands)

Verleur, R.; Verhagen, Pleunes Willem; Crawford, Margaret; Simonson, Michael; Lamboy, Carmen

2001-01-01

To explore the educational potential of video-evoked affective responses in a Web-based environment, the question was raised whether video in a Web-based environment is experienced differently from video in a traditional context. An experiment was conducted that studied the affect-evoking power of

Video games: good, bad, or other?

Science.gov (United States)

Prot, Sara; McDonald, Katelyn A; Anderson, Craig A; Gentile, Douglas A

2012-06-01

Video games are a pervasive pastime among children and adolescents. The growing popularity of video games has instigated a debate among parents, researchers, video game producers, and policymakers concerning potential harmful and helpful effects of video games on children. This article provides an overview of research findings on the positive and negative effects of video games, thus providing an empirical answer to the question, are video games good or bad? The article also provides some guidelines to help pediatricians, parents, and other caregivers protect children from negative effects and to maximize positive effects of video games. Copyright © 2012 Elsevier Inc. All rights reserved.

Facial Expression Recognition from Video Sequences Based on Spatial-Temporal Motion Local Binary Pattern and Gabor Multiorientation Fusion Histogram

Directory of Open Access Journals (Sweden)

Lei Zhao

2017-01-01

Full Text Available This paper proposes novel framework for facial expressions analysis using dynamic and static information in video sequences. First, based on incremental formulation, discriminative deformable face alignment method is adapted to locate facial points to correct in-plane head rotation and break up facial region from background. Then, spatial-temporal motion local binary pattern (LBP feature is extracted and integrated with Gabor multiorientation fusion histogram to give descriptors, which reflect static and dynamic texture information of facial expressions. Finally, a one-versus-one strategy based multiclass support vector machine (SVM classifier is applied to classify facial expressions. Experiments on Cohn-Kanade (CK + facial expression dataset illustrate that integrated framework outperforms methods using single descriptors. Compared with other state-of-the-art methods on CK+, MMI, and Oulu-CASIA VIS datasets, our proposed framework performs better.

Proteomics dataset

DEFF Research Database (Denmark)

Bennike, Tue Bjerg; Carlsen, Thomas Gelsing; Ellingsen, Torkell

2017-01-01

patients (Morgan et al., 2012; Abraham and Medzhitov, 2011; Bennike, 2014) [8–10. Therefore, we characterized the proteome of colon mucosa biopsies from 10 inflammatory bowel disease ulcerative colitis (UC) patients, 11 gastrointestinal healthy rheumatoid arthritis (RA) patients, and 10 controls. We...... been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001608 for ulcerative colitis and control samples, and PXD003082 for rheumatoid arthritis samples....

Hierarchical event selection for video storyboards with a case study on snooker video visualization.

Science.gov (United States)

Parry, Matthew L; Legg, Philip A; Chung, David H S; Griffiths, Iwan W; Chen, Min

2011-12-01

Video storyboard, which is a form of video visualization, summarizes the major events in a video using illustrative visualization. There are three main technical challenges in creating a video storyboard, (a) event classification, (b) event selection and (c) event illustration. Among these challenges, (a) is highly application-dependent and requires a significant amount of application specific semantics to be encoded in a system or manually specified by users. This paper focuses on challenges (b) and (c). In particular, we present a framework for hierarchical event representation, and an importance-based selection algorithm for supporting the creation of a video storyboard from a video. We consider the storyboard to be an event summarization for the whole video, whilst each individual illustration on the board is also an event summarization but for a smaller time window. We utilized a 3D visualization template for depicting and annotating events in illustrations. To demonstrate the concepts and algorithms developed, we use Snooker video visualization as a case study, because it has a concrete and agreeable set of semantic definitions for events and can make use of existing techniques of event detection and 3D reconstruction in a reliable manner. Nevertheless, most of our concepts and algorithms developed for challenges (b) and (c) can be applied to other application areas. © 2010 IEEE

Intelligent keyframe extraction for video printing

Science.gov (United States)

Zhang, Tong

2004-10-01

Nowadays most digital cameras have the functionality of taking short video clips, with the length of video ranging from several seconds to a couple of minutes. The purpose of this research is to develop an algorithm which extracts an optimal set of keyframes from each short video clip so that the user could obtain proper video frames to print out. In current video printing systems, keyframes are normally obtained by evenly sampling the video clip over time. Such an approach, however, may not reflect highlights or regions of interest in the video. Keyframes derived in this way may also be improper for video printing in terms of either content or image quality. In this paper, we present an intelligent keyframe extraction approach to derive an improved keyframe set by performing semantic analysis of the video content. For a video clip, a number of video and audio features are analyzed to first generate a candidate keyframe set. These features include accumulative color histogram and color layout differences, camera motion estimation, moving object tracking, face detection and audio event detection. Then, the candidate keyframes are clustered and evaluated to obtain a final keyframe set. The objective is to automatically generate a limited number of keyframes to show different views of the scene; to show different people and their actions in the scene; and to tell the story in the video shot. Moreover, frame extraction for video printing, which is a rather subjective problem, is considered in this work for the first time, and a semi-automatic approach is proposed.

3D video-based deformation measurement of the pelvis bone under dynamic cyclic loading

Directory of Open Access Journals (Sweden)

Freslier Marie

2011-07-01

Full Text Available Abstract Background Dynamic three-dimensional (3D deformation of the pelvic bones is a crucial factor in the successful design and longevity of complex orthopaedic oncological implants. The current solutions are often not very promising for the patient; thus it would be interesting to measure the dynamic 3D-deformation of the whole pelvic bone in order to get a more realistic dataset for a better implant design. Therefore we hypothesis if it would be possible to combine a material testing machine with a 3D video motion capturing system, used in clinical gait analysis, to measure the sub millimetre deformation of a whole pelvis specimen. Method A pelvis specimen was placed in a standing position on a material testing machine. Passive reflective markers, traceable by the 3D video motion capturing system, were fixed to the bony surface of the pelvis specimen. While applying a dynamic sinusoidal load the 3D-movement of the markers was recorded by the cameras and afterwards the 3D-deformation of the pelvis specimen was computed. The accuracy of the 3D-movement of the markers was verified with 3D-displacement curve with a step function using a manual driven 3D micro-motion-stage. Results The resulting accuracy of the measurement system depended on the number of cameras tracking a marker. The noise level for a marker seen by two cameras was during the stationary phase of the calibration procedure ± 0.036 mm, and ± 0.022 mm if tracked by 6 cameras. The detectable 3D-movement performed by the 3D-micro-motion-stage was smaller than the noise level of the 3D-video motion capturing system. Therefore the limiting factor of the setup was the noise level, which resulted in a measurement accuracy for the dynamic test setup of ± 0.036 mm. Conclusion This 3D test setup opens new possibilities in dynamic testing of wide range materials, like anatomical specimens, biomaterials, and its combinations. The resulting 3D-deformation dataset can be used for a better

Comparison of Shallow Survey 2012 Multibeam Datasets

Science.gov (United States)

Ramirez, T. M.

2012-12-01

The purpose of the Shallow Survey common dataset is a comparison of the different technologies utilized for data acquisition in the shallow survey marine environment. The common dataset consists of a series of surveys conducted over a common area of seabed using a variety of systems. It provides equipment manufacturers the opportunity to showcase their latest systems while giving hydrographic researchers and scientists a chance to test their latest algorithms on the dataset so that rigorous comparisons can be made. Five companies collected data for the Common Dataset in the Wellington Harbor area in New Zealand between May 2010 and May 2011; including Kongsberg, Reson, R2Sonic, GeoAcoustics, and Applied Acoustics. The Wellington harbor and surrounding coastal area was selected since it has a number of well-defined features, including the HMNZS South Seas and HMNZS Wellington wrecks, an armored seawall constructed of Tetrapods and Akmons, aquifers, wharves and marinas. The seabed inside the harbor basin is largely fine-grained sediment, with gravel and reefs around the coast. The area outside the harbor on the southern coast is an active environment, with moving sand and exposed reefs. A marine reserve is also in this area. For consistency between datasets, the coastal research vessel R/V Ikatere and crew were used for all surveys conducted for the common dataset. Using Triton's Perspective processing software multibeam datasets collected for the Shallow Survey were processed for detail analysis. Datasets from each sonar manufacturer were processed using the CUBE algorithm developed by the Center for Coastal and Ocean Mapping/Joint Hydrographic Center (CCOM/JHC). Each dataset was gridded at 0.5 and 1.0 meter resolutions for cross comparison and compliance with International Hydrographic Organization (IHO) requirements. Detailed comparisons were made of equipment specifications (transmit frequency, number of beams, beam width), data density, total uncertainty, and

National Hydrography Dataset (NHD)

Data.gov (United States)

Kansas Data Access and Support Center — The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that comprise the...

Surgeon-Manipulated Live Surgery Video Recording Apparatuses: Personal Experience and Review of Literature.

Science.gov (United States)

Kapi, Emin

2017-06-01

Visual recording of surgical procedures is a method that is used quite frequently in practices of plastic surgery. While presentations containing photographs are quite common in education seminars and congresses, video-containing presentations find more favour. For this reason, the presentation of surgical procedures in the form of real-time video display has increased especially recently. Appropriate technical equipment for video recording is not available in most hospitals, so there is a need to set up external apparatus in the operating room. Among these apparatuses can be listed such options as head-mounted video cameras, chest-mounted cameras, and tripod-mountable cameras. The head-mounted video camera is an apparatus that is capable of capturing high-resolution and detailed close-up footage. The tripod-mountable camera enables video capturing from a fixed point. Certain user-specific modifications can be made to overcome some of these restrictions. Among these modifications, custom-made applications are one of the most effective solutions. The article makes an attempt to present the features and experiences concerning the use of a combination of a head- or chest-mounted action camera, a custom-made portable tripod apparatus of versatile features, and an underwater camera. The descriptions we used are quite easy-to-assembly, quickly installed, and inexpensive apparatuses that do not require specific technical knowledge and can be manipulated by the surgeon personally in all procedures. The author believes that video recording apparatuses will be integrated more to the operating room, become a standard practice, and become more enabling for self-manipulation by the surgeon in the near future. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Rheumatoid Arthritis Educational Video Series

Medline Plus

Full Text Available ... Patient Webcasts / Rheumatoid Arthritis Educational Video Series Rheumatoid Arthritis Educational Video Series This series of five videos ... member of our patient care team. Managing Your Arthritis Managing Your Arthritis Managing Chronic Pain and Depression ...

Rheumatoid Arthritis Educational Video Series

Science.gov (United States)

... Corner / Patient Webcasts / Rheumatoid Arthritis Educational Video Series Rheumatoid Arthritis Educational Video Series This series of five videos ... Your Arthritis Managing Chronic Pain and Depression in Arthritis Nutrition & Rheumatoid Arthritis Arthritis and Health-related Quality of Life ...

Video game addiction: The push to pathologize video games

DEFF Research Database (Denmark)

Nielsen, Rune Kristian Lundedal; Ferguson, Christopher; Bean, Anthony

2017-01-01

With proposals to include “gaming disorder” in both the Diagnostic and Statistical Manual (DSM) and International Compendium of Diseases (ICD), the concept of video game addiction has gained traction. However, many aspects of this concept remain controversial. At present, little clarity has been...... achieved regarding diagnostic criteria and appropriate symptoms. It is unclear if symptoms that involve problematic video gaming behavior should be reified as a new disorder, or are the expression of underlying mental conditions. Nonetheless, the recent proposals around gaming disorder from respected...... and necessity of the overarching construct. This raises multiple concerns. First, the current approaches to understanding “gaming addiction” are rooted in substance abuse research and approaches do not necessarily translate to media consumption. Second, some research has indicated that “video game addiction...

The Harvard organic photovoltaic dataset.

Science.gov (United States)

Lopez, Steven A; Pyzer-Knapp, Edward O; Simm, Gregor N; Lutzow, Trevor; Li, Kewei; Seress, Laszlo R; Hachmann, Johannes; Aspuru-Guzik, Alán

2016-09-27

The Harvard Organic Photovoltaic Dataset (HOPV15) presented in this work is a collation of experimental photovoltaic data from the literature, and corresponding quantum-chemical calculations performed over a range of conformers, each with quantum chemical results using a variety of density functionals and basis sets. It is anticipated that this dataset will be of use in both relating electronic structure calculations to experimental observations through the generation of calibration schemes, as well as for the creation of new semi-empirical methods and the benchmarking of current and future model chemistries for organic electronic applications.

Video game use and cognitive performance: does it vary with the presence of problematic video game use?

Science.gov (United States)

Collins, Emily; Freeman, Jonathan

2014-03-01

Action video game players have been found to outperform nonplayers on a variety of cognitive tasks. However, several failures to replicate these video game player advantages have indicated that this relationship may not be straightforward. Moreover, despite the discovery that problematic video game players do not appear to demonstrate the same superior performance as nonproblematic video game players in relation to multiple object tracking paradigms, this has not been investigated for other tasks. Consequently, this study compared gamers and nongamers in task switching ability, visual short-term memory, mental rotation, enumeration, and flanker interference, as well as investigated the influence of self-reported problematic video game use. A total of 66 participants completed the experiment, 26 of whom played action video games, including 20 problematic players. The results revealed no significant effect of playing action video games, nor any influence of problematic video game play. This indicates that the previously reported cognitive advantages in video game players may be restricted to specific task features or samples. Furthermore, problematic video game play may not have a detrimental effect on cognitive performance, although this is difficult to ascertain considering the lack of video game player advantage. More research is therefore sorely needed.

Video frame processor

International Nuclear Information System (INIS)

Joshi, V.M.; Agashe, Alok; Bairi, B.R.

1993-01-01

This report provides technical description regarding the Video Frame Processor (VFP) developed at Bhabha Atomic Research Centre. The instrument provides capture of video images available in CCIR format. Two memory planes each with a capacity of 512 x 512 x 8 bit data enable storage of two video image frames. The stored image can be processed on-line and on-line image subtraction can also be carried out for image comparisons. The VFP is a PC Add-on board and is I/O mapped within the host IBM PC/AT compatible computer. (author). 9 refs., 4 figs., 19 photographs

Visual Analytics and Storytelling through Video

Energy Technology Data Exchange (ETDEWEB)

Wong, Pak C.; Perrine, Kenneth A.; Mackey, Patrick S.; Foote, Harlan P.; Thomas, Jim

2005-10-31

This paper supplements a video clip submitted to the Video Track of IEEE Symposium on Information Visualization 2005. The original video submission applies a two-way storytelling approach to demonstrate the visual analytics capabilities of a new visualization technique. The paper presents our video production philosophy, describes the plot of the video, explains the rationale behind the plot, and finally, shares our production experiences with our readers.

The good, the bad and the ugly: a meta-analytic review of positive and negative effects of violent video games.

Science.gov (United States)

Ferguson, Christopher John

2007-12-01

Video game violence has become a highly politicized issue for scientists and the general public. There is continuing concern that playing violent video games may increase the risk of aggression in players. Less often discussed is the possibility that playing violent video games may promote certain positive developments, particularly related to visuospatial cognition. The objective of the current article was to conduct a meta-analytic review of studies that examine the impact of violent video games on both aggressive behavior and visuospatial cognition in order to understand the full impact of such games. A detailed literature search was used to identify peer-reviewed articles addressing violent video game effects. Effect sizes r (a common measure of effect size based on the correlational coefficient) were calculated for all included studies. Effect sizes were adjusted for observed publication bias. Results indicated that publication bias was a problem for studies of both aggressive behavior and visuospatial cognition. Once corrected for publication bias, studies of video game violence provided no support for the hypothesis that violent video game playing is associated with higher aggression. However playing violent video games remained related to higher visuospatial cognition (r (x) = 0.36). Results from the current analysis did not support the conclusion that violent video game playing leads to aggressive behavior. However, violent video game playing was associated with higher visuospatial cognition. It may be advisable to reframe the violent video game debate in reference to potential costs and benefits of this medium.

NEI You Tube Videos: Amblyopia

Medline Plus

Full Text Available ... questions Clinical Studies Publications Catalog Photos and Images Spanish Language Information Grants and Funding Extramural Research Division ... Low Vision Refractive Errors Retinopathy of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded video ...

Interactive Video, The Next Step

Science.gov (United States)

Strong, L. R.; Wold-Brennon, R.; Cooper, S. K.; Brinkhuis, D.

2012-12-01

Video has the ingredients to reach us emotionally - with amazing images, enthusiastic interviews, music, and video game-like animations-- and it's emotion that motivates us to learn more about our new interest. However, watching video is usually passive. New web-based technology is expanding and enhancing the video experience, creating opportunities to use video with more direct interaction. This talk will look at an Educaton and Outreach team's experience producing video-centric curriculum using innovative interactive media tools from TED-Ed and FlixMaster. The Consortium for Ocean Leadership's Deep Earth Academy has partnered with the Center for Dark Energy Biosphere Investigations (C-DEBI) to send educators and a video producer aboard three deep sea research expeditions to the Juan de Fuca plate to install and service sub-seafloor observatories. This collaboration between teachers, students, scientists and media producers has proved a productive confluence, providing new ways of understanding both ground-breaking science and the process of science itself - by experimenting with new ways to use multimedia during ocean-going expeditions and developing curriculum and other projects post-cruise.

Real-time video quality monitoring

Science.gov (United States)

Liu, Tao; Narvekar, Niranjan; Wang, Beibei; Ding, Ran; Zou, Dekun; Cash, Glenn; Bhagavathy, Sitaram; Bloom, Jeffrey

2011-12-01

The ITU-T Recommendation G.1070 is a standardized opinion model for video telephony applications that uses video bitrate, frame rate, and packet-loss rate to measure the video quality. However, this model was original designed as an offline quality planning tool. It cannot be directly used for quality monitoring since the above three input parameters are not readily available within a network or at the decoder. And there is a great room for the performance improvement of this quality metric. In this article, we present a real-time video quality monitoring solution based on this Recommendation. We first propose a scheme to efficiently estimate the three parameters from video bitstreams, so that it can be used as a real-time video quality monitoring tool. Furthermore, an enhanced algorithm based on the G.1070 model that provides more accurate quality prediction is proposed. Finally, to use this metric in real-world applications, we present an example emerging application of real-time quality measurement to the management of transmitted videos, especially those delivered to mobile devices.

Collaborative Video Search Combining Video Retrieval with Human-Based Visual Inspection

NARCIS (Netherlands)

Hudelist, M.A.; Cobârzan, C.; Beecks, C.; van de Werken, Rob; Kletz, S.; Hürst, W.O.; Schoeffmann, K.

2016-01-01

We propose a novel video browsing approach that aims at optimally integrating traditional, machine-based retrieval methods with an interface design optimized for human browsing performance. Advanced video retrieval and filtering (e.g., via color and motion signatures, and visual concepts) on a

76 FR 55585 - Video Description: Implementation of the Twenty-First Century Communications and Video...

Science.gov (United States)

2011-09-08

... of Video Programming Report and Order (15 F.C.C.R. 15,230 (2000)), recon. granted in part and denied... dialogue, makes video programming more accessible to individuals who are blind or visually impaired. The... networks, and multichannel video programming distributor systems (``MVPDs'') with more than 50,000...

Tables and figure datasets

Data.gov (United States)

U.S. Environmental Protection Agency — Soil and air concentrations of asbestos in Sumas study. This dataset is associated with the following publication: Wroble, J., T. Frederick, A. Frame, and D....

Comparison of the Effects of Continuous Video Modeling, Video Prompting, and Video Modeling on Task Completion by Young Adults with Moderate Intellectual Disability

Science.gov (United States)

Mechling, Linda C.; Ayres, Kevin M.; Bryant, Kathryn J.; Foster, Ashley L.

2014-01-01

This study compared the effects of three procedures (video prompting: VP, video modeling: VM, and continuous video modeling: CVM) on task completion by three high school students with moderate intellectual disability. The comparison was made across three sets of fundamentally different tasks (putting away household items in clusters of two items;…

Rheumatoid Arthritis Educational Video Series

Medline Plus

Full Text Available ... Corner / Patient Webcasts / Rheumatoid Arthritis Educational Video Series Rheumatoid Arthritis Educational Video Series This series of five videos ... Your Arthritis Managing Chronic Pain and Depression in Arthritis Nutrition & Rheumatoid Arthritis Arthritis and Health-related Quality of Life ...

Atlantic small-mammal: a dataset of communities of rodents and marsupials of the Atlantic forests of South America.

Science.gov (United States)

Bovendorp, Ricardo S; Villar, Nacho; de Abreu-Junior, Edson F; Bello, Carolina; Regolin, André L; Percequillo, Alexandre R; Galetti, Mauro

2017-08-01

The contribution of small mammal ecology to the understanding of macroecological patterns of biodiversity, population dynamics, and community assembly has been hindered by the absence of large datasets of small mammal communities from tropical regions. Here we compile the largest dataset of inventories of small mammal communities for the Neotropical region. The dataset reviews small mammal communities from the Atlantic forest of South America, one of the regions with the highest diversity of small mammals and a global biodiversity hotspot, though currently covering less than 12% of its original area due to anthropogenic pressures. The dataset comprises 136 references from 300 locations covering seven vegetation types of tropical and subtropical Atlantic forests of South America, and presents data on species composition, richness, and relative abundance (captures/trap-nights). One paper was published more than 70 yr ago, but 80% of them were published after 2000. The dataset comprises 53,518 individuals of 124 species of small mammals, including 30 species of marsupials and 94 species of rodents. Species richness averaged 8.2 species (1-21) per site. Only two species occurred in more than 50% of the sites (the common opossum, Didelphis aurita and black-footed pigmy rice rat Oligoryzomys nigripes). Mean species abundance varied 430-fold, from 4.3 to 0.01 individuals/trap-night. The dataset also revealed a hyper-dominance of 22 species that comprised 78.29% of all individuals captured, with only seven species representing 44% of all captures. The information contained on this dataset can be applied in the study of macroecological patterns of biodiversity, communities, and populations, but also to evaluate the ecological consequences of fragmentation and defaunation, and predict disease outbreaks, trophic interactions and community dynamics in this biodiversity hotspot. © 2017 by the Ecological Society of America.

Social video content delivery

CERN Document Server

Wang, Zhi; Zhu, Wenwu

2016-01-01

This brief presents new architecture and strategies for distribution of social video content. A primary framework for socially-aware video delivery and a thorough overview of the possible approaches is provided. The book identifies the unique characteristics of socially-aware video access and social content propagation, revealing the design and integration of individual modules that are aimed at enhancing user experience in the social network context. The change in video content generation, propagation, and consumption for online social networks, has significantly challenged the traditional video delivery paradigm. Given the massive amount of user-generated content shared in online social networks, users are now engaged as active participants in the social ecosystem rather than as passive receivers of media content. This revolution is being driven further by the deep penetration of 3G/4G wireless networks and smart mobile devices that are seamlessly integrated with online social networking and media-sharing s...

Children's Video Games as Interactive Racialization

OpenAIRE

Martin, Cathlena

2008-01-01

Cathlena Martin explores in her paper "Children's Video Games as Interactive Racialization" selected children's video games. Martin argues that children's video games often act as reinforcement for the games' television and film counterparts and their racializing characteristics and features. In Martin's analysis the video games discussed represent media through which to analyze racial identities and ideologies. In making the case for positive female minority leads in children's video games, ...

Accuracy of microbial community diversity estimated by closed- and open-reference OTUs

Directory of Open Access Journals (Sweden)

Robert C. Edgar

2017-10-01

Full Text Available Next-generation sequencing of 16S ribosomal RNA is widely used to survey microbial communities. Sequences are typically assigned to Operational Taxonomic Units (OTUs. Closed- and open-reference OTU assignment matches reads to a reference database at 97% identity (closed, then clusters unmatched reads using a de novo method (open. Implementations of these methods in the QIIME package were tested on several mock community datasets with 20 strains using different sequencing technologies and primers. Richness (number of reported OTUs was often greatly exaggerated, with hundreds or thousands of OTUs generated on Illumina datasets. Between-sample diversity was also found to be highly exaggerated in many cases, with weighted Jaccard distances between identical mock samples often close to one, indicating very low similarity. Non-overlapping hyper-variable regions in 70% of species were assigned to different OTUs. On mock communities with Illumina V4 reads, 56% to 88% of predicted genus names were false positives. Biological inferences obtained using these methods are therefore not reliable.

Novel Intermode Prediction Algorithm for High Efficiency Video Coding Encoder

Directory of Open Access Journals (Sweden)

Chan-seob Park

2014-01-01

Full Text Available The joint collaborative team on video coding (JCT-VC is developing the next-generation video coding standard which is called high efficiency video coding (HEVC. In the HEVC, there are three units in block structure: coding unit (CU, prediction unit (PU, and transform unit (TU. The CU is the basic unit of region splitting like macroblock (MB. Each CU performs recursive splitting into four blocks with equal size, starting from the tree block. In this paper, we propose a fast CU depth decision algorithm for HEVC technology to reduce its computational complexity. In 2N×2N PU, the proposed method compares the rate-distortion (RD cost and determines the depth using the compared information. Moreover, in order to speed up the encoding time, the efficient merge SKIP detection method is developed additionally based on the contextual mode information of neighboring CUs. Experimental result shows that the proposed algorithm achieves the average time-saving factor of 44.84% in the random access (RA at Main profile configuration with the HEVC test model (HM 10.0 reference software. Compared to HM 10.0 encoder, a small BD-bitrate loss of 0.17% is also observed without significant loss of image quality.

Subjective Video Quality Assessment in H.264/AVC Video Coding Standard

Directory of Open Access Journals (Sweden)

Z. Miličević

2012-11-01

Full Text Available This paper seeks to provide an approach for subjective video quality assessment in the H.264/AVC standard. For this purpose a special software program for the subjective assessment of quality of all the tested video sequences is developed. It was developed in accordance with recommendation ITU-T P.910, since it is suitable for the testing of multimedia applications. The obtained results show that in the proposed selective intra prediction and optimized inter prediction algorithm there is a small difference in picture quality (signal-to-noise ratio between decoded original and modified video sequences.

Illusory control, gambling, and video gaming: an investigation of regular gamblers and video game players.

Science.gov (United States)

King, Daniel L; Ejova, Anastasia; Delfabbro, Paul H

2012-09-01

There is a paucity of empirical research examining the possible association between gambling and video game play. In two studies, we examined the association between video game playing, erroneous gambling cognitions, and risky gambling behaviour. One hundred and fifteen participants, including 65 electronic gambling machine (EGM) players and 50 regular video game players, were administered a questionnaire that examined video game play, gambling involvement, problem gambling, and beliefs about gambling. We then assessed each groups' performance on a computerised gambling task that involved real money. A post-game survey examined perceptions of the skill and chance involved in the gambling task. The results showed that video game playing itself was not significantly associated with gambling involvement or problem gambling status. However, among those persons who both gambled and played video games, video game playing was uniquely and significantly positively associated with the perception of direct control over chance-based gambling events. Further research is needed to better understand the nature of this association, as it may assist in understanding the impact of emerging digital gambling technologies.

PHYSICS PERFORMANCE AND DATASET (PPD)

CERN Multimedia

L. Silvestris

2013-01-01

The first part of the Long Shutdown period has been dedicated to the preparation of the samples for the analysis targeting the summer conferences. In particular, the 8 TeV data acquired in 2012, including most of the “parked datasets”, have been reconstructed profiting from improved alignment and calibration conditions for all the sub-detectors. A careful planning of the resources was essential in order to deliver the datasets well in time to the analysts, and to schedule the update of all the conditions and calibrations needed at the analysis level. The newly reprocessed data have undergone detailed scrutiny by the Dataset Certification team allowing to recover some of the data for analysis usage and further improving the certification efficiency, which is now at 91% of the recorded luminosity. With the aim of delivering a consistent dataset for 2011 and 2012, both in terms of conditions and release (53X), the PPD team is now working to set up a data re-reconstruction and a new MC pro...

Integrated Surface Dataset (Global)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Integrated Surface (ISD) Dataset (ISD) is composed of worldwide surface weather observations from over 35,000 stations, though the best spatial coverage is...

Aaron Journal article datasets

Data.gov (United States)

U.S. Environmental Protection Agency — All figures used in the journal article are in netCDF format. This dataset is associated with the following publication: Sims, A., K. Alapaty , and S. Raman....

Market Squid Ecology Dataset

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains ecological information collected on the major adult spawning and juvenile habitats of market squid off California and the US Pacific Northwest....

Video-Based Big Data Analytics in Cyberlearning

Science.gov (United States)

Wang, Shuangbao; Kelly, William

2017-01-01

In this paper, we present a novel system, inVideo, for video data analytics, and its use in transforming linear videos into interactive learning objects. InVideo is able to analyze video content automatically without the need for initial viewing by a human. Using a highly efficient video indexing engine we developed, the system is able to analyze…

Web Audio/Video Streaming Tool

Science.gov (United States)

Guruvadoo, Eranna K.

2003-01-01

In order to promote NASA-wide educational outreach program to educate and inform the public of space exploration, NASA, at Kennedy Space Center, is seeking efficient ways to add more contents to the web by streaming audio/video files. This project proposes a high level overview of a framework for the creation, management, and scheduling of audio/video assets over the web. To support short-term goals, the prototype of a web-based tool is designed and demonstrated to automate the process of streaming audio/video files. The tool provides web-enabled users interfaces to manage video assets, create publishable schedules of video assets for streaming, and schedule the streaming events. These operations are performed on user-defined and system-derived metadata of audio/video assets stored in a relational database while the assets reside on separate repository. The prototype tool is designed using ColdFusion 5.0.

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).

Mechanisms of video-game epilepsy.

Science.gov (United States)

Fylan, F; Harding, G F; Edson, A S; Webb, R M

1999-01-01

We aimed to elucidate the mechanisms underlying video-game epilepsy by comparing the flicker- and spatial-frequency ranges over which photic and pattern stimulation elicited photoparoxysmal responses in two different populations: (a) 25 patients with a history of seizures experienced while playing video games; and (b) 25 age- and medication-matched controls with a history of photosensitive epilepsy, but no history of video-game seizures. Abnormality ranges were determined by measuring photoparoxysmal EEG abnormalities as a function of the flicker frequency of patterned and diffuse intermittent photic stimulation (IPS) and the spatial frequency of patterns on a raster display. There was no significant difference between the groups in respect of the abnormality ranges elicited by patterned or diffuse IPS or by spatial patterns. When the groups were compared at one specific IPS frequency (-50 Hz), however, the flicker frequency of European television displays, the video-game patients were significantly more likely to be sensitive. The results suggest that video-game seizures are a manifestation of photosensitive epilepsy. The increased sensitivity of video-game patients to IPS at 50 Hz indicates that display flicker may underlie video-game seizures. The similarity in photic- and pattern-stimulation ranges over which abnormalities are elicited in video-game patients and controls suggests that all patients with photosensitive epilepsy may be predisposed toward video-game-induced seizures. Photosensitivity screening should therefore include assessment by using both IPS at 50 Hz and patterns displayed on a television or monitor with a 50-Hz frame rate.