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.

Film grain noise modeling in advanced video coding

Science.gov (United States)

Oh, Byung Tae; Kuo, C.-C. Jay; Sun, Shijun; Lei, Shawmin

2007-01-01

A new technique for film grain noise extraction, modeling and synthesis is proposed and applied to the coding of high definition video in this work. The film grain noise is viewed as a part of artistic presentation by people in the movie industry. On one hand, since the film grain noise can boost the natural appearance of pictures in high definition video, it should be preserved in high-fidelity video processing systems. On the other hand, video coding with film grain noise is expensive. It is desirable to extract film grain noise from the input video as a pre-processing step at the encoder and re-synthesize the film grain noise and add it back to the decoded video as a post-processing step at the decoder. Under this framework, the coding gain of the denoised video is higher while the quality of the final reconstructed video can still be well preserved. Following this idea, we present a method to remove film grain noise from image/video without distorting its original content. Besides, we describe a parametric model containing a small set of parameters to represent the extracted film grain noise. The proposed model generates the film grain noise that is close to the real one in terms of power spectral density and cross-channel spectral correlation. Experimental results are shown to demonstrate the efficiency of the proposed scheme.

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.

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.

A novel visual saliency detection method for infrared video sequences

Science.gov (United States)

Wang, Xin; Zhang, Yuzhen; Ning, Chen

2017-12-01

Infrared video applications such as target detection and recognition, moving target tracking, and so forth can benefit a lot from visual saliency detection, which is essentially a method to automatically localize the ;important; content in videos. In this paper, a novel visual saliency detection method for infrared video sequences is proposed. Specifically, for infrared video saliency detection, both the spatial saliency and temporal saliency are considered. For spatial saliency, we adopt a mutual consistency-guided spatial cues combination-based method to capture the regions with obvious luminance contrast and contour features. For temporal saliency, a multi-frame symmetric difference approach is proposed to discriminate salient moving regions of interest from background motions. Then, the spatial saliency and temporal saliency are combined to compute the spatiotemporal saliency using an adaptive fusion strategy. Besides, to highlight the spatiotemporal salient regions uniformly, a multi-scale fusion approach is embedded into the spatiotemporal saliency model. Finally, a Gestalt theory-inspired optimization algorithm is designed to further improve the reliability of the final saliency map. Experimental results demonstrate that our method outperforms many state-of-the-art saliency detection approaches for infrared videos under various backgrounds.

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.

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.

Efficient Use of Video for 3d Modelling of Cultural Heritage Objects

Science.gov (United States)

Alsadik, B.; Gerke, M.; Vosselman, G.

2015-03-01

Currently, there is a rapid development in the techniques of the automated image based modelling (IBM), especially in advanced structure-from-motion (SFM) and dense image matching methods, and camera technology. One possibility is to use video imaging to create 3D reality based models of cultural heritage architectures and monuments. Practically, video imaging is much easier to apply when compared to still image shooting in IBM techniques because the latter needs a thorough planning and proficiency. However, one is faced with mainly three problems when video image sequences are used for highly detailed modelling and dimensional survey of cultural heritage objects. These problems are: the low resolution of video images, the need to process a large number of short baseline video images and blur effects due to camera shake on a significant number of images. In this research, the feasibility of using video images for efficient 3D modelling is investigated. A method is developed to find the minimal significant number of video images in terms of object coverage and blur effect. This reduction in video images is convenient to decrease the processing time and to create a reliable textured 3D model compared with models produced by still imaging. Two experiments for modelling a building and a monument are tested using a video image resolution of 1920×1080 pixels. Internal and external validations of the produced models are applied to find out the final predicted accuracy and the model level of details. Related to the object complexity and video imaging resolution, the tests show an achievable average accuracy between 1 - 5 cm when using video imaging, which is suitable for visualization, virtual museums and low detailed documentation.

EFFICIENT USE OF VIDEO FOR 3D MODELLING OF CULTURAL HERITAGE OBJECTS

Directory of Open Access Journals (Sweden)

B. Alsadik

2015-03-01

Full Text Available Currently, there is a rapid development in the techniques of the automated image based modelling (IBM, especially in advanced structure-from-motion (SFM and dense image matching methods, and camera technology. One possibility is to use video imaging to create 3D reality based models of cultural heritage architectures and monuments. Practically, video imaging is much easier to apply when compared to still image shooting in IBM techniques because the latter needs a thorough planning and proficiency. However, one is faced with mainly three problems when video image sequences are used for highly detailed modelling and dimensional survey of cultural heritage objects. These problems are: the low resolution of video images, the need to process a large number of short baseline video images and blur effects due to camera shake on a significant number of images. In this research, the feasibility of using video images for efficient 3D modelling is investigated. A method is developed to find the minimal significant number of video images in terms of object coverage and blur effect. This reduction in video images is convenient to decrease the processing time and to create a reliable textured 3D model compared with models produced by still imaging. Two experiments for modelling a building and a monument are tested using a video image resolution of 1920×1080 pixels. Internal and external validations of the produced models are applied to find out the final predicted accuracy and the model level of details. Related to the object complexity and video imaging resolution, the tests show an achievable average accuracy between 1 – 5 cm when using video imaging, which is suitable for visualization, virtual museums and low detailed documentation.

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

Science.gov (United States)

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

2014-05-01

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

Dynamic Textures Modeling via Joint Video Dictionary Learning.

Science.gov (United States)

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

2017-04-06

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

Adherent Raindrop Modeling, Detectionand Removal in Video.

Science.gov (United States)

You, Shaodi; Tan, Robby T; Kawakami, Rei; Mukaigawa, Yasuhiro; Ikeuchi, Katsushi

2016-09-01

Raindrops adhered to a windscreen or window glass can significantly degrade the visibility of a scene. Modeling, detecting and removing raindrops will, therefore, benefit many computer vision applications, particularly outdoor surveillance systems and intelligent vehicle systems. In this paper, a method that automatically detects and removes adherent raindrops is introduced. The core idea is to exploit the local spatio-temporal derivatives of raindrops. To accomplish the idea, we first model adherent raindrops using law of physics, and detect raindrops based on these models in combination with motion and intensity temporal derivatives of the input video. Having detected the raindrops, we remove them and restore the images based on an analysis that some areas of raindrops completely occludes the scene, and some other areas occlude only partially. For partially occluding areas, we restore them by retrieving as much as possible information of the scene, namely, by solving a blending function on the detected partially occluding areas using the temporal intensity derivative. For completely occluding areas, we recover them by using a video completion technique. Experimental results using various real videos show the effectiveness of our method.

Enhance Video Film using Retnix method

Science.gov (United States)

Awad, Rasha; Al-Zuky, Ali A.; Al-Saleh, Anwar H.; Mohamad, Haidar J.

2018-05-01

An enhancement technique used to improve the studied video quality. Algorithms like mean and standard deviation are used as a criterion within this paper, and it applied for each video clip that divided into 80 images. The studied filming environment has different light intensity (315, 566, and 644Lux). This different environment gives similar reality to the outdoor filming. The outputs of the suggested algorithm are compared with the results before applying it. This method is applied into two ways: first, it is applied for the full video clip to get the enhanced film; second, it is applied for every individual image to get the enhanced image then compiler them to get the enhanced film. This paper shows that the enhancement technique gives good quality video film depending on a statistical method, and it is recommended to use it in different application.

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;…

Effective Educational Methods In Educational Video Games

OpenAIRE

Van Zyl, Abraham

2014-01-01

This thesis examines the teaching methods used in three successful educational video games with the goal to provide a concise, practical guide for the proper implementation of educational learning into video games. The main source for analysing the teaching methods of educational games in this thesis is James Paul Gee’s book What Video Games Have To Teach Us About Learning And Literacy (2004). Gee expresses 36 learning principles existing in good games (chapter 4.2). This ideology serves ...

Attention modeling for video quality assessment

DEFF Research Database (Denmark)

You, Junyong; Korhonen, Jari; Perkis, Andrew

2010-01-01

averaged spatiotemporal pooling. The local quality is derived from visual attention modeling and quality variations over frames. Saliency, motion, and contrast information are taken into account in modeling visual attention, which is then integrated into IQMs to calculate the local quality of a video frame...... average between the global quality and the local quality. Experimental results demonstrate that the combination of the global quality and local quality outperforms both sole global quality and local quality, as well as other quality models, in video quality assessment. In addition, the proposed video...... quality modeling algorithm can improve the performance of image quality metrics on video quality assessment compared to the normal averaged spatiotemporal pooling scheme....

Infrared video based gas leak detection method using modified FAST features

Science.gov (United States)

Wang, Min; Hong, Hanyu; Huang, Likun

2018-03-01

In order to detect the invisible leaking gas that is usually dangerous and easily leads to fire or explosion in time, many new technologies have arisen in the recent years, among which the infrared video based gas leak detection is widely recognized as a viable tool. However, all the moving regions of a video frame can be detected as leaking gas regions by the existing infrared video based gas leak detection methods, without discriminating the property of each detected region, e.g., a walking person in a video frame may be also detected as gas by the current gas leak detection methods.To solve this problem, we propose a novel infrared video based gas leak detection method in this paper, which is able to effectively suppress strong motion disturbances.Firstly, the Gaussian mixture model(GMM) is used to establish the background model.Then due to the observation that the shapes of gas regions are different from most rigid moving objects, we modify the Features From Accelerated Segment Test (FAST) algorithm and use the modified FAST (mFAST) features to describe each connected component. In view of the fact that the statistical property of the mFAST features extracted from gas regions is different from that of other motion regions, we propose the Pixel-Per-Points (PPP) condition to further select candidate connected components.Experimental results show that the algorithm is able to effectively suppress most strong motion disturbances and achieve real-time leaking gas detection.

Water surface modeling from a single viewpoint video.

Science.gov (United States)

Li, Chuan; Pickup, David; Saunders, Thomas; Cosker, Darren; Marshall, David; Hall, Peter; Willis, Philip

2013-07-01

We introduce a video-based approach for producing water surface models. Recent advances in this field output high-quality results but require dedicated capturing devices and only work in limited conditions. In contrast, our method achieves a good tradeoff between the visual quality and the production cost: It automatically produces a visually plausible animation using a single viewpoint video as the input. Our approach is based on two discoveries: first, shape from shading (SFS) is adequate to capture the appearance and dynamic behavior of the example water; second, shallow water model can be used to estimate a velocity field that produces complex surface dynamics. We will provide qualitative evaluation of our method and demonstrate its good performance across a wide range of scenes.

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

Science.gov (United States)

Mitra, Adway; Biswas, Soma; Bhattacharyya, Chiranjib

2017-03-01

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

Fast Appearance Modeling for Automatic Primary Video Object Segmentation.

Science.gov (United States)

Yang, Jiong; Price, Brian; Shen, Xiaohui; Lin, Zhe; Yuan, Junsong

2016-02-01

Automatic segmentation of the primary object in a video clip is a challenging problem as there is no prior knowledge of the primary object. Most existing techniques thus adapt an iterative approach for foreground and background appearance modeling, i.e., fix the appearance model while optimizing the segmentation and fix the segmentation while optimizing the appearance model. However, these approaches may rely on good initialization and can be easily trapped in local optimal. In addition, they are usually time consuming for analyzing videos. To address these limitations, we propose a novel and efficient appearance modeling technique for automatic primary video object segmentation in the Markov random field (MRF) framework. It embeds the appearance constraint as auxiliary nodes and edges in the MRF structure, and can optimize both the segmentation and appearance model parameters simultaneously in one graph cut. The extensive experimental evaluations validate the superiority of the proposed approach over the state-of-the-art methods, in both efficiency and effectiveness.

Does the Model Matter? Comparing Video Self-Modeling and Video Adult Modeling for Task Acquisition and Maintenance by Adolescents with Autism Spectrum Disorders

Science.gov (United States)

Cihak, David F.; Schrader, Linda

2009-01-01

The purpose of this study was to compare the effectiveness and efficiency of learning and maintaining vocational chain tasks using video self-modeling and video adult modeling instruction. Four adolescents with autism spectrum disorders were taught vocational and prevocational skills. Although both video modeling conditions were effective for…

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.

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.

The experiments and analysis of several selective video encryption methods

Science.gov (United States)

Zhang, Yue; Yang, Cheng; Wang, Lei

2013-07-01

This paper presents four methods for selective video encryption based on the MPEG-2 video compression,including the slices, the I-frames, the motion vectors, and the DCT coefficients. We use the AES encryption method for simulation experiment for the four methods on VS2010 Platform, and compare the video effects and the processing speed of each frame after the video encrypted. The encryption depth can be arbitrarily selected, and design the encryption depth by using the double limit counting method, so the accuracy can be increased.

When Video Games Tell Stories: A Model of Video Game Narrative Architectures

Directory of Open Access Journals (Sweden)

Marcello Arnaldo Picucci

2014-11-01

Full Text Available In the present study a model is proposed offering a comprehensive categorization of video game narrative structures intended as the methods and techniques used by game designers and allowed by the medium to deliver the story content throughout the gameplay in collaboration with the players. A case is first made for the presence of narrative in video games and its growth of importance as a central component in game design. An in-depth analysis ensues focusing on how games tell stories, guided by the criteria of linearity/nonlinearity, interactivity and randomness. Light is shed upon the fundamental architectures through which stories are told as well as the essential boundaries posed by the close link between narrative and game AI.

Sub-component modeling for face image reconstruction in video communications

Science.gov (United States)

Shiell, Derek J.; Xiao, Jing; Katsaggelos, Aggelos K.

2008-08-01

Emerging communications trends point to streaming video as a new form of content delivery. These systems are implemented over wired systems, such as cable or ethernet, and wireless networks, cell phones, and portable game systems. These communications systems require sophisticated methods of compression and error-resilience encoding to enable communications across band-limited and noisy delivery channels. Additionally, the transmitted video data must be of high enough quality to ensure a satisfactory end-user experience. Traditionally, video compression makes use of temporal and spatial coherence to reduce the information required to represent an image. In many communications systems, the communications channel is characterized by a probabilistic model which describes the capacity or fidelity of the channel. The implication is that information is lost or distorted in the channel, and requires concealment on the receiving end. We demonstrate a generative model based transmission scheme to compress human face images in video, which has the advantages of a potentially higher compression ratio, while maintaining robustness to errors and data corruption. This is accomplished by training an offline face model and using the model to reconstruct face images on the receiving end. We propose a sub-component AAM modeling the appearance of sub-facial components individually, and show face reconstruction results under different types of video degradation using a weighted and non-weighted version of the sub-component AAM.

A method of mobile video transmission based on J2ee

Science.gov (United States)

Guo, Jian-xin; Zhao, Ji-chun; Gong, Jing; Chun, Yang

2013-03-01

As 3G (3rd-generation) networks evolve worldwide, the rising demand for mobile video services and the enormous growth of video on the internet is creating major new revenue opportunities for mobile network operators and application developers. The text introduced a method of mobile video transmission based on J2ME, giving the method of video compressing, then describing the video compressing standard, and then describing the software design. The proposed mobile video method based on J2EE is a typical mobile multimedia application, which has a higher availability and a wide range of applications. The users can get the video through terminal devices such as phone.

4K Video Traffic Prediction using Seasonal Autoregressive Modeling

Directory of Open Access Journals (Sweden)

D. R. Marković

2017-06-01

Full Text Available From the perspective of average viewer, high definition video streams such as HD (High Definition and UHD (Ultra HD are increasing their internet presence year over year. This is not surprising, having in mind expansion of HD streaming services, such as YouTube, Netflix etc. Therefore, high definition video streams are starting to challenge network resource allocation with their bandwidth requirements and statistical characteristics. Need for analysis and modeling of this demanding video traffic has essential importance for better quality of service and experience support. In this paper we use an easy-to-apply statistical model for prediction of 4K video traffic. Namely, seasonal autoregressive modeling is applied in prediction of 4K video traffic, encoded with HEVC (High Efficiency Video Coding. Analysis and modeling were performed within R programming environment using over 17.000 high definition video frames. It is shown that the proposed methodology provides good accuracy in high definition video traffic modeling.

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

Science.gov (United States)

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

2013-01-01

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

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/.

Video coding and decoding devices and methods preserving PPG relevant information

NARCIS (Netherlands)

2015-01-01

The present invention relates to a video encoding device (10, 10', 10") and method for encoding video data and to a corresponding video decoding device (60, 60') and method. To preserve PPG relevant information after encoding without requiring a large amount of additional data for the video encoder

Video coding and decoding devices and methods preserving ppg relevant information

NARCIS (Netherlands)

2013-01-01

The present invention relates to a video encoding device (10, 10', 10'') and method for encoding video data and to a corresponding video decoding device (60, 60') and method. To preserve PPG relevant information after encoding without requiring a large amount of additional data for the video encoder

Objective video quality assessment method for freeze distortion based on freeze aggregation

Science.gov (United States)

Watanabe, Keishiro; Okamoto, Jun; Kurita, Takaaki

2006-01-01

With the development of the broadband network, video communications such as videophone, video distribution, and IPTV services are beginning to become common. In order to provide these services appropriately, we must manage them based on subjective video quality, in addition to designing a network system based on it. Currently, subjective quality assessment is the main method used to quantify video quality. However, it is time-consuming and expensive. Therefore, we need an objective quality assessment technology that can estimate video quality from video characteristics effectively. Video degradation can be categorized into two types: spatial and temporal. Objective quality assessment methods for spatial degradation have been studied extensively, but methods for temporal degradation have hardly been examined even though it occurs frequently due to network degradation and has a large impact on subjective quality. In this paper, we propose an objective quality assessment method for temporal degradation. Our approach is to aggregate multiple freeze distortions into an equivalent freeze distortion and then derive the objective video quality from the equivalent freeze distortion. Specifically, our method considers the total length of all freeze distortions in a video sequence as the length of the equivalent single freeze distortion. In addition, we propose a method using the perceptual characteristics of short freeze distortions. We verified that our method can estimate the objective video quality well within the deviation of subjective video quality.

Comparison of Video Steganography Methods for Watermark Embedding

Directory of Open Access Journals (Sweden)

Griberman David

2016-05-01

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

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

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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.

Multi-Model Estimation Based Moving Object Detection for Aerial Video

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Yanning Zhang

2015-04-01

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

A low delay transmission method of multi-channel video based on FPGA

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Fu, Weijian; Wei, Baozhi; Li, Xiaobin; Wang, Quan; Hu, Xiaofei

2018-03-01

In order to guarantee the fluency of multi-channel video transmission in video monitoring scenarios, we designed a kind of video format conversion method based on FPGA and its DMA scheduling for video data, reduces the overall video transmission delay.In order to sace the time in the conversion process, the parallel ability of FPGA is used to video format conversion. In order to improve the direct memory access (DMA) writing transmission rate of PCIe bus, a DMA scheduling method based on asynchronous command buffer is proposed. The experimental results show that this paper designs a low delay transmission method based on FPGA, which increases the DMA writing transmission rate by 34% compared with the existing method, and then the video overall delay is reduced to 23.6ms.

Intelligent Model for Video Survillance Security System

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J. Vidhya

2013-12-01

Full Text Available Video surveillance system senses and trails out all the threatening issues in the real time environment. It prevents from security threats with the help of visual devices which gather the information related to videos like CCTV’S and IP (Internet Protocol cameras. Video surveillance system has become a key for addressing problems in the public security. They are mostly deployed on the IP based network. So, all the possible security threats exist in the IP based application might also be the threats available for the reliable application which is available for video surveillance. In result, it may increase cybercrime, illegal video access, mishandling videos and so on. Hence, in this paper an intelligent model is used to propose security for video surveillance system which ensures safety and it provides secured access on video.

Video elicitation interviews: a qualitative research method for investigating physician-patient interactions.

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Henry, Stephen G; Fetters, Michael D

2012-01-01

We describe the concept and method of video elicitation interviews and provide practical guidance for primary care researchers who want to use this qualitative method to investigate physician-patient interactions. During video elicitation interviews, researchers interview patients or physicians about a recent clinical interaction using a video recording of that interaction as an elicitation tool. Video elicitation is useful because it allows researchers to integrate data about the content of physician-patient interactions gained from video recordings with data about participants' associated thoughts, beliefs, and emotions gained from elicitation interviews. This method also facilitates investigation of specific events or moments during interactions. Video elicitation interviews are logistically demanding and time consuming, and they should be reserved for research questions that cannot be fully addressed using either standard interviews or video recordings in isolation. As many components of primary care fall into this category, high-quality video elicitation interviews can be an important method for understanding and improving physician-patient interactions in primary care.

Video Elicitation Interviews: A Qualitative Research Method for Investigating Physician-Patient Interactions

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Henry, Stephen G.; Fetters, Michael D.

2012-01-01

We describe the concept and method of video elicitation interviews and provide practical guidance for primary care researchers who want to use this qualitative method to investigate physician-patient interactions. During video elicitation interviews, researchers interview patients or physicians about a recent clinical interaction using a video recording of that interaction as an elicitation tool. Video elicitation is useful because it allows researchers to integrate data about the content of physician-patient interactions gained from video recordings with data about participants’ associated thoughts, beliefs, and emotions gained from elicitation interviews. This method also facilitates investigation of specific events or moments during interactions. Video elicitation interviews are logistically demanding and time consuming, and they should be reserved for research questions that cannot be fully addressed using either standard interviews or video recordings in isolation. As many components of primary care fall into this category, high-quality video elicitation interviews can be an important method for understanding and improving physician-patient interactions in primary care. PMID:22412003

Segment scheduling method for reducing 360° video streaming latency

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Gudumasu, Srinivas; Asbun, Eduardo; He, Yong; Ye, Yan

2017-09-01

360° video is an emerging new format in the media industry enabled by the growing availability of virtual reality devices. It provides the viewer a new sense of presence and immersion. Compared to conventional rectilinear video (2D or 3D), 360° video poses a new and difficult set of engineering challenges on video processing and delivery. Enabling comfortable and immersive user experience requires very high video quality and very low latency, while the large video file size poses a challenge to delivering 360° video in a quality manner at scale. Conventionally, 360° video represented in equirectangular or other projection formats can be encoded as a single standards-compliant bitstream using existing video codecs such as H.264/AVC or H.265/HEVC. Such method usually needs very high bandwidth to provide an immersive user experience. While at the client side, much of such high bandwidth and the computational power used to decode the video are wasted because the user only watches a small portion (i.e., viewport) of the entire picture. Viewport dependent 360°video processing and delivery approaches spend more bandwidth on the viewport than on non-viewports and are therefore able to reduce the overall transmission bandwidth. This paper proposes a dual buffer segment scheduling algorithm for viewport adaptive streaming methods to reduce latency when switching between high quality viewports in 360° video streaming. The approach decouples the scheduling of viewport segments and non-viewport segments to ensure the viewport segment requested matches the latest user head orientation. A base layer buffer stores all lower quality segments, and a viewport buffer stores high quality viewport segments corresponding to the most recent viewer's head orientation. The scheduling scheme determines viewport requesting time based on the buffer status and the head orientation. This paper also discusses how to deploy the proposed scheduling design for various viewport adaptive video

Learning to Swim Using Video Modelling and Video Feedback within a Self-Management Program

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Lao, So-An; Furlonger, Brett E.; Moore, Dennis W.; Busacca, Margherita

2016-01-01

Although many adults who cannot swim are primarily interested in learning by direct coaching there are options that have a focus on self-directed learning. As an alternative a self-management program combined with video modelling, video feedback and high quality and affordable video technology was used to assess its effectiveness to assisting an…

Dimensioning Method for Conversational Video Applications in Wireless Convergent Networks

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Raquel Perez Leal

2007-12-01

Full Text Available New convergent services are becoming possible, thanks to the expansion of IP networks based on the availability of innovative advanced coding formats such as H.264, which reduce network bandwidth requirements providing good video quality, and the rapid growth in the supply of dual-mode WiFi cellular terminals. This paper provides, first, a comprehensive subject overview as several technologies are involved, such as medium access protocol in IEEE802.11, H.264 advanced video coding standards, and conversational application characterization and recommendations. Second, the paper presents a new and simple dimensioning model of conversational video over wireless LAN. WLAN is addressed under the optimal network throughput and the perspective of video quality. The maximum number of simultaneous users resulting from throughput is limited by the collisions taking place in the shared medium with the statistical contention protocol. The video quality is conditioned by the packet loss in the contention protocol. Both approaches are analyzed within the scope of the advanced video codecs used in conversational video over IP, to conclude that conversational video dimensioning based on network throughput is not enough to ensure a satisfactory user experience, and video quality has to be taken also into account. Finally, the proposed model has been applied to a real-office scenario.

Dimensioning Method for Conversational Video Applications in Wireless Convergent Networks

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Alonso JoséI

2008-01-01

Full Text Available Abstract New convergent services are becoming possible, thanks to the expansion of IP networks based on the availability of innovative advanced coding formats such as H.264, which reduce network bandwidth requirements providing good video quality, and the rapid growth in the supply of dual-mode WiFi cellular terminals. This paper provides, first, a comprehensive subject overview as several technologies are involved, such as medium access protocol in IEEE802.11, H.264 advanced video coding standards, and conversational application characterization and recommendations. Second, the paper presents a new and simple dimensioning model of conversational video over wireless LAN. WLAN is addressed under the optimal network throughput and the perspective of video quality. The maximum number of simultaneous users resulting from throughput is limited by the collisions taking place in the shared medium with the statistical contention protocol. The video quality is conditioned by the packet loss in the contention protocol. Both approaches are analyzed within the scope of the advanced video codecs used in conversational video over IP, to conclude that conversational video dimensioning based on network throughput is not enough to ensure a satisfactory user experience, and video quality has to be taken also into account. Finally, the proposed model has been applied to a real-office scenario.

Methods and Algorithms for Detecting Objects in Video Files

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Nguyen The Cuong

2018-01-01

Full Text Available Video files are files that store motion pictures and sounds like in real life. In today's world, the need for automated processing of information in video files is increasing. Automated processing of information has a wide range of application including office/home surveillance cameras, traffic control, sports applications, remote object detection, and others. In particular, detection and tracking of object movement in video file plays an important role. This article describes the methods of detecting objects in video files. Today, this problem in the field of computer vision is being studied worldwide.

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

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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.

Using Video-Based Modeling to Promote Acquisition of Fundamental Motor Skills

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Obrusnikova, Iva; Rattigan, Peter J.

2016-01-01

Video-based modeling is becoming increasingly popular for teaching fundamental motor skills to children in physical education. Two frequently used video-based instructional strategies that incorporate modeling are video prompting (VP) and video modeling (VM). Both strategies have been used across multiple disciplines and populations to teach a…

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

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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.

Learning a Continuous-Time Streaming Video QoE Model.

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

2018-05-01

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

Teaching Daily Living Skills to Seven Individuals with Severe Intellectual Disabilities: A Comparison of Video Prompting to Video Modeling

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Cannella-Malone, Helen I.; Fleming, Courtney; Chung, Yi-Cheih; Wheeler, Geoffrey M.; Basbagill, Abby R.; Singh, Angella H.

2011-01-01

We conducted a systematic replication of Cannella-Malone et al. by comparing the effects of video prompting to video modeling for teaching seven students with severe disabilities to do laundry and wash dishes. The video prompting and video modeling procedures were counterbalanced across tasks and participants and compared in an alternating…

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.

Hierarchical Context Modeling for Video Event Recognition.

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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.

Examining human behavior in video games: The development of a computational model to measure aggression.

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Lamb, Richard; Annetta, Leonard; Hoston, Douglas; Shapiro, Marina; Matthews, Benjamin

2018-06-01

Video games with violent content have raised considerable concern in popular media and within academia. Recently, there has been considerable attention regarding the claim of the relationship between aggression and video game play. The authors of this study propose the use of a new class of tools developed via computational models to allow examination of the question of whether there is a relationship between violent video games and aggression. The purpose of this study is to computationally model and compare the General Aggression Model with the Diathesis Mode of Aggression related to the play of violent content in video games. A secondary purpose is to provide a method of measuring and examining individual aggression arising from video game play. Total participants examined for this study are N = 1065. This study occurs in three phases. Phase 1 is the development and quantification of the profile combination of traits via latent class profile analysis. Phase 2 is the training of the artificial neural network. Phase 3 is the comparison of each model as a computational model with and without the presence of video game violence. Results suggest that a combination of environmental factors and genetic predispositions trigger aggression related to video games.

Comparing Video Modeling and Graduated Guidance Together and Video Modeling Alone for Teaching Role Playing Skills to Children with Autism

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Akmanoglu, Nurgul; Yanardag, Mehmet; Batu, E. Sema

2014-01-01

Teaching play skills is important for children with autism. The purpose of the present study was to compare effectiveness and efficiency of providing video modeling and graduated guidance together and video modeling alone for teaching role playing skills to children with autism. The study was conducted with four students. The study was conducted…

An Aerial Video Stabilization Method Based on SURF Feature

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Wu Hao

2016-01-01

Full Text Available The video captured by Micro Aerial Vehicle is often degraded due to unexpected random trembling and jitter caused by wind and the shake of the aerial platform. An approach for stabilizing the aerial video based on SURF feature and Kalman filter is proposed. SURF feature points are extracted in each frame, and the feature points between adjacent frames are matched using Fast Library for Approximate Nearest Neighbors search method. Then Random Sampling Consensus matching algorithm and Least Squares Method are used to remove mismatching points pairs, and estimate the transformation between the adjacent images. Finally, Kalman filter is applied to smooth the motion parameters and separate Intentional Motion from Unwanted Motion to stabilize the aerial video. Experiments results show that the approach can stabilize aerial video efficiently with high accuracy, and it is robust to the translation, rotation and zooming motion of camera.

A comparison of peer video modeling and self video modeling to teach textual responses in children with autism.

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Marcus, Alonna; Wilder, David A

2009-01-01

Peer video modeling was compared to self video modeling to teach 3 children with autism to respond appropriately to (i.e., identify or label) novel letters. A combination multiple baseline and multielement design was used to compare the two procedures. Results showed that all 3 participants met the mastery criterion in the self-modeling condition, whereas only 1 of the participants met the mastery criterion in the peer-modeling condition. In addition, the participant who met the mastery criterion in both conditions reached the criterion more quickly in the self-modeling condition. Results are discussed in terms of their implications for teaching new skills to children with autism.

Learning from video modeling examples : Effects of seeing the human model's face

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Van Gog, Tamara; Verveer, Ilse; Verveer, Lise

2014-01-01

Video modeling examples in which a human(-like) model shows learners how to perform a task are increasingly used in education, as they have become very easy to create and distribute in e-learning environments. However, little is known about design guidelines to optimize learning from video modeling

Teaching autistic children conversational speech using video modeling.

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Charlop, M H; Milstein, J P

1989-01-01

We assessed the effects of video modeling on acquisition and generalization of conversational skills among autistic children. Three autistic boys observed videotaped conversations consisting of two people discussing specific toys. When criterion for learning was met, generalization of conversational skills was assessed with untrained topics of conversation; new stimuli (toys); unfamiliar persons, siblings, and autistic peers; and other settings. The results indicated that the children learned through video modeling, generalized their conversational skills, and maintained conversational speech over a 15-month period. Video modeling shows much promise as a rapid and effective procedure for teaching complex verbal skills such as conversational speech. PMID:2793634

An evaluation of the production effects of video self-modeling.

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O'Handley, Roderick D; Allen, Keith D

2017-12-01

A multiple baseline across tasks design was used to evaluate the production effects of video self-modeling on three activities of daily living tasks of an adult male with Autism Spectrum Disorder and Intellectual Disability. Results indicated large increases in task accuracy after the production of a self-modeling video for each task, but before the video was viewed by the participant. Results also indicated small increases when the participant was directed to view the same video self-models before being prompted to complete each task. Copyright © 2017 Elsevier Ltd. All rights reserved.

Constructing Self-Modeling Videos: Procedures and Technology

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Collier-Meek, Melissa A.; Fallon, Lindsay M.; Johnson, Austin H.; Sanetti, Lisa M. H.; Delcampo, Marisa A.

2012-01-01

Although widely recommended, evidence-based interventions are not regularly utilized by school practitioners. Video self-modeling is an effective and efficient evidence-based intervention for a variety of student problem behaviors. However, like many other evidence-based interventions, it is not frequently used in schools. As video creation…

An Overview of Deep Learning Based Methods for Unsupervised and Semi-Supervised Anomaly Detection in Videos

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B. Ravi Kiran

2018-02-01

Full Text Available Videos represent the primary source of information for surveillance applications. Video material is often available in large quantities but in most cases it contains little or no annotation for supervised learning. This article reviews the state-of-the-art deep learning based methods for video anomaly detection and categorizes them based on the type of model and criteria of detection. We also perform simple studies to understand the different approaches and provide the criteria of evaluation for spatio-temporal anomaly detection.

Using video-based observation research methods in primary care health encounters to evaluate complex interactions.

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Asan, Onur; Montague, Enid

2014-01-01

The purpose of this paper is to describe the use of video-based observation research methods in primary care environment and highlight important methodological considerations and provide practical guidance for primary care and human factors researchers conducting video studies to understand patient-clinician interaction in primary care settings. We reviewed studies in the literature which used video methods in health care research, and we also used our own experience based on the video studies we conducted in primary care settings. This paper highlighted the benefits of using video techniques, such as multi-channel recording and video coding, and compared "unmanned" video recording with the traditional observation method in primary care research. We proposed a list that can be followed step by step to conduct an effective video study in a primary care setting for a given problem. This paper also described obstacles, researchers should anticipate when using video recording methods in future studies. With the new technological improvements, video-based observation research is becoming a promising method in primary care and HFE research. Video recording has been under-utilised as a data collection tool because of confidentiality and privacy issues. However, it has many benefits as opposed to traditional observations, and recent studies using video recording methods have introduced new research areas and approaches.

Video Modeling and Word Identification in Adolescents with Autism Spectrum Disorder

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Morlock, Larissa; Reynolds, Jennifer L.; Fisher, Sycarah; Comer, Ronald J.

2015-01-01

Video modeling involves the learner viewing videos of a model demonstrating a target skill. According to the National Professional Development Center on Autism Spectrum Disorders (2011), video modeling is an evidenced-based intervention for individuals with Autism Spectrum Disorder (ASD) in elementary through middle school. Little research exists…

A Novel Video Data-Source Authentication Model Based on Digital Watermarking and MAC in Multicast

Institute of Scientific and Technical Information of China (English)

ZHAO Anjun; LU Xiangli; GUO Lei

2006-01-01

A novel video data authentication model based on digital video watermarking and MAC (message authentication code) in multicast protocol is proposed in this paper. The digital watermarking which composes of the MAC of the significant video content, the key and instant authentication data is embedded into the insignificant video component by the MLUT (modified look-up table) video watermarking technology. We explain a method that does not require storage of each data packet for a time, thus making receiver not vulnerable to DOS (denial of service) attack. So the video packets can be authenticated instantly without large volume buffer in the receivers. TESLA(timed efficient stream loss-tolerant authentication) does not explain how to select the suitable value for d, which is an important parameter in multicast source authentication. So we give a method to calculate the key disclosure delay (number of intervals). Simulation results show that the proposed algorithms improve the performance of data source authentication in multicast.

Video-modelling to improve task completion in a child with autism.

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Rayner, Christopher Stephen

2010-01-01

To evaluate the use of video modelling as an intervention for increasing task completion for individuals with autism who have high support needs. A 12-year-old-boy with autism received video modelling intervention on two routines (unpacking his bag and brushing his teeth). Use of the video modelling intervention led to rapid increases in the percentage of steps performed in the unpacking his bag sequence and these gains generalized to packing his bag prior to departure from school. There was limited success in the use of the video modelling intervention for teaching the participant to brush his teeth. Video modelling can be successfully applied to enhance daily functioning in a classroom environment for students with autism and high support needs.

An Innovative SIFT-Based Method for Rigid Video Object Recognition

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Jie Yu

2014-01-01

Full Text Available This paper presents an innovative SIFT-based method for rigid video object recognition (hereafter called RVO-SIFT. Just like what happens in the vision system of human being, this method makes the object recognition and feature updating process organically unify together, using both trajectory and feature matching, and thereby it can learn new features not only in the training stage but also in the recognition stage, which can improve greatly the completeness of the video object’s features automatically and, in turn, increases the ratio of correct recognition drastically. The experimental results on real video sequences demonstrate its surprising robustness and efficiency.

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

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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.

Gas leak detection in infrared video with background modeling

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Zeng, Xiaoxia; Huang, Likun

2018-03-01

Background modeling plays an important role in the task of gas detection based on infrared video. VIBE algorithm is a widely used background modeling algorithm in recent years. However, the processing speed of the VIBE algorithm sometimes cannot meet the requirements of some real time detection applications. Therefore, based on the traditional VIBE algorithm, we propose a fast prospect model and optimize the results by combining the connected domain algorithm and the nine-spaces algorithm in the following processing steps. Experiments show the effectiveness of the proposed method.

Occupational Therapy and Video Modeling for Children with Autism

Science.gov (United States)

Becker, Emily Ann; Watry-Christian, Meghan; Simmons, Amanda; Van Eperen, Ashleigh

2016-01-01

This review explores the evidence in support of using video modeling for teaching children with autism. The process of implementing video modeling, the use of various perspectives, and a wide range of target skills are addressed. Additionally, several helpful clinician resources including handheld device applications, books, and websites are…

Damaged Watermarks Detection in Frequency Domain as a Primary Method for Video Concealment

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Robert Hudec

2011-01-01

Full Text Available This paper deals with video transmission over lossy communication networks. The main idea is to develop video concealment method for information losses and errors correction. At the beginning, three main groups of video concealment methods, divided by encoder/decoder collaboration, are briefly described. The modified algorithm based on the detection and filtration of damaged watermark blocks encapsulated to the transmitted video was developed. Finally, the efficiency of developed algorithm is presented in experimental part of this paper.

Fixed-point data-collection method of video signal

International Nuclear Information System (INIS)

Tang Yu; Yin Zejie; Qian Weiming; Wu Xiaoyi

1997-01-01

The author describes a Fixed-point data-collection method of video signal. The method provides an idea of fixed-point data-collection, and has been successfully applied in the research of real-time radiography on dose field, a project supported by National Science Fund

News video story segmentation method using fusion of audio-visual features

Science.gov (United States)

Wen, Jun; Wu, Ling-da; Zeng, Pu; Luan, Xi-dao; Xie, Yu-xiang

2007-11-01

News story segmentation is an important aspect for news video analysis. This paper presents a method for news video story segmentation. Different form prior works, which base on visual features transform, the proposed technique uses audio features as baseline and fuses visual features with it to refine the results. At first, it selects silence clips as audio features candidate points, and selects shot boundaries and anchor shots as two kinds of visual features candidate points. Then this paper selects audio feature candidates as cues and develops different fusion method, which effectively using diverse type visual candidates to refine audio candidates, to get story boundaries. Experiment results show that this method has high efficiency and adaptability to different kinds of news video.

Non-intrusive Packet-Layer Model for Monitoring Video Quality of IPTV Services

Science.gov (United States)

Yamagishi, Kazuhisa; Hayashi, Takanori

Developing a non-intrusive packet-layer model is required to passively monitor the quality of experience (QoE) during service. We propose a packet-layer model that can be used to estimate the video quality of IPTV using quality parameters derived from transmitted packet headers. The computational load of the model is lighter than that of the model that takes video signals and/or video-related bitstream information such as motion vectors as input. This model is applicable even if the transmitted bitstream information is encrypted because it uses transmitted packet headers rather than bitstream information. For developing the model, we conducted three extensive subjective quality assessments for different encoders and decoders (codecs), and video content. Then, we modeled the subjective video quality assessment characteristics based on objective features affected by coding and packet loss. Finally, we verified the model's validity by applying our model to unknown data sets different from training data sets used above.

An Effective Transform Unit Size Decision Method for High Efficiency Video Coding

Directory of Open Access Journals (Sweden)

Chou-Chen Wang

2014-01-01

Full Text Available High efficiency video coding (HEVC is the latest video coding standard. HEVC can achieve higher compression performance than previous standards, such as MPEG-4, H.263, and H.264/AVC. However, HEVC requires enormous computational complexity in encoding process due to quadtree structure. In order to reduce the computational burden of HEVC encoder, an early transform unit (TU decision algorithm (ETDA is adopted to pruning the residual quadtree (RQT at early stage based on the number of nonzero DCT coefficients (called NNZ-EDTA to accelerate the encoding process. However, the NNZ-ETDA cannot effectively reduce the computational load for sequences with active motion or rich texture. Therefore, in order to further improve the performance of NNZ-ETDA, we propose an adaptive RQT-depth decision for NNZ-ETDA (called ARD-NNZ-ETDA by exploiting the characteristics of high temporal-spatial correlation that exist in nature video sequences. Simulation results show that the proposed method can achieve time improving ratio (TIR about 61.26%~81.48% when compared to the HEVC test model 8.1 (HM 8.1 with insignificant loss of image quality. Compared with the NNZ-ETDA, the proposed method can further achieve an average TIR about 8.29%~17.92%.

Effects of Video Modeling on Treatment Integrity of Behavioral Interventions

Science.gov (United States)

DiGennaro-Reed, Florence D.; Codding, Robin; Catania, Cynthia N.; Maguire, Helena

2010-01-01

We examined the effects of individualized video modeling on the accurate implementation of behavioral interventions using a multiple baseline design across 3 teachers. During video modeling, treatment integrity improved above baseline levels; however, teacher performance remained variable. The addition of verbal performance feedback increased…

Using Video Modeling and Video Prompting to Teach Core Academic Content to Students with Learning Disabilities

Science.gov (United States)

Kellems, Ryan O.; Edwards, Sean

2016-01-01

Practitioners are constantly searching for evidence-based practices that are effective in teaching academic skills to students with learning disabilities (LD). Video modeling (VM) and video prompting have become popular instructional interventions for many students across a wide range of different disability classifications, including those with…

Use of Video Modeling and Video Prompting Interventions for Teaching Daily Living Skills to Individuals with Autism Spectrum Disorders: A Review

Science.gov (United States)

Gardner, Stephanie; Wolfe, Pamela

2013-01-01

Identifying methods to increase the independent functioning of individuals with autism spectrum disorders (ASD) is vital in enhancing their quality of life; teaching students with ASD daily living skills can foster independent functioning. This review examines interventions that implement video modeling and/or prompting to teach individuals with…

Video modeling to train staff to implement discrete-trial instruction.

Science.gov (United States)

Catania, Cynthia N; Almeida, Daniel; Liu-Constant, Brian; DiGennaro Reed, Florence D

2009-01-01

Three new direct-service staff participated in a program that used a video model to train target skills needed to conduct a discrete-trial session. Percentage accuracy in completing a discrete-trial teaching session was evaluated using a multiple baseline design across participants. During baseline, performances ranged from a mean of 12% to 63% accuracy. During video modeling, there was an immediate increase in accuracy to a mean of 98%, 85%, and 94% for each participant. Performance during maintenance and generalization probes remained at high levels. Results suggest that video modeling can be an effective technique to train staff to conduct discrete-trial sessions.

The Global Classroom Video Conferencing Model and First Evaluations

DEFF Research Database (Denmark)

Weitze, Charlotte Lærke; Ørngreen, Rikke; Levinsen, Karin

2013-01-01

pedagogical innovativeness, including collaborative and technological issues. The research is based on the Global Classroom Model as it is implemented and used at an adult learning center in Denmark (VUC Storstrøm). VUC Storstrøms (VUC) Global Classroom Model is an approach to video conferencing and e......Learning using campus-based teaching combined with laptop solutions for students at home. After a couple of years of campus-to-campus video streaming, VUC started a fulltime day program in 2011 with the support of a hybrid campus and videoconference model. In this model the teachers and some of the students......This paper presents and discusses findings about how students, teachers, and the organization experience a start-up-project applying video conferences between campus and home. This is new territory for adult learning centers. The paper discusses the transition to this eLearning form and discusses...

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.

Learning-Based Just-Noticeable-Quantization- Distortion Modeling for Perceptual Video Coding.

Science.gov (United States)

Ki, Sehwan; Bae, Sung-Ho; Kim, Munchurl; Ko, Hyunsuk

2018-07-01

Conventional predictive video coding-based approaches are reaching the limit of their potential coding efficiency improvements, because of severely increasing computation complexity. As an alternative approach, perceptual video coding (PVC) has attempted to achieve high coding efficiency by eliminating perceptual redundancy, using just-noticeable-distortion (JND) directed PVC. The previous JNDs were modeled by adding white Gaussian noise or specific signal patterns into the original images, which were not appropriate in finding JND thresholds due to distortion with energy reduction. In this paper, we present a novel discrete cosine transform-based energy-reduced JND model, called ERJND, that is more suitable for JND-based PVC schemes. Then, the proposed ERJND model is extended to two learning-based just-noticeable-quantization-distortion (JNQD) models as preprocessing that can be applied for perceptual video coding. The two JNQD models can automatically adjust JND levels based on given quantization step sizes. One of the two JNQD models, called LR-JNQD, is based on linear regression and determines the model parameter for JNQD based on extracted handcraft features. The other JNQD model is based on a convolution neural network (CNN), called CNN-JNQD. To our best knowledge, our paper is the first approach to automatically adjust JND levels according to quantization step sizes for preprocessing the input to video encoders. In experiments, both the LR-JNQD and CNN-JNQD models were applied to high efficiency video coding (HEVC) and yielded maximum (average) bitrate reductions of 38.51% (10.38%) and 67.88% (24.91%), respectively, with little subjective video quality degradation, compared with the input without preprocessing applied.

Recurrent and Dynamic Models for Predicting Streaming Video Quality of Experience.

Science.gov (United States)

Bampis, Christos G; Li, Zhi; Katsavounidis, Ioannis; Bovik, Alan C

2018-07-01

Streaming video services represent a very large fraction of global bandwidth consumption. Due to the exploding demands of mobile video streaming services, coupled with limited bandwidth availability, video streams are often transmitted through unreliable, low-bandwidth networks. This unavoidably leads to two types of major streaming-related impairments: compression artifacts and/or rebuffering events. In streaming video applications, the end-user is a human observer; hence being able to predict the subjective Quality of Experience (QoE) associated with streamed videos could lead to the creation of perceptually optimized resource allocation strategies driving higher quality video streaming services. We propose a variety of recurrent dynamic neural networks that conduct continuous-time subjective QoE prediction. By formulating the problem as one of time-series forecasting, we train a variety of recurrent neural networks and non-linear autoregressive models to predict QoE using several recently developed subjective QoE databases. These models combine multiple, diverse neural network inputs, such as predicted video quality scores, rebuffering measurements, and data related to memory and its effects on human behavioral responses, using them to predict QoE on video streams impaired by both compression artifacts and rebuffering events. Instead of finding a single time-series prediction model, we propose and evaluate ways of aggregating different models into a forecasting ensemble that delivers improved results with reduced forecasting variance. We also deploy appropriate new evaluation metrics for comparing time-series predictions in streaming applications. Our experimental results demonstrate improved prediction performance that approaches human performance. An implementation of this work can be found at https://github.com/christosbampis/NARX_QoE_release.

Cross-band noise model refinement for transform domain Wyner–Ziv video coding

DEFF Research Database (Denmark)

Huang, Xin; Forchhammer, Søren

2012-01-01

TDWZ video coding trails that of conventional video coding solutions, mainly due to the quality of side information, inaccurate noise modeling and loss in the final coding step. The major goal of this paper is to enhance the accuracy of the noise modeling, which is one of the most important aspects...... influencing the coding performance of DVC. A TDWZ video decoder with a novel cross-band based adaptive noise model is proposed, and a noise residue refinement scheme is introduced to successively update the estimated noise residue for noise modeling after each bit-plane. Experimental results show...... that the proposed noise model and noise residue refinement scheme can improve the rate-distortion (RD) performance of TDWZ video coding significantly. The quality of the side information modeling is also evaluated by a measure of the ideal code length....

Application of discriminative models for interactive query refinement in video retrieval

Science.gov (United States)

Srivastava, Amit; Khanwalkar, Saurabh; Kumar, Anoop

2013-12-01

The ability to quickly search for large volumes of videos for specific actions or events can provide a dramatic new capability to intelligence agencies. Example-based queries from video are a form of content-based information retrieval (CBIR) where the objective is to retrieve clips from a video corpus, or stream, using a representative query sample to find more like this. Often, the accuracy of video retrieval is largely limited by the gap between the available video descriptors and the underlying query concept, and such exemplar queries return many irrelevant results with relevant ones. In this paper, we present an Interactive Query Refinement (IQR) system which acts as a powerful tool to leverage human feedback and allow intelligence analyst to iteratively refine search queries for improved precision in the retrieved results. In our approach to IQR, we leverage discriminative models that operate on high dimensional features derived from low-level video descriptors in an iterative framework. Our IQR model solicits relevance feedback on examples selected from the region of uncertainty and updates the discriminating boundary to produce a relevance ranked results list. We achieved 358% relative improvement in Mean Average Precision (MAP) over initial retrieval list at a rank cutoff of 100 over 4 iterations. We compare our discriminative IQR model approach to a naïve IQR and show our model-based approach yields 49% relative improvement over the no model naïve system.

A Method for Counting Moving People in Video Surveillance Videos

Directory of Open Access Journals (Sweden)

Mario Vento

2010-01-01

Full Text Available People counting is an important problem in video surveillance applications. This problem has been faced either by trying to detect people in the scene and then counting them or by establishing a mapping between some scene feature and the number of people (avoiding the complex detection problem. This paper presents a novel method, following this second approach, that is based on the use of SURF features and of an ϵ-SVR regressor provide an estimate of this count. The algorithm takes specifically into account problems due to partial occlusions and to perspective. In the experimental evaluation, the proposed method has been compared with the algorithm by Albiol et al., winner of the PETS 2009 contest on people counting, using the same PETS 2009 database. The provided results confirm that the proposed method yields an improved accuracy, while retaining the robustness of Albiol's algorithm.

A Method for Counting Moving People in Video Surveillance Videos

Directory of Open Access Journals (Sweden)

Conte Donatello

2010-01-01

Full Text Available People counting is an important problem in video surveillance applications. This problem has been faced either by trying to detect people in the scene and then counting them or by establishing a mapping between some scene feature and the number of people (avoiding the complex detection problem. This paper presents a novel method, following this second approach, that is based on the use of SURF features and of an -SVR regressor provide an estimate of this count. The algorithm takes specifically into account problems due to partial occlusions and to perspective. In the experimental evaluation, the proposed method has been compared with the algorithm by Albiol et al., winner of the PETS 2009 contest on people counting, using the same PETS 2009 database. The provided results confirm that the proposed method yields an improved accuracy, while retaining the robustness of Albiol's algorithm.

A Method for Counting Moving People in Video Surveillance Videos

Science.gov (United States)

Conte, Donatello; Foggia, Pasquale; Percannella, Gennaro; Tufano, Francesco; Vento, Mario

2010-12-01

People counting is an important problem in video surveillance applications. This problem has been faced either by trying to detect people in the scene and then counting them or by establishing a mapping between some scene feature and the number of people (avoiding the complex detection problem). This paper presents a novel method, following this second approach, that is based on the use of SURF features and of an [InlineEquation not available: see fulltext.]-SVR regressor provide an estimate of this count. The algorithm takes specifically into account problems due to partial occlusions and to perspective. In the experimental evaluation, the proposed method has been compared with the algorithm by Albiol et al., winner of the PETS 2009 contest on people counting, using the same PETS 2009 database. The provided results confirm that the proposed method yields an improved accuracy, while retaining the robustness of Albiol's algorithm.

Examining the Effects of Video Modeling and Prompts to Teach Activities of Daily Living Skills.

Science.gov (United States)

Aldi, Catarina; Crigler, Alexandra; Kates-McElrath, Kelly; Long, Brian; Smith, Hillary; Rehak, Kim; Wilkinson, Lisa

2016-12-01

Video modeling has been shown to be effective in teaching a number of skills to learners diagnosed with autism spectrum disorders (ASD). In this study, we taught two young men diagnosed with ASD three different activities of daily living skills (ADLS) using point-of-view video modeling. Results indicated that both participants met criterion for all ADLS. Participants did not maintain mastery criterion at a 1-month follow-up, but did score above baseline at maintenance with and without video modeling. • Point-of-view video models may be an effective intervention to teach daily living skills. • Video modeling with handheld portable devices (Apple iPod or iPad) can be just as effective as video modeling with stationary viewing devices (television or computer). • The use of handheld portable devices (Apple iPod and iPad) makes video modeling accessible and possible in a wide variety of environments.

Continuous Video Modeling to Prompt Completion of Multi-Component Tasks by Adults with Moderate Intellectual Disability

Science.gov (United States)

Mechling, Linda C.; Ayres, Kevin M.; Purrazzella, Kaitlin; Purrazzella, Kimberly

2014-01-01

This investigation examined the ability of four adults with moderate intellectual disability to complete multi-component tasks using continuous video modeling. Continuous video modeling, which is a newly researched application of video modeling, presents video in a "looping" format which automatically repeats playing of the video while…

Using Mixed Methods to Analyze Video Data: A Mathematics Teacher Professional Development Example

Science.gov (United States)

DeCuir-Gunby, Jessica T.; Marshall, Patricia L.; McCulloch, Allison W.

2012-01-01

This article uses data from 65 teachers participating in a K-2 mathematics professional development research project as an example of how to analyze video recordings of teachers' classroom lessons using mixed methods. Through their discussion, the authors demonstrate how using a mixed methods approach to classroom video analysis allows researchers…

An effective method of collecting practical knowledge by presentation of videos and related words

Directory of Open Access Journals (Sweden)

Satoshi Shimada

2017-12-01

Full Text Available The concentration of practical knowledge and experiential knowledge in the form of collective intelligence (the wisdom of the crowd is of interest in the area of skill transfer. Previous studies have confirmed that collective intelligence can be formed through the utilization of video annotation systems where knowledge that is recalled while watching videos of work tasks can be assigned in the form of a comment. The knowledge that can be collected is limited, however, to the content that can be depicted in videos, meaning that it is necessary to prepare many videos when collecting knowledge. This paper proposes a method for expanding the scope of recall from the same video through the automatic generation and simultaneous display of related words and video scenes. Further, the validity of the proposed method is empirically illustrated through the example of a field experiment related to mountaineering skills.

Digital Video as a Personalized Learning Assignment: A Qualitative Study of Student Authored Video Using the ICSDR Model

Science.gov (United States)

Campbell, Laurie O.; Cox, Thomas D.

2018-01-01

Students within this study followed the ICSDR (Identify, Conceptualize/Connect, Storyboard, Develop, Review/Reflect/Revise) development model to create digital video, as a personalized and active learning assignment. The participants, graduate students in education, indicated that following the ICSDR framework for student-authored video guided…

Video Modeling and Prompting in Practice: Teaching Cooking Skills

Science.gov (United States)

Kellems, Ryan O.; Mourra, Kjerstin; Morgan, Robert L.; Riesen, Tim; Glasgow, Malinda; Huddleston, Robin

2016-01-01

This article discusses the creation of video modeling (VM) and video prompting (VP) interventions for teaching novel multi-step tasks to individuals with disabilities. This article reviews factors to consider when selecting skills to teach, and students for whom VM/VP may be successful, as well as the difference between VM and VP and circumstances…

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.

Effects of creating video-based modeling examples on learning and transfer

NARCIS (Netherlands)

Hoogerheide, Vincent; Loyens, Sofie M M; van Gog, Tamara

2014-01-01

Two experiments investigated whether acting as a peer model for a video-based modeling example, which entails studying a text with the intention to explain it to others and then actually explaining it on video, would foster learning and transfer. In both experiments, novices were instructed to study

Video Modeling and Observational Learning to Teach Gaming Access to Students with ASD

Science.gov (United States)

Spriggs, Amy D.; Gast, David L.; Knight, Victoria F.

2016-01-01

The purpose of this study was to evaluate both video modeling and observational learning to teach age-appropriate recreation and leisure skills (i.e., accessing video games) to students with autism spectrum disorder. Effects of video modeling were evaluated via a multiple probe design across participants and criteria for mastery were based on…

Using Video Modeling as an Anti-bullying Intervention for Children with Autism Spectrum Disorder.

Science.gov (United States)

Rex, Catherine; Charlop, Marjorie H; Spector, Vicki

2018-03-07

In the present study, we used a multiple baseline design across participants to assess the efficacy of a video modeling intervention to teach six children with autism spectrum disorder (ASD) to assertively respond to bullying. During baseline, the children made few appropriate responses upon viewing video clips of bullying scenarios. During the video modeling intervention, participants viewed videos of models assertively responding to three types of bullying: physical, verbal bullying, and social exclusion. Results indicated that all six children learned through video modeling to make appropriate assertive responses to bullying scenarios. Four of the six children demonstrated learning in the in situ bullying probes. The results are discussed in terms of an intervention for victims of bullying with ASD.

Energy saving approaches for video streaming on smartphone based on QoE modeling

DEFF Research Database (Denmark)

Ballesteros, Luis Guillermo Martinez; Ickin, Selim; Fiedler, Markus

2016-01-01

In this paper, we study the influence of video stalling on QoE. We provide QoE models that are obtained in realistic scenarios on the smartphone, and provide energy-saving approaches for smartphone by leveraging the proposed QoE models in relation to energy. Results show that approximately 5J...... is saved in a 3 minutes video clip with an acceptable Mean Opinion Score (MOS) level when the video frames are skipped. If the video frames are not skipped, then it is suggested to avoid freezes during a video stream as the freezes highly increase the energy waste on the smartphones....

Player behavioural modelling for video games

NARCIS (Netherlands)

van Lankveld, G.; Spronck, P.H.M.; Bakkes, S.C.J.

2012-01-01

Player behavioural modelling has grown from a means to improve the playing strength of computer programs that play classic games (e.g., chess), to a means for impacting the player experience and satisfaction in video games, as well as in cross-domain applications such as interactive storytelling. In

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

A Batch-Incremental Video Background Estimation Model using Weighted Low-Rank Approximation of Matrices

KAUST Repository

Dutta, Aritra

2017-07-02

Principal component pursuit (PCP) is a state-of-the-art approach for background estimation problems. Due to their higher computational cost, PCP algorithms, such as robust principal component analysis (RPCA) and its variants, are not feasible in processing high definition videos. To avoid the curse of dimensionality in those algorithms, several methods have been proposed to solve the background estimation problem in an incremental manner. We propose a batch-incremental background estimation model using a special weighted low-rank approximation of matrices. Through experiments with real and synthetic video sequences, we demonstrate that our method is superior to the state-of-the-art background estimation algorithms such as GRASTA, ReProCS, incPCP, and GFL.

A Batch-Incremental Video Background Estimation Model using Weighted Low-Rank Approximation of Matrices

KAUST Repository

Dutta, Aritra; Li, Xin; Richtarik, Peter

2017-01-01

Principal component pursuit (PCP) is a state-of-the-art approach for background estimation problems. Due to their higher computational cost, PCP algorithms, such as robust principal component analysis (RPCA) and its variants, are not feasible in processing high definition videos. To avoid the curse of dimensionality in those algorithms, several methods have been proposed to solve the background estimation problem in an incremental manner. We propose a batch-incremental background estimation model using a special weighted low-rank approximation of matrices. Through experiments with real and synthetic video sequences, we demonstrate that our method is superior to the state-of-the-art background estimation algorithms such as GRASTA, ReProCS, incPCP, and GFL.

Reviewing Instructional Studies Conducted Using Video Modeling to Children with Autism

Science.gov (United States)

Acar, Cimen; Diken, Ibrahim H.

2012-01-01

This study explored 31 instructional research articles written using video modeling to children with autism and published in peer-reviewed journals. The studies in this research have been reached by searching EBSCO, Academic Search Complete, ERIC and other Anadolu University online search engines and using keywords such as "autism, video modeling,…

A simplified 2D to 3D video conversion technology——taking virtual campus video production as an example

Directory of Open Access Journals (Sweden)

ZHUANG Huiyang

2012-10-01

Full Text Available This paper describes a simplified 2D to 3D Video Conversion Technology, taking virtual campus 3D video production as an example. First, it clarifies the meaning of the 2D to 3D Video Conversion Technology, and points out the disadvantages of traditional methods. Second, it forms an innovative and convenient method. A flow diagram, software and hardware configurations are presented. Finally, detailed description of the conversion steps and precautions are given in turn to the three processes, namely, preparing materials, modeling objects and baking landscapes, recording screen and converting videos .

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 ...

Strategies for Teaching Children with Autism to Imitate Response Chains Using Video Modeling

Science.gov (United States)

Tereshko, Lisa; MacDonald, Rebecca; Ahearn, William H.

2010-01-01

Video modeling has been found to be an effective procedure for teaching a variety of skills to persons with autism, however, some individuals do not learn through video instruction. The purpose of the current investigation was to teach children with autism, who initially did not imitate a video model, to construct three toy structures through the…

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.

Is Video-Based Education an Effective Method in Surgical Education? A Systematic Review.

Science.gov (United States)

Ahmet, Akgul; Gamze, Kus; Rustem, Mustafaoglu; Sezen, Karaborklu Argut

2018-02-12

Visual signs draw more attention during the learning process. Video is one of the most effective tool including a lot of visual cues. This systematic review set out to explore the influence of video in surgical education. We reviewed the current evidence for the video-based surgical education methods, discuss the advantages and disadvantages on the teaching of technical and nontechnical surgical skills. This systematic review was conducted according to the guidelines defined in the preferred reporting items for systematic reviews and meta-analyses statement. The electronic databases: the Cochrane Library, Medline (PubMED), and ProQuest were searched from their inception to the 30 January 2016. The Medical Subject Headings (MeSH) terms and keywords used were "video," "education," and "surgery." We analyzed all full-texts, randomised and nonrandomised clinical trials and observational studies including video-based education methods about any surgery. "Education" means a medical resident's or student's training and teaching process; not patients' education. We did not impose restrictions about language or publication date. A total of nine articles which met inclusion criteria were included. These trials enrolled 507 participants and the total number of participants per trial ranged from 10 to 172. Nearly all of the studies reviewed report significant knowledge gain from video-based education techniques. The findings of this systematic review provide fair to good quality studies to demonstrate significant gains in knowledge compared with traditional teaching. Additional video to simulator exercise or 3D animations has beneficial effects on training time, learning duration, acquisition of surgical skills, and trainee's satisfaction. Video-based education has potential for use in surgical education as trainees face significant barriers in their practice. This method is effective according to the recent literature. Video should be used in addition to standard techniques

A model of R-D performance evaluation for Rate-Distortion-Complexity evaluation of H.264 video coding

DEFF Research Database (Denmark)

Wu, Mo; Forchhammer, Søren

2007-01-01

This paper considers a method for evaluation of Rate-Distortion-Complexity (R-D-C) performance of video coding. A statistical model of the transformed coefficients is used to estimate the Rate-Distortion (R-D) performance. A model frame work for rate, distortion and slope of the R-D curve for inter...... and intra frame is presented. Assumptions are given for analyzing an R-D model for fast R-D-C evaluation. The theoretical expressions are combined with H.264 video coding, and confirmed by experimental results. The complexity frame work is applied to the integer motion estimation....

Traffic characterization and modeling of wavelet-based VBR encoded video

Energy Technology Data Exchange (ETDEWEB)

Yu Kuo; Jabbari, B. [George Mason Univ., Fairfax, VA (United States); Zafar, S. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.

1997-07-01

Wavelet-based video codecs provide a hierarchical structure for the encoded data, which can cater to a wide variety of applications such as multimedia systems. The characteristics of such an encoder and its output, however, have not been well examined. In this paper, the authors investigate the output characteristics of a wavelet-based video codec and develop a composite model to capture the traffic behavior of its output video data. Wavelet decomposition transforms the input video in a hierarchical structure with a number of subimages at different resolutions and scales. the top-level wavelet in this structure contains most of the signal energy. They first describe the characteristics of traffic generated by each subimage and the effect of dropping various subimages at the encoder on the signal-to-noise ratio at the receiver. They then develop an N-state Markov model to describe the traffic behavior of the top wavelet. The behavior of the remaining wavelets are then obtained through estimation, based on the correlations between these subimages at the same level of resolution and those wavelets located at an immediate higher level. In this paper, a three-state Markov model is developed. The resulting traffic behavior described by various statistical properties, such as moments and correlations, etc., is then utilized to validate their model.

Blind identification of full-field vibration modes from video measurements with phase-based video motion magnification

Science.gov (United States)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Kenyon, Garrett; Farrar, Charles; Mascareñas, David

2017-02-01

Experimental or operational modal analysis traditionally requires physically-attached wired or wireless sensors for vibration measurement of structures. This instrumentation can result in mass-loading on lightweight structures, and is costly and time-consuming to install and maintain on large civil structures, especially for long-term applications (e.g., structural health monitoring) that require significant maintenance for cabling (wired sensors) or periodic replacement of the energy supply (wireless sensors). Moreover, these sensors are typically placed at a limited number of discrete locations, providing low spatial sensing resolution that is hardly sufficient for modal-based damage localization, or model correlation and updating for larger-scale structures. Non-contact measurement methods such as scanning laser vibrometers provide high-resolution sensing capacity without the mass-loading effect; however, they make sequential measurements that require considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation, optical flow), video camera based measurements have been successfully used for vibration measurements and subsequent modal analysis, based on techniques such as the digital image correlation (DIC) and the point-tracking. However, they typically require speckle pattern or high-contrast markers to be placed on the surface of structures, which poses challenges when the measurement area is large or inaccessible. This work explores advanced computer vision and video processing algorithms to develop a novel video measurement and vision-based operational (output-only) modal analysis method that alleviate the need of structural surface preparation associated with existing vision-based methods and can be implemented in a relatively efficient and autonomous manner with little

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 bilingual child learns social communication skills through video modeling-a single case study in a norwegian school setting

Directory of Open Access Journals (Sweden)

Meral Özerk

2015-09-01

Full Text Available Video modeling is one of the recognized methods used in the training and teaching of children with Autism Spectrum Disorders (ASD. The model’s theoretical base stems from Albert Bandura's (1977; 1986 social learning theory in which he asserts that children can learn many skills and behaviors observationally through modeling. One can assume that by observing others, a child with ASD can construct an idea of how new behaviors are performed, and on later occasions this mentally and visually constructed information will serve as a guide for his/her way of behaving. There are two types of methods for model learning: 1 In Vivo Modeling and 2 Video Modeling. These can be used a to teach children with ASD skills that are not yet in their behavioral repertoire and / or b to improve the children's emerging behaviors or skills. In the case of linguistic minority children at any stage of their bilingual development, it has been presumed that some of their behaviors that can be interpreted as attitude or culture-related actions. This approach, however, can sometimes delay referral, diagnosis, and intervention. In our project, we used Video Modeling and achieved positive results with regard to teaching social communication skills and target behavior to an eleven year-old bilingual boy with ASD. Our study also reveals that through Video Modeling, children with ASD can learn desirable behavioral skills as by-products. Video Modeling can also contribute positively to the social inclusion of bilingual children with ASD in school settings. In other words, bilingual children with ASD can transfer the social communication skills and targeted behaviors they learn through second-language at school to a first-language milieu.

Low-complexity video encoding method for wireless image transmission in capsule endoscope.

Science.gov (United States)

Takizawa, Kenichi; Hamaguchi, Kiyoshi

2010-01-01

This paper presents a low-complexity video encoding method applicable for wireless image transmission in capsule endoscopes. This encoding method is based on Wyner-Ziv theory, in which side information available at a transmitter is treated as side information at its receiver. Therefore complex processes in video encoding, such as estimation of the motion vector, are moved to the receiver side, which has a larger-capacity battery. As a result, the encoding process is only to decimate coded original data through channel coding. We provide a performance evaluation for a low-density parity check (LDPC) coding method in the AWGN channel.

Photo-acoustic and video-acoustic methods for sensing distant sound sources

Science.gov (United States)

Slater, Dan; Kozacik, Stephen; Kelmelis, Eric

2017-05-01

Long range telescopic video imagery of distant terrestrial scenes, aircraft, rockets and other aerospace vehicles can be a powerful observational tool. But what about the associated acoustic activity? A new technology, Remote Acoustic Sensing (RAS), may provide a method to remotely listen to the acoustic activity near these distant objects. Local acoustic activity sometimes weakly modulates the ambient illumination in a way that can be remotely sensed. RAS is a new type of microphone that separates an acoustic transducer into two spatially separated components: 1) a naturally formed in situ acousto-optic modulator (AOM) located within the distant scene and 2) a remote sensing readout device that recovers the distant audio. These two elements are passively coupled over long distances at the speed of light by naturally occurring ambient light energy or other electromagnetic fields. Stereophonic, multichannel and acoustic beam forming are all possible using RAS techniques and when combined with high-definition video imagery it can help to provide a more cinema like immersive viewing experience. A practical implementation of a remote acousto-optic readout device can be a challenging engineering problem. The acoustic influence on the optical signal is generally weak and often with a strong bias term. The optical signal is further degraded by atmospheric seeing turbulence. In this paper, we consider two fundamentally different optical readout approaches: 1) a low pixel count photodiode based RAS photoreceiver and 2) audio extraction directly from a video stream. Most of our RAS experiments to date have used the first method for reasons of performance and simplicity. But there are potential advantages to extracting audio directly from a video stream. These advantages include the straight forward ability to work with multiple AOMs (useful for acoustic beam forming), simpler optical configurations, and a potential ability to use certain preexisting video recordings. However

Web-enabled video-feedback: a method to reflect on the communication skills of experienced physicians.

NARCIS (Netherlands)

Noordman, J.; Verhaak, P.; Dulmen, S. van

2011-01-01

OBJECTIVE: To describe our web-enabled video-feedback method designed to reflect on the communication skills of experienced physicians. METHODS: Participating physicians (n=28) received a 'personal web link' to two of their video-recorded consultations. After watching the consultations physicians

A Collaborative Video Sketching Model in the Making

DEFF Research Database (Denmark)

Gundersen, Peter Bukovica; Ørngreen, Rikke; Hautopp, Heidi

model, where we explore the relation between the educational research design team, their sketching and video sketching activities. The results show how sketching can be done in different modes and how it supports thinking, communication, reflection and distributed cognition in design teams when......The literature on design research emphasizes working in iterative cycles that investigate and explore many ideas and alternative designs. However, these cycles are seldom applied or documented in educational research papers. In this paper, we illustrate the development process of a video sketching...

A collaborative video sketching model in the making

DEFF Research Database (Denmark)

Gundersen, Peter; Ørngreen, Rikke; Henningsen, Birgitte

2018-01-01

model, where we explore the relation between the educational research design team, their sketching and video sketching activities. The results show how sketching can be done in different modes and how it supports thinking, communication, reflection and distributed cognition in design teams when......The literature on design research emphasizes working in iterative cycles that investigate and explore many ideas and alternative designs. However, these cycles are seldom applied or documented in educational research papers. In this paper, we illustrate the development process of a video sketching...

Exploring inter-frame correlation analysis and wavelet-domain modeling for real-time caption detection in streaming video

Science.gov (United States)

Li, Jia; Tian, Yonghong; Gao, Wen

2008-01-01

In recent years, the amount of streaming video has grown rapidly on the Web. Often, retrieving these streaming videos offers the challenge of indexing and analyzing the media in real time because the streams must be treated as effectively infinite in length, thus precluding offline processing. Generally speaking, captions are important semantic clues for video indexing and retrieval. However, existing caption detection methods often have difficulties to make real-time detection for streaming video, and few of them concern on the differentiation of captions from scene texts and scrolling texts. In general, these texts have different roles in streaming video retrieval. To overcome these difficulties, this paper proposes a novel approach which explores the inter-frame correlation analysis and wavelet-domain modeling for real-time caption detection in streaming video. In our approach, the inter-frame correlation information is used to distinguish caption texts from scene texts and scrolling texts. Moreover, wavelet-domain Generalized Gaussian Models (GGMs) are utilized to automatically remove non-text regions from each frame and only keep caption regions for further processing. Experiment results show that our approach is able to offer real-time caption detection with high recall and low false alarm rate, and also can effectively discern caption texts from the other texts even in low resolutions.

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.

Priority-based methods for reducing the impact of packet loss on HEVC encoded video streams

Science.gov (United States)

Nightingale, James; Wang, Qi; Grecos, Christos

2013-02-01

The rapid growth in the use of video streaming over IP networks has outstripped the rate at which new network infrastructure has been deployed. These bandwidth-hungry applications now comprise a significant part of all Internet traffic and present major challenges for network service providers. The situation is more acute in mobile networks where the available bandwidth is often limited. Work towards the standardisation of High Efficiency Video Coding (HEVC), the next generation video coding scheme, is currently on track for completion in 2013. HEVC offers the prospect of a 50% improvement in compression over the current H.264 Advanced Video Coding standard (H.264/AVC) for the same quality. However, there has been very little published research on HEVC streaming or the challenges of delivering HEVC streams in resource-constrained network environments. In this paper we consider the problem of adapting an HEVC encoded video stream to meet the bandwidth limitation in a mobile networks environment. Video sequences were encoded using the Test Model under Consideration (TMuC HM6) for HEVC. Network abstraction layers (NAL) units were packetized, on a one NAL unit per RTP packet basis, and transmitted over a realistic hybrid wired/wireless testbed configured with dynamically changing network path conditions and multiple independent network paths from the streamer to the client. Two different schemes for the prioritisation of RTP packets, based on the NAL units they contain, have been implemented and empirically compared using a range of video sequences, encoder configurations, bandwidths and network topologies. In the first prioritisation method the importance of an RTP packet was determined by the type of picture and the temporal switching point information carried in the NAL unit header. Packets containing parameter set NAL units and video coding layer (VCL) NAL units of the instantaneous decoder refresh (IDR) and the clean random access (CRA) pictures were given the

Scalable gastroscopic video summarization via similar-inhibition dictionary selection.

Science.gov (United States)

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

2016-01-01

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

Semantic-based surveillance video retrieval.

Science.gov (United States)

Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

Operation quality assessment model for video conference system

Science.gov (United States)

Du, Bangshi; Qi, Feng; Shao, Sujie; Wang, Ying; Li, Weijian

2018-01-01

Video conference system has become an important support platform for smart grid operation and management, its operation quality is gradually concerning grid enterprise. First, the evaluation indicator system covering network, business and operation maintenance aspects was established on basis of video conference system's operation statistics. Then, the operation quality assessment model combining genetic algorithm with regularized BP neural network was proposed, which outputs operation quality level of the system within a time period and provides company manager with some optimization advice. The simulation results show that the proposed evaluation model offers the advantages of fast convergence and high prediction accuracy in contrast with regularized BP neural network, and its generalization ability is superior to LM-BP neural network and Bayesian BP neural network.

Using Video Modeling to Teach Young Children with Autism Developmentally Appropriate Play and Connected Speech

Science.gov (United States)

Scheflen, Sarah Clifford; Freeman, Stephanny F. N.; Paparella, Tanya

2012-01-01

Four children with autism were taught play skills through the use of video modeling. Video instruction was used to model play and appropriate language through a developmental sequence of play levels integrated with language techniques. Results showed that children with autism could successfully use video modeling to learn how to play appropriately…

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.

The Effects of Video Self-Modeling on High School Students with Emotional and Behavioral Disturbances

Science.gov (United States)

Chu, Szu-Yin; Baker, Sonia

2015-01-01

Video self-modeling has been proven to be effective with other populations with challenging behaviors, but only a few studies of video self-modeling have been conducted with high school students with emotional and behavioral disorders. This study aimed to focus on analyzing the effects of video self-modeling on four high school students with…

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.

Improved virtual channel noise model for transform domain Wyner-Ziv video coding

DEFF Research Database (Denmark)

Huang, Xin; Forchhammer, Søren

2009-01-01

Distributed video coding (DVC) has been proposed as a new video coding paradigm to deal with lossy source coding using side information to exploit the statistics at the decoder to reduce computational demands at the encoder. A virtual channel noise model is utilized at the decoder to estimate...... the noise distribution between the side information frame and the original frame. This is one of the most important aspects influencing the coding performance of DVC. Noise models with different granularity have been proposed. In this paper, an improved noise model for transform domain Wyner-Ziv video...... coding is proposed, which utilizes cross-band correlation to estimate the Laplacian parameters more accurately. Experimental results show that the proposed noise model can improve the rate-distortion (RD) performance....

Video Self-Modelling: An Intervention for Children with Behavioural Difficulties

Science.gov (United States)

Regan, Helen; Howe, Julia

2017-01-01

There has recently been a growth in interest in the use of video technology in the practice of educational psychologists. This research explores the effects of a video self-modelling (VSM) intervention on the behaviours of a child in mainstream education using a single case study design set within a behaviourist paradigm. VSM is a behavioural…

Teaching physical activities to students with significant disabilities using video modeling.

Science.gov (United States)

Cannella-Malone, Helen I; Mizrachi, Sharona V; Sabielny, Linsey M; Jimenez, Eliseo D

2013-06-01

The objective of this study was to examine the effectiveness of video modeling on teaching physical activities to three adolescents with significant disabilities. The study implemented a multiple baseline across six physical activities (three per student): jumping rope, scooter board with cones, ladder drill (i.e., feet going in and out), ladder design (i.e., multiple steps), shuttle run, and disc ride. Additional prompt procedures (i.e., verbal, gestural, visual cues, and modeling) were implemented within the study. After the students mastered the physical activities, we tested to see if they would link the skills together (i.e., complete an obstacle course). All three students made progress learning the physical activities, but only one learned them with video modeling alone (i.e., without error correction). Video modeling can be an effective tool for teaching students with significant disabilities various physical activities, though additional prompting procedures may be needed.

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.

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

DEFF Research Database (Denmark)

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

2011-01-01

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

Modeling the Quality of Videos Displayed With Local Dimming Backlight at Different Peak White and Ambient Light Levels

DEFF Research Database (Denmark)

Mantel, Claire; Søgaard, Jacob; Bech, Søren

2016-01-01

is computed using a model of the display. Widely used objective quality metrics are applied based on the rendering models of the videos to predict the subjective evaluations. As these predictions are not satisfying, three machine learning methods are applied: partial least square regression, elastic net......This paper investigates the impact of ambient light and peak white (maximum brightness of a display) on the perceived quality of videos displayed using local backlight dimming. Two subjective tests providing quality evaluations are presented and analyzed. The analyses of variance show significant...

Method and device for decoding coded digital video signals

NARCIS (Netherlands)

2000-01-01

The invention relates to a video coding method and system including a quantization and coding sub-assembly (38) in which a quantization parameter is controlled by another parameter defined as being in direct relation with the dynamic range value of the data contained in given blocks of pixels.

Impairment-Factor-Based Audiovisual Quality Model for IPTV: Influence of Video Resolution, Degradation Type, and Content Type

Directory of Open Access Journals (Sweden)

Garcia MN

2011-01-01

Full Text Available This paper presents an audiovisual quality model for IPTV services. The model estimates the audiovisual quality of standard and high definition video as perceived by the user. The model is developed for applications such as network planning and packet-layer quality monitoring. It mainly covers audio and video compression artifacts and impairments due to packet loss. The quality tests conducted for model development demonstrate a mutual influence of the perceived audio and video quality, and the predominance of the video quality for the overall audiovisual quality. The balance between audio quality and video quality, however, depends on the content, the video format, and the audio degradation type. The proposed model is based on impairment factors which quantify the quality-impact of the different degradations. The impairment factors are computed from parameters extracted from the bitstream or packet headers. For high definition video, the model predictions show a correlation with unknown subjective ratings of 95%. For comparison, we have developed a more classical audiovisual quality model which is based on the audio and video qualities and their interaction. Both quality- and impairment-factor-based models are further refined by taking the content-type into account. At last, the different model variants are compared with modeling approaches described in the literature.

Stochastic modeling of soundtrack for efficient segmentation and indexing of video

Science.gov (United States)

Naphade, Milind R.; Huang, Thomas S.

1999-12-01

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

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.

Science on TeacherTube: A Mixed Methods Analysis of Teacher Produced Video

Science.gov (United States)

Chmiel, Margaret (Marjee)

Increased bandwidth, inexpensive video cameras and easy-to-use video editing software have made social media sites featuring user generated video (UGV) an increasingly popular vehicle for online communication. As such, UGV have come to play a role in education, both formal and informal, but there has been little research on this topic in scholarly literature. In this mixed-methods study, a content and discourse analysis are used to describe the most successful UGV in the science channel of an education-focused site called TeacherTube. The analysis finds that state achievement tests, and their focus on vocabulary and recall-level knowledge, drive much of the content found on TeacherTube.

Detection of goal events in soccer videos

Science.gov (United States)

Kim, Hyoung-Gook; Roeber, Steffen; Samour, Amjad; Sikora, Thomas

2005-01-01

In this paper, we present an automatic extraction of goal events in soccer videos by using audio track features alone without relying on expensive-to-compute video track features. The extracted goal events can be used for high-level indexing and selective browsing of soccer videos. The detection of soccer video highlights using audio contents comprises three steps: 1) extraction of audio features from a video sequence, 2) event candidate detection of highlight events based on the information provided by the feature extraction Methods and the Hidden Markov Model (HMM), 3) goal event selection to finally determine the video intervals to be included in the summary. For this purpose we compared the performance of the well known Mel-scale Frequency Cepstral Coefficients (MFCC) feature extraction method vs. MPEG-7 Audio Spectrum Projection feature (ASP) extraction method based on three different decomposition methods namely Principal Component Analysis( PCA), Independent Component Analysis (ICA) and Non-Negative Matrix Factorization (NMF). To evaluate our system we collected five soccer game videos from various sources. In total we have seven hours of soccer games consisting of eight gigabytes of data. One of five soccer games is used as the training data (e.g., announcers' excited speech, audience ambient speech noise, audience clapping, environmental sounds). Our goal event detection results are encouraging.

Video Self-Modeling as an Intervention Strategy for Individuals with Autism Spectrum Disorders

Science.gov (United States)

Gelbar, Nicholas W.; Anderson, Candace; McCarthy, Scott; Buggey, Tom

2012-01-01

Video self-modeling demonstrates promise as an intervention strategy to improve outcomes in individuals with autism spectrum disorders. This article summarizes the empirical evidence supporting the use of video self-modeling with individuals with autism spectrum disorders to increase language and communication, increase social skills, modify…

Video enhancement : content classification and model selection

NARCIS (Netherlands)

Hu, H.

2010-01-01

The purpose of video enhancement is to improve the subjective picture quality. The field of video enhancement includes a broad category of research topics, such as removing noise in the video, highlighting some specified features and improving the appearance or visibility of the video content. The

Developing model-making and model-breaking skills using direct measurement video-based activities

Science.gov (United States)

Vonk, Matthew; Bohacek, Peter; Militello, Cheryl; Iverson, Ellen

2017-12-01

This study focuses on student development of two important laboratory skills in the context of introductory college-level physics. The first skill, which we call model making, is the ability to analyze a phenomenon in a way that produces a quantitative multimodal model. The second skill, which we call model breaking, is the ability to critically evaluate if the behavior of a system is consistent with a given model. This study involved 116 introductory physics students in four different sections, each taught by a different instructor. All of the students within a given class section participated in the same instruction (including labs) with the exception of five activities performed throughout the semester. For those five activities, each class section was split into two groups; one group was scaffolded to focus on model-making skills and the other was scaffolded to focus on model-breaking skills. Both conditions involved direct measurement videos. In some cases, students could vary important experimental parameters within the video like mass, frequency, and tension. Data collected at the end of the semester indicate that students in the model-making treatment group significantly outperformed the other group on the model-making skill despite the fact that both groups shared a common physical lab experience. Likewise, the model-breaking treatment group significantly outperformed the other group on the model-breaking skill. This is important because it shows that direct measurement video-based instruction can help students acquire science-process skills, which are critical for scientists, and which are a key part of current science education approaches such as the Next Generation Science Standards and the Advanced Placement Physics 1 course.

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...

Effectiveness of Video Modeling Provided by Mothers in Teaching Play Skills to Children with Autism

Science.gov (United States)

Besler, Fatma; Kurt, Onur

2016-01-01

Video modeling is an evidence-based practice that can be used to provide instruction to individuals with autism. Studies show that this instructional practice is effective in teaching many types of skills such as self-help skills, social skills, and academic skills. However, in previous studies, videos used in the video modeling process were…

Playing with Process: Video Game Choice as a Model of Behavior

Science.gov (United States)

Waelchli, Paul

2010-01-01

Popular culture experience in video games creates avenues to practice information literacy skills and model research in a real-world setting. Video games create a unique popular culture experience where players can invest dozens of hours on one game, create characters to identify with, organize skill sets and plot points, collaborate with people…

Real-World Implementation of Video Outpatient Consultations at Macro, Meso, and Micro Levels: Mixed-Method Study.

Science.gov (United States)

Greenhalgh, Trisha; Shaw, Sara; Wherton, Joseph; Vijayaraghavan, Shanti; Morris, Joanne; Bhattacharya, Satya; Hanson, Philippa; Campbell-Richards, Desirée; Ramoutar, Seendy; Collard, Anna; Hodkinson, Isabel

2018-04-17

There is much interest in virtual consultations using video technology. Randomized controlled trials have shown video consultations to be acceptable, safe, and effective in selected conditions and circumstances. However, this model has rarely been mainstreamed and sustained in real-world settings. The study sought to (1) define good practice and inform implementation of video outpatient consultations and (2) generate transferable knowledge about challenges to scaling up and routinizing this service model. A multilevel, mixed-method study of Skype video consultations (micro level) was embedded in an organizational case study (meso level), taking account of national context and wider influences (macro level). The study followed the introduction of video outpatient consultations in three clinical services (diabetes, diabetes antenatal, and cancer surgery) in a National Health Service trust (covering three hospitals) in London, United Kingdom. Data sources included 36 national-level stakeholders (exploratory and semistructured interviews), longitudinal organizational ethnography (300 hours of observations; 24 staff interviews), 30 videotaped remote consultations, 17 audiotaped face-to-face consultations, and national and local documents. Qualitative data, analyzed using sociotechnical change theories, addressed staff and patient experience and organizational and system drivers. Quantitative data, analyzed via descriptive statistics, included uptake of video consultations by staff and patients and microcategorization of different kinds of talk (using the Roter interaction analysis system). When clinical, technical, and practical preconditions were met, video consultations appeared safe and were popular with some patients and staff. Compared with face-to-face consultations for similar conditions, video consultations were very slightly shorter, patients did slightly more talking, and both parties sometimes needed to make explicit things that typically remained implicit in

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

Effects of video modeling with video feedback on vocational skills of adults with autism spectrum disorder.

Science.gov (United States)

English, Derek L; Gounden, Sadhana; Dagher, Richard E; Chan, Shu Fen; Furlonger, Brett E; Anderson, Angelika; Moore, Dennis W

2017-11-01

To examine the effectiveness of a video modeling (VM) with video feedback (VFB) intervention to teach vocational gardening skills to three adults with autism spectrum disorder (ASD). A multiple probe design across skills was used to assess the effects of the intervention on the three participants' ability to perform skills accurately. The use of VM with VFB led to improvements across skills for two of the participants. The third participant required video prompting (VP) for successful skill acquisition. Skill performance generalized across personnel and settings for two of the participants, but it was not assessed for the third. Skill performance maintained at follow-up for all three participants. Social validity data gathered from participants, parents, and co-workers were positive. These findings suggest that VM with VFB and VP with VFB were effective and socially acceptable interventions for teaching vocational gardening skills to young adults with ASD.

Video Modeling Training Effects on Types of Attention Delivered by Educational Care-Providers.

Science.gov (United States)

Taber, Traci A; Lambright, Nathan; Luiselli, James K

2017-06-01

We evaluated the effects of abbreviated (i.e., one-session) video modeling on delivery of student-preferred attention by educational care-providers. The video depicted a novel care-provider interacting with and delivering attention to the student. Within a concurrent multiple baseline design, video modeling increased delivery of the targeted attention for all participants as well as their delivery of another type of attention that was not trained although these effects were variable within and between care-providers. We discuss the clinical and training implications from these findings.

A model for measurement of noise in CCD digital-video cameras

International Nuclear Information System (INIS)

Irie, K; Woodhead, I M; McKinnon, A E; Unsworth, K

2008-01-01

This study presents a comprehensive measurement of CCD digital-video camera noise. Knowledge of noise detail within images or video streams allows for the development of more sophisticated algorithms for separating true image content from the noise generated in an image sensor. The robustness and performance of an image-processing algorithm is fundamentally limited by sensor noise. The individual noise sources present in CCD sensors are well understood, but there has been little literature on the development of a complete noise model for CCD digital-video cameras, incorporating the effects of quantization and demosaicing

A new method for robust video watermarking resistant against key estimation attacks

Science.gov (United States)

Mitekin, Vitaly

2015-12-01

This paper presents a new method for high-capacity robust digital video watermarking and algorithms of embedding and extraction of watermark based on this method. Proposed method uses password-based two-dimensional pseudonoise arrays for watermark embedding, making brute-force attacks aimed at steganographic key retrieval mostly impractical. Proposed algorithm for 2-dimensional "noise-like" watermarking patterns generation also allows to significantly decrease watermark collision probability ( i.e. probability of correct watermark detection and extraction using incorrect steganographic key or password).. Experimental research provided in this work also shows that simple correlation-based watermark detection procedure can be used, providing watermark robustness against lossy compression and watermark estimation attacks. At the same time, without decreasing robustness of embedded watermark, average complexity of the brute-force key retrieval attack can be increased to 1014 watermark extraction attempts (compared to 104-106 for a known robust watermarking schemes). Experimental results also shows that for lowest embedding intensity watermark preserves it's robustness against lossy compression of host video and at the same time preserves higher video quality (PSNR up to 51dB) compared to known wavelet-based and DCT-based watermarking algorithms.

A Practical Strategy for Teaching a Child with Autism to Attend to and Imitate a Portable Video Model

Science.gov (United States)

Plavnick, Joshua B.

2012-01-01

Video modeling is an effective and efficient methodology for teaching new skills to individuals with autism. New technology may enhance video modeling as smartphones or tablet computers allow for portable video displays. However, the reduced screen size may decrease the likelihood of attending to the video model for some children. The present…

Video Super-Resolution via Bidirectional Recurrent Convolutional Networks.

Science.gov (United States)

Huang, Yan; Wang, Wei; Wang, Liang

2018-04-01

Super resolving a low-resolution video, namely video super-resolution (SR), is usually handled by either single-image SR or multi-frame SR. Single-Image SR deals with each video frame independently, and ignores intrinsic temporal dependency of video frames which actually plays a very important role in video SR. Multi-Frame SR generally extracts motion information, e.g., optical flow, to model the temporal dependency, but often shows high computational cost. Considering that recurrent neural networks (RNNs) can model long-term temporal dependency of video sequences well, we propose a fully convolutional RNN named bidirectional recurrent convolutional network for efficient multi-frame SR. Different from vanilla RNNs, 1) the commonly-used full feedforward and recurrent connections are replaced with weight-sharing convolutional connections. So they can greatly reduce the large number of network parameters and well model the temporal dependency in a finer level, i.e., patch-based rather than frame-based, and 2) connections from input layers at previous timesteps to the current hidden layer are added by 3D feedforward convolutions, which aim to capture discriminate spatio-temporal patterns for short-term fast-varying motions in local adjacent frames. Due to the cheap convolutional operations, our model has a low computational complexity and runs orders of magnitude faster than other multi-frame SR methods. With the powerful temporal dependency modeling, our model can super resolve videos with complex motions and achieve well performance.

Watch This! A Guide to Implementing Video Modeling in the Classroom

Science.gov (United States)

Wynkoop, Kaylee Stahr

2016-01-01

The video modeling (VM) teaching strategy is one in which a student watches a video of someone performing a specific behavior, skill, or task and is then expected to complete the behavior, skill, or task. This column discusses the variety of ways in which VM has been documented within the literature and supports teacher interest in the strategy by…

The impact of thin models in music videos on adolescent girls' body dissatisfaction.

Science.gov (United States)

Bell, Beth T; Lawton, Rebecca; Dittmar, Helga

2007-06-01

Music videos are a particularly influential, new form of mass media for adolescents, which include the depiction of scantily clad female models whose bodies epitomise the ultra-thin sociocultural ideal for young women. The present study is the first exposure experiment that examines the impact of thin models in music videos on the body dissatisfaction of 16-19-year-old adolescent girls (n=87). First, participants completed measures of positive and negative affect, body image, and self-esteem. Under the guise of a memory experiment, they then either watched three music videos, listened to three songs (from the videos), or learned a list of words. Affect and body image were assessed afterwards. In contrast to the music listening and word-learning conditions, girls who watched the music videos reported significantly elevated scores on an adaptation of the Body Image States Scale after exposure, indicating increased body dissatisfaction. Self-esteem was not found to be a significant moderator of this relationship. Implications and future research are discussed.

A systematic review of methods for studying consumer health YouTube videos, with implications for systematic reviews

Directory of Open Access Journals (Sweden)

Margaret Sampson

2013-09-01

Full Text Available Background. YouTube is an increasingly important medium for consumer health information – with content provided by healthcare professionals, government and non-government organizations, industry, and consumers themselves. It is a rapidly developing area of study for healthcare researchers. We examine the methods used in reviews of YouTube consumer health videos to identify trends and best practices.Methods and Materials. Published reviews of consumer-oriented health-related YouTube videos were identified through PubMed. Data extracted from these studies included type of journal, topic, characteristics of the search, methods of review including number of reviewers and method to achieve consensus between reviewers, inclusion and exclusion criteria, characteristics of the videos reported, ethical oversight, and follow-up.Results. Thirty-three studies were identified. Most were recent and published in specialty journals. Typically, these included more than 100 videos, and were examined by multiple reviewers. Most studies described characteristics of the videos, number of views, and sometime characteristics of the viewers. Accuracy of portrayal of the health issue under consideration was a common focus.Conclusion. Optimal transparency and reproducibility of studies of YouTube health-related videos can be achieved by following guidance designed for systematic review reporting, with attention to several elements specific to the video medium. Particularly when seeking to replicate consumer viewing behavior, investigators should consider the method used to select search terms, and use a snowballing rather than a sequential screening approach. Discontinuation protocols for online screening of relevance ranked search results is an area identified for further development.

A systematic review of methods for studying consumer health YouTube videos, with implications for systematic reviews

Science.gov (United States)

Cumber, Jordi; Li, Claudia; Pound, Catherine M.; Fuller, Ann; Harrison, Denise

2013-01-01

Background. YouTube is an increasingly important medium for consumer health information – with content provided by healthcare professionals, government and non-government organizations, industry, and consumers themselves. It is a rapidly developing area of study for healthcare researchers. We examine the methods used in reviews of YouTube consumer health videos to identify trends and best practices. Methods and Materials. Published reviews of consumer-oriented health-related YouTube videos were identified through PubMed. Data extracted from these studies included type of journal, topic, characteristics of the search, methods of review including number of reviewers and method to achieve consensus between reviewers, inclusion and exclusion criteria, characteristics of the videos reported, ethical oversight, and follow-up. Results. Thirty-three studies were identified. Most were recent and published in specialty journals. Typically, these included more than 100 videos, and were examined by multiple reviewers. Most studies described characteristics of the videos, number of views, and sometime characteristics of the viewers. Accuracy of portrayal of the health issue under consideration was a common focus. Conclusion. Optimal transparency and reproducibility of studies of YouTube health-related videos can be achieved by following guidance designed for systematic review reporting, with attention to several elements specific to the video medium. Particularly when seeking to replicate consumer viewing behavior, investigators should consider the method used to select search terms, and use a snowballing rather than a sequential screening approach. Discontinuation protocols for online screening of relevance ranked search results is an area identified for further development. PMID:24058879

A systematic review of methods for studying consumer health YouTube videos, with implications for systematic reviews.

Science.gov (United States)

Sampson, Margaret; Cumber, Jordi; Li, Claudia; Pound, Catherine M; Fuller, Ann; Harrison, Denise

2013-01-01

Background. YouTube is an increasingly important medium for consumer health information - with content provided by healthcare professionals, government and non-government organizations, industry, and consumers themselves. It is a rapidly developing area of study for healthcare researchers. We examine the methods used in reviews of YouTube consumer health videos to identify trends and best practices. Methods and Materials. Published reviews of consumer-oriented health-related YouTube videos were identified through PubMed. Data extracted from these studies included type of journal, topic, characteristics of the search, methods of review including number of reviewers and method to achieve consensus between reviewers, inclusion and exclusion criteria, characteristics of the videos reported, ethical oversight, and follow-up. Results. Thirty-three studies were identified. Most were recent and published in specialty journals. Typically, these included more than 100 videos, and were examined by multiple reviewers. Most studies described characteristics of the videos, number of views, and sometime characteristics of the viewers. Accuracy of portrayal of the health issue under consideration was a common focus. Conclusion. Optimal transparency and reproducibility of studies of YouTube health-related videos can be achieved by following guidance designed for systematic review reporting, with attention to several elements specific to the video medium. Particularly when seeking to replicate consumer viewing behavior, investigators should consider the method used to select search terms, and use a snowballing rather than a sequential screening approach. Discontinuation protocols for online screening of relevance ranked search results is an area identified for further development.

Effects of video modeling on communicative social skills of college students with Asperger syndrome.

Science.gov (United States)

Mason, Rose A; Rispoli, Mandy; Ganz, Jennifer B; Boles, Margot B; Orr, Kristie

2012-01-01

Empirical support regarding effective interventions for individuals with autism spectrum disorder (ASD) within a postsecondary community is limited. Video modeling, an empirically supported intervention for children and adolescents with ASD, may prove effective in addressing the needs of individuals with ASD in higher education. This study evaluated the effects of video modeling without additional treatment components to improve social-communicative skills, specifically, eye contact, facial expression, and conversational turntaking in college students with ASD. This study utilized a multiple baseline single-case design across behaviors for two post-secondary students with ASD to evaluate the effects of the video modeling intervention. Large effect sizes and statistically significant change across all targeted skills for one participant and eye contact and turntaking for the other participant were obtained. The use of video modeling without additional intervention may increase the social skills of post-secondary students with ASD. Implications for future research are discussed.

No-Reference Video Quality Assessment using Codec Analysis

DEFF Research Database (Denmark)

Søgaard, Jacob; Forchhammer, Søren; Korhonen, Jari

2015-01-01

types of videos, estimating the level of quantization used in the I-frames, and exploiting this information to assess the video quality. In order to do this for H.264/AVC, the distribution of the DCT-coefficients after intra-prediction and deblocking are modeled. To obtain VQA features for H.264/AVC, we......A no-reference video quality assessment (VQA) method is presented for videos distorted by H.264/AVC and MPEG-2. The assessment is performed without access to the bit-stream. Instead we analyze and estimate coefficients based on decoded pixels. The approach involves distinguishing between the two...... propose a novel estimation method of the quantization in H.264/AVC videos without bitstream access, which can also be used for Peak Signalto-Noise Ratio (PSNR) estimation. The results from the MPEG-2 and H.264/AVC analysis are mapped to a perceptual measure of video quality by Support Vector Regression...

Video-based noncooperative iris image segmentation.

Science.gov (United States)

Du, Yingzi; Arslanturk, Emrah; Zhou, Zhi; Belcher, Craig

2011-02-01

In this paper, we propose a video-based noncooperative iris image segmentation scheme that incorporates a quality filter to quickly eliminate images without an eye, employs a coarse-to-fine segmentation scheme to improve the overall efficiency, uses a direct least squares fitting of ellipses method to model the deformed pupil and limbic boundaries, and develops a window gradient-based method to remove noise in the iris region. A remote iris acquisition system is set up to collect noncooperative iris video images. An objective method is used to quantitatively evaluate the accuracy of the segmentation results. The experimental results demonstrate the effectiveness of this method. The proposed method would make noncooperative iris recognition or iris surveillance possible.

Advanced methods for image registration applied to JET videos

Energy Technology Data Exchange (ETDEWEB)

Craciunescu, Teddy, E-mail: teddy.craciunescu@jet.uk [EURATOM-MEdC Association, NILPRP, Bucharest (Romania); Murari, Andrea [Consorzio RFX, Associazione EURATOM-ENEA per la Fusione, Padova (Italy); Gelfusa, Michela [Associazione EURATOM-ENEA – University of Rome “Tor Vergata”, Roma (Italy); Tiseanu, Ion; Zoita, Vasile [EURATOM-MEdC Association, NILPRP, Bucharest (Romania); Arnoux, Gilles [EURATOM/CCFE Fusion Association, Culham Science Centre, Abingdon, Oxon (United Kingdom)

2015-10-15

Graphical abstract: - Highlights: • Development of an image registration method for JET IR and fast visible cameras. • Method based on SIFT descriptors and coherent point drift points set registration technique. • Method able to deal with extremely noisy images and very low luminosity images. • Computation time compatible with the inter-shot analysis. - Abstract: The last years have witnessed a significant increase in the use of digital cameras on JET. They are routinely applied for imaging in the IR and visible spectral regions. One of the main technical difficulties in interpreting the data of camera based diagnostics is the presence of movements of the field of view. Small movements occur due to machine shaking during normal pulses while large ones may arise during disruptions. Some cameras show a correlation of image movement with change of magnetic field strength. For deriving unaltered information from the videos and for allowing correct interpretation an image registration method, based on highly distinctive scale invariant feature transform (SIFT) descriptors and on the coherent point drift (CPD) points set registration technique, has been developed. The algorithm incorporates a complex procedure for rejecting outliers. The method has been applied for vibrations correction to videos collected by the JET wide angle infrared camera and for the correction of spurious rotations in the case of the JET fast visible camera (which is equipped with an image intensifier). The method has proved to be able to deal with the images provided by this camera frequently characterized by low contrast and a high level of blurring and noise.

A Bilingual Child Learns Social Communication Skills through Video Modeling--A Single Case Study in a Norwegian School Setting

Science.gov (United States)

Özerk, Meral; Özerk, Kamil

2015-01-01

"Video modeling" is one of the recognized methods used in the training and teaching of children with Autism Spectrum Disorders (ASD). The model's theoretical base stems from Albert Bandura's (1977; 1986) social learning theory in which he asserts that children can learn many skills and behaviors observationally through modeling. One can…

An evaluation of preference for video and in vivo modeling.

Science.gov (United States)

Geiger, Kaneen B; Leblanc, Linda A; Dillon, Courtney M; Bates, Stephanie L

2010-01-01

We assessed preference for video or in vivo modeling using a concurrent-chains arrangement with 3 children with autism. The two modeling conditions produced similar acquisition rates and no differential selection (i.e., preference) for all 3 participants.

Nonintrusive Method Based on Neural Networks for Video Quality of Experience Assessment

Directory of Open Access Journals (Sweden)

Diego José Luis Botia Valderrama

2016-01-01

Full Text Available The measurement and evaluation of the QoE (Quality of Experience have become one of the main focuses in the telecommunications to provide services with the expected quality for their users. However, factors like the network parameters and codification can affect the quality of video, limiting the correlation between the objective and subjective metrics. The above increases the complexity to evaluate the real quality of video perceived by users. In this paper, a model based on artificial neural networks such as BPNNs (Backpropagation Neural Networks and the RNNs (Random Neural Networks is applied to evaluate the subjective quality metrics MOS (Mean Opinion Score and the PSNR (Peak Signal Noise Ratio, SSIM (Structural Similarity Index Metric, VQM (Video Quality Metric, and QIBF (Quality Index Based Frame. The proposed model allows establishing the QoS (Quality of Service based in the strategy Diffserv. The metrics were analyzed through Pearson’s and Spearman’s correlation coefficients, RMSE (Root Mean Square Error, and outliers rate. Correlation values greater than 90% were obtained for all the evaluated metrics.

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...

Modeling the video distribution link in the Next Generation Optical Access Networks

International Nuclear Information System (INIS)

Amaya, F; Cardenas, A; Tafur, I

2011-01-01

In this work we present a model for the design and optimization of the video distribution link in the next generation optical access network. We analyze the video distribution performance in a SCM-WDM link, including the noise, the distortion and the fiber optic nonlinearities. Additionally, we consider in the model the effect of distributed Raman amplification, used to extent the capacity and the reach of the optical link. In the model, we use the nonlinear Schroedinger equation with the purpose to obtain capacity limitations and design constrains of the next generation optical access networks.

Continuous Video Modeling to Assist with Completion of Multi-Step Home Living Tasks 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

The current study evaluated a relatively new video-based procedure, continuous video modeling (CVM), to teach multi-step cleaning tasks to high school students with moderate intellectual disability. CVM in contrast to video modeling and video prompting allows repetition of the video model (looping) as many times as needed while the user completes…

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.

Variability in the Effectiveness of a Video Modeling Intervention Package for Children with Autism

Science.gov (United States)

Plavnick, Joshua B.; MacFarland, Mari C.; Ferreri, Summer J.

2015-01-01

Video modeling is an evidence-based instructional strategy for teaching a variety of skills to individuals with autism. Despite the effectiveness of this strategy, there is some uncertainty regarding the conditions under which video modeling is likely to be effective. The present investigation examined the differential effectiveness of video…

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.

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).

Surgical gesture classification from video and kinematic data.

Science.gov (United States)

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

2013-10-01

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

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.

Real-Time Human Detection for Aerial Captured Video Sequences via Deep Models

Directory of Open Access Journals (Sweden)

Nouar AlDahoul

2018-01-01

Full Text Available Human detection in videos plays an important role in various real life applications. Most of traditional approaches depend on utilizing handcrafted features which are problem-dependent and optimal for specific tasks. Moreover, they are highly susceptible to dynamical events such as illumination changes, camera jitter, and variations in object sizes. On the other hand, the proposed feature learning approaches are cheaper and easier because highly abstract and discriminative features can be produced automatically without the need of expert knowledge. In this paper, we utilize automatic feature learning methods which combine optical flow and three different deep models (i.e., supervised convolutional neural network (S-CNN, pretrained CNN feature extractor, and hierarchical extreme learning machine for human detection in videos captured using a nonstatic camera on an aerial platform with varying altitudes. The models are trained and tested on the publicly available and highly challenging UCF-ARG aerial dataset. The comparison between these models in terms of training, testing accuracy, and learning speed is analyzed. The performance evaluation considers five human actions (digging, waving, throwing, walking, and running. Experimental results demonstrated that the proposed methods are successful for human detection task. Pretrained CNN produces an average accuracy of 98.09%. S-CNN produces an average accuracy of 95.6% with soft-max and 91.7% with Support Vector Machines (SVM. H-ELM has an average accuracy of 95.9%. Using a normal Central Processing Unit (CPU, H-ELM’s training time takes 445 seconds. Learning in S-CNN takes 770 seconds with a high performance Graphical Processing Unit (GPU.

Smoking, ADHD, and Problematic Video Game Use: A Structural Modeling Approach.

Science.gov (United States)

Lee, Hyo Jin; Tran, Denise D; Morrell, Holly E R

2018-05-01

Problematic video game use (PVGU), or addiction-like use of video games, is associated with physical and mental health problems and problems in social and occupational functioning. Possible correlates of PVGU include frequency of play, cigarette smoking, and attention deficit hyperactivity disorder (ADHD). The aim of the current study was to explore simultaneously the relationships among these variables as well as test whether two separate measures of PVGU measure the same construct, using a structural modeling approach. Secondary data analysis was conducted on 2,801 video game users (M age  = 22.43 years, standard deviation [SD] age  = 4.7; 93 percent male) who completed an online survey. The full model fit the data well: χ 2 (2) = 2.017, p > 0.05; root mean square error of approximation (RMSEA) = 0.002 (90% CI [0.000-0.038]); comparative fit index (CFI) = 1.000; standardized root mean square residual (SRMR) = 0.004; and all standardized residuals video game use explained 41.8 percent of variance in PVGU. Tracking these variables may be useful for PVGU prevention and assessment. Young's Internet Addiction Scale, adapted for video game use, and the Problem Videogame Playing Scale both loaded strongly onto a PVGU factor, suggesting that they measure the same construct, that studies using either measure may be compared to each other, and that both measures may be used as a screener of PVGU.

Modelling audiovisual integration of affect from videos and music.

Science.gov (United States)

Gao, Chuanji; Wedell, Douglas H; Kim, Jongwan; Weber, Christine E; Shinkareva, Svetlana V

2018-05-01

Two experiments examined how affective values from visual and auditory modalities are integrated. Experiment 1 paired music and videos drawn from three levels of valence while holding arousal constant. Experiment 2 included a parallel combination of three levels of arousal while holding valence constant. In each experiment, participants rated their affective states after unimodal and multimodal presentations. Experiment 1 revealed a congruency effect in which stimulus combinations of the same extreme valence resulted in more extreme state ratings than component stimuli presented in isolation. An interaction between music and video valence reflected the greater influence of negative affect. Video valence was found to have a significantly greater effect on combined ratings than music valence. The pattern of data was explained by a five parameter differential weight averaging model that attributed greater weight to the visual modality and increased weight with decreasing values of valence. Experiment 2 revealed a congruency effect only for high arousal combinations and no interaction effects. This pattern was explained by a three parameter constant weight averaging model with greater weight for the auditory modality and a very low arousal value for the initial state. These results demonstrate key differences in audiovisual integration between valence and arousal.

Incremental principal component pursuit for video background modeling

Science.gov (United States)

Rodriquez-Valderrama, Paul A.; Wohlberg, Brendt

2017-03-14

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

Key Issues in Modeling of Complex 3D Structures from Video Sequences

Directory of Open Access Journals (Sweden)

Shengyong Chen

2012-01-01

Full Text Available Construction of three-dimensional structures from video sequences has wide applications for intelligent video analysis. This paper summarizes the key issues of the theory and surveys the recent advances in the state of the art. Reconstruction of a scene object from video sequences often takes the basic principle of structure from motion with an uncalibrated camera. This paper lists the typical strategies and summarizes the typical solutions or algorithms for modeling of complex three-dimensional structures. Open difficult problems are also suggested for further study.

Modeling the video distribution link in the Next Generation Optical Access Networks

DEFF Research Database (Denmark)

Amaya, F.; Cárdenas, A.; Tafur Monroy, Idelfonso

2011-01-01

In this work we present a model for the design and optimization of the video distribution link in the next generation optical access network. We analyze the video distribution performance in a SCM-WDM link, including the noise, the distortion and the fiber optic nonlinearities. Additionally, we...... consider in the model the effect of distributed Raman amplification, used to extent the capacity and the reach of the optical link. In the model, we use the nonlinear Schrödinger equation with the purpose to obtain capacity limitations and design constrains of the next generation optical access networks....

Incorporating Video Modeling into a School-Based Intervention for Students with Autism Spectrum Disorders

Science.gov (United States)

Wilson, Kaitlyn P.

2013-01-01

Purpose: Video modeling is an intervention strategy that has been shown to be effective in improving the social and communication skills of students with autism spectrum disorders, or ASDs. The purpose of this tutorial is to outline empirically supported, step-by-step instructions for the use of video modeling by school-based speech-language…

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

Science.gov (United States)

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

2014-01-01

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

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.

An Improved Mixture-of-Gaussians Background Model with Frame Difference and Blob Tracking in Video Stream

Directory of Open Access Journals (Sweden)

Li Yao

2014-01-01

Full Text Available Modeling background and segmenting moving objects are significant techniques for computer vision applications. Mixture-of-Gaussians (MoG background model is commonly used in foreground extraction in video steam. However considering the case that the objects enter the scenery and stay for a while, the foreground extraction would fail as the objects stay still and gradually merge into the background. In this paper, we adopt a blob tracking method to cope with this situation. To construct the MoG model more quickly, we add frame difference method to the foreground extracted from MoG for very crowded situations. What is more, a new shadow removal method based on RGB color space is proposed.

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.

Prerequisite Skills That Support Learning through Video Modeling

Science.gov (United States)

MacDonald, Rebecca P. F.; Dickson, Chata A.; Martineau, Meaghan; Ahearn, William H.

2015-01-01

The purpose of this study was to evaluate the relationship between tasks that require delayed discriminations such as delayed imitation and delayed matching to sample on acquisition of skills using video modeling. Twenty-nine participants with an ASD diagnosis were assessed on a battery of tasks including both immediate and delayed imitation and…

Participatory Video: Toward a Method, Advocacy and Voice (MAV) Framework

Science.gov (United States)

Sitter, Kathleen C.

2012-01-01

Using the new conceptual framework of participatory visual media as method, advocacy and voice (MAV), the author explores an action research study using an exemplar in which advocates from the disability community created and distributed a series of videos about love and sexuality as a critical human rights issue in the disability community. The…

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.

Using Video Modeling with Substitutable Loops to Teach Varied Play to Children with Autism

Science.gov (United States)

Dupere, Sally; MacDonald, Rebecca P. F.; Ahearn, William H.

2013-01-01

Children with autism often engage in repetitive play with little variation in the actions performed or items used. This study examined the use of video modeling with scripted substitutable loops on children's pretend play with trained and untrained characters. Three young children with autism were shown a video model of scripted toy play that…

A Simple FSPN Model of P2P Live Video Streaming System

OpenAIRE

Kotevski, Zoran; Mitrevski, Pece

2011-01-01

Peer to Peer (P2P) live streaming is relatively new paradigm that aims at streaming live video to large number of clients at low cost. Many such applications already exist in the market, but, prior to creating such system it is necessary to analyze its performance via representative model that can provide good insight in the system’s behavior. Modeling and performance analysis of P2P live video streaming systems is challenging task which requires addressing many properties and issues of P2P s...

Video coding and decoding devices and methods preserving ppg relevant information

NARCIS (Netherlands)

2013-01-01

The present invention relates to a video encoding device (10) for encoding video data and a corresponding video decoding device, wherein during decoding PPG relevant information shall be preserved. For this purpose the video coding device (10) comprises a first encoder (20) for encoding input video

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

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.

Video Journaling as a Method of Reflective Practice

Science.gov (United States)

Parikh, Sejal B.; Janson, Christopher; Singleton, Tiffany

2012-01-01

The purpose of this phenomenological study was to examine seven school counseling students' experiences of creating reflective video journals during their first internship course. Specifically, this study focused on capturing the essence of the experiences related to personal reactions, feelings, and thoughts about creating two video journal…

Using video self- and peer modeling to facilitate reading fluency in children with learning disabilities.

Science.gov (United States)

Decker, Martha M; Buggey, Tom

2014-01-01

The authors compared the effects of video self-modeling and video peer modeling on oral reading fluency of elementary students with learning disabilities. A control group was also included to gauge general improvement due to reading instruction and familiarity with researchers. The results indicated that both interventions resulted in improved fluency. Students in both experimental groups improved their reading fluency. Two students in the self-modeling group made substantial and immediate gains beyond any of the other students. Discussion is included that focuses on the importance that positive imagery can have on student performance and the possible applications of both forms of video modeling with students who have had negative experiences in reading.

Anatomical knowledge gain through a clay-modeling exercise compared to live and video observations.

Science.gov (United States)

Kooloos, Jan G M; Schepens-Franke, Annelieke N; Bergman, Esther M; Donders, Rogier A R T; Vorstenbosch, Marc A T M

2014-01-01

Clay modeling is increasingly used as a teaching method other than dissection. The haptic experience during clay modeling is supposed to correspond to the learning effect of manipulations during exercises in the dissection room involving tissues and organs. We questioned this assumption in two pretest-post-test experiments. In these experiments, the learning effects of clay modeling were compared to either live observations (Experiment I) or video observations (Experiment II) of the clay-modeling exercise. The effects of learning were measured with multiple choice questions, extended matching questions, and recognition of structures on illustrations of cross-sections. Analysis of covariance with pretest scores as the covariate was used to elaborate the results. Experiment I showed a significantly higher post-test score for the observers, whereas Experiment II showed a significantly higher post-test score for the clay modelers. This study shows that (1) students who perform clay-modeling exercises show less gain in anatomical knowledge than students who attentively observe the same exercise being carried out and (2) performing a clay-modeling exercise is better in anatomical knowledge gain compared to the study of a video of the recorded exercise. The most important learning effect seems to be the engagement in the exercise, focusing attention and stimulating time on task. © 2014 American Association of Anatomists.

Using video modeling for generalizing toy play in children with autism.

Science.gov (United States)

Paterson, Claire R; Arco, Lucius

2007-09-01

The present study examined effects of video modeling on generalized independent toy play of two boys with autism. Appropriate and repetitive verbal and motor play were measured, and intermeasure relationships were examined. Two single-participant experiments with multiple baselines and withdrawals across toy play were used. One boy was presented with three physically unrelated toys, whereas the other was presented with three related toys. Video modeling produced increases in appropriate play and decreases in repetitive play, but generalized play was observed only with the related toys. Generalization may have resulted from variables including the toys' common physical characteristics and natural reinforcing properties and the increased correspondence between verbal and motor play.

A Meta-Analysis of Video Modeling Interventions for Children and Adolescents with Emotional/Behavioral Disorders

Science.gov (United States)

Clinton, Elias

2016-01-01

Video modeling is a non-punitive, evidence-based intervention that has been proven effective for teaching functional life skills and social skills to individuals with autism and developmental disabilities. Compared to the literature base on using video modeling for students with autism and developmental disabilities, fewer studies have examined…

A Comparative Study of Registration Methods for RGB-D Video of Static Scenes

Directory of Open Access Journals (Sweden)

Vicente Morell-Gimenez

2014-05-01

Full Text Available The use of RGB-D sensors for mapping and recognition tasks in robotics or, in general, for virtual reconstruction has increased in recent years. The key aspect of these kinds of sensors is that they provide both depth and color information using the same device. In this paper, we present a comparative analysis of the most important methods used in the literature for the registration of subsequent RGB-D video frames in static scenarios. The analysis begins by explaining the characteristics of the registration problem, dividing it into two representative applications: scene modeling and object reconstruction. Then, a detailed experimentation is carried out to determine the behavior of the different methods depending on the application. For both applications, we used standard datasets and a new one built for object reconstruction.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos.

Science.gov (United States)

Aghamohammadi, Amirhossein; Ang, Mei Choo; A Sundararajan, Elankovan; Weng, Ng Kok; Mogharrebi, Marzieh; Banihashem, Seyed Yashar

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods.

Modifying the affective behavior of preschoolers with autism using in-vivo or video modeling and reinforcement contingencies.

Science.gov (United States)

Gena, Angeliki; Couloura, Sophia; Kymissis, Effie

2005-10-01

The purpose of this study was to modify the affective behavior of three preschoolers with autism in home settings and in the context of play activities, and to compare the effects of video modeling to the effects of in-vivo modeling in teaching these children contextually appropriate affective responses. A multiple-baseline design across subjects, with a return to baseline condition, was used to assess the effects of treatment that consisted of reinforcement, video modeling, in-vivo modeling, and prompting. During training trials, reinforcement in the form of verbal praise and tokens was delivered contingent upon appropriate affective responding. Error correction procedures differed for each treatment condition. In the in-vivo modeling condition, the therapist used modeling and verbal prompting. In the video modeling condition, video segments of a peer modeling the correct response and verbal prompting by the therapist were used as corrective procedures. Participants received treatment in three categories of affective behavior--sympathy, appreciation, and disapproval--and were presented with a total of 140 different scenarios. The study demonstrated that both treatments--video modeling and in-vivo modeling--systematically increased appropriate affective responding in all response categories for the three participants. Additionally, treatment effects generalized across responses to untrained scenarios, the child's mother, new therapists, and time.

Evaluation of Online Video Usage and Learning Satisfaction: An Extension of the Technology Acceptance Model

Science.gov (United States)

Nagy, Judit T.

2018-01-01

The aim of the study was to examine the determining factors of students' video usage and their learning satisfaction relating to the supplementary application of educational videos, accessible in a Moodle environment in a Business Mathematics Course. The research model is based on the extension of "Technology Acceptance Model" (TAM), in…

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 genre classification using multimodal features

Science.gov (United States)

Jin, Sung Ho; Bae, Tae Meon; Choo, Jin Ho; Ro, Yong Man

2003-12-01

We propose a video genre classification method using multimodal features. The proposed method is applied for the preprocessing of automatic video summarization or the retrieval and classification of broadcasting video contents. Through a statistical analysis of low-level and middle-level audio-visual features in video, the proposed method can achieve good performance in classifying several broadcasting genres such as cartoon, drama, music video, news, and sports. In this paper, we adopt MPEG-7 audio-visual descriptors as multimodal features of video contents and evaluate the performance of the classification by feeding the features into a decision tree-based classifier which is trained by CART. The experimental results show that the proposed method can recognize several broadcasting video genres with a high accuracy and the classification performance with multimodal features is superior to the one with unimodal features in the genre classification.

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....

Automatic video segmentation employing object/camera modeling techniques

NARCIS (Netherlands)

Farin, D.S.

2005-01-01

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

Video Coaching as an Efficient Teaching Method for Surgical Residents-A Randomized Controlled Trial.

Science.gov (United States)

Soucisse, Mikael L; Boulva, Kerianne; Sideris, Lucas; Drolet, Pierre; Morin, Michel; Dubé, Pierre

As surgical training is evolving and operative exposure is decreasing, new, effective, and experiential learning methods are needed to ensure surgical competency and patient safety. Video coaching is an emerging concept in surgery that needs further investigation. In this randomized controlled trial conducted at a single teaching hospital, participating residents were filmed performing a side-to-side intestinal anastomosis on cadaveric dog bowel for baseline assessment. The Surgical Video Coaching (SVC) group then participated in a one-on-one video playback coaching and debriefing session with a surgeon, during which constructive feedback was given. The control group went on with their normal clinical duties without coaching or debriefing. All participants were filmed making a second intestinal anastomosis. This was compared to their first anastomosis using a 7-category-validated technical skill global rating scale, the Objective Structured Assessment of Technical Skills. A single independent surgeon who did not participate in coaching or debriefing to the SVC group reviewed all videos. A satisfaction survey was then sent to the residents in the coaching group. Department of Surgery, HôpitalMaisonneuve-Rosemont, tertiary teaching hospital affiliated to the University of Montreal, Canada. General surgery residents from University of Montreal were recruited to take part in this trial. A total of 28 residents were randomized and completed the study. After intervention, the SVC group (n = 14) significantly increased their Objective Structured Assessment of Technical Skills score (mean of differences 3.36, [1.09-5.63], p = 0.007) when compared to the control group (n = 14) (mean of differences 0.29, p = 0.759). All residents agreed or strongly agreed that video coaching was a time-efficient teaching method. Video coaching is an effective and efficient teaching intervention to improve surgical residents' technical skills. Crown Copyright © 2017. Published by Elsevier

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.

Analysis of facial expressions in parkinson's disease through video-based automatic methods.

Science.gov (United States)

Bandini, Andrea; Orlandi, Silvia; Escalante, Hugo Jair; Giovannelli, Fabio; Cincotta, Massimo; Reyes-Garcia, Carlos A; Vanni, Paola; Zaccara, Gaetano; Manfredi, Claudia

2017-04-01

The automatic analysis of facial expressions is an evolving field that finds several clinical applications. One of these applications is the study of facial bradykinesia in Parkinson's disease (PD), which is a major motor sign of this neurodegenerative illness. Facial bradykinesia consists in the reduction/loss of facial movements and emotional facial expressions called hypomimia. In this work we propose an automatic method for studying facial expressions in PD patients relying on video-based METHODS: 17 Parkinsonian patients and 17 healthy control subjects were asked to show basic facial expressions, upon request of the clinician and after the imitation of a visual cue on a screen. Through an existing face tracker, the Euclidean distance of the facial model from a neutral baseline was computed in order to quantify the changes in facial expressivity during the tasks. Moreover, an automatic facial expressions recognition algorithm was trained in order to study how PD expressions differed from the standard expressions. Results show that control subjects reported on average higher distances than PD patients along the tasks. This confirms that control subjects show larger movements during both posed and imitated facial expressions. Moreover, our results demonstrate that anger and disgust are the two most impaired expressions in PD patients. Contactless video-based systems can be important techniques for analyzing facial expressions also in rehabilitation, in particular speech therapy, where patients could get a definite advantage from a real-time feedback about the proper facial expressions/movements to perform. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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.

Identification of Mobile Phone and Analysis of Original Version of Videos through a Delay Time Analysis of Sound Signals from Mobile Phone Videos.

Science.gov (United States)

Hwang, Min Gu; Har, Dong Hwan

2017-11-01

This study designs a method of identifying the camera model used to take videos that are distributed through mobile phones and determines the original version of the mobile phone video for use as legal evidence. For this analysis, an experiment was conducted to find the unique characteristics of each mobile phone. The videos recorded by mobile phones were analyzed to establish the delay time of sound signals, and the differences between the delay times of sound signals for different mobile phones were traced by classifying their characteristics. Furthermore, the sound input signals for mobile phone videos used as legal evidence were analyzed to ascertain whether they have the unique characteristics of the original version. The objective of this study was to find a method for validating the use of mobile phone videos as legal evidence using mobile phones through differences in the delay times of sound input signals. © 2017 American Academy of Forensic Sciences.

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...

The use of scientific direct instruction model with video learning of ethnoscience to improve students’ critical thinking skills

Science.gov (United States)

Sudarmin, S.; Mursiti, S.; Asih, A. G.

2018-04-01

In this disruption era, students are encouraged to develop critical thinking skills and important cultural conservation characters. Student's thinking skill in chemistry learning has not been developed because learning chemistry in schools still uses teacher-centered, lecture method, is less interesting and does not utilize local culture as a learning resource. The purpose of this research is to know the influence of the application of direct Instruction (DI) model with video learning of ethnoscience on the improvement of students’ critical thinking skills. This study was experimental research. The population was the students from class XI MIPA MA Negeri Gombong with the sample chosen by purposive random sampling. The material of local wisdom as the study of ethnosciences which was the focus of the research was the production of genting, dawet, lanting, and sempor reservoirs which is integrated with colloidal chemical contents. The learning video of ethnoscience before being applied was validated by experts. Students’ critical thinking skills were revealed through the concept of conceptualizing test instruments. The data analysis technique used was the test of proportion and Kolmogorov-Smirnov test. The results of this study suggested that the experimental class that was treated by scientific direct instruction model with the learning video of ethnoscience shows cognitive learning and critical thinking which were better than the control class. Besides, the students indicated their interest in the application of scientific direct instruction model with ethnoscience learning video.

Effectiveness of Video Demonstration over Conventional Methods in Teaching Osteology in Anatomy.

Science.gov (United States)

Viswasom, Angela A; Jobby, Abraham

2017-02-01

Technology and its applications are the most happening things in the world. So, is it in the field of medical education. This study was an evaluation of whether the conventional methods can compete with the test of technology. A comparative study of traditional method of teaching osteology in human anatomy with an innovative visual aided method. The study was conducted on 94 students admitted to MBBS 2014 to 2015 batch of Travancore Medical College. The students were divided into two academically validated groups. They were taught using conventional and video demonstrational techniques in a systematic manner. Post evaluation tests were conducted. Analysis of the mark pattern revealed that the group taught using traditional method scored better when compared to the visual aided method. Feedback analysis showed that, the students were able to identify bony features better with clear visualisation and three dimensional view when taught using the video demonstration method. The students identified visual aided method as the more interesting one for learning which helped them in applying the knowledge gained. In most of the questions asked, the two methods of teaching were found to be comparable on the same scale. As the study ends, we discover that, no new technique can be substituted for time tested techniques of teaching and learning. The ideal method would be incorporating newer multimedia techniques into traditional classes.

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

Science.gov (United States)

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

2015-01-01

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

Handbook of video databases design and applications

CERN Document Server

Furht, Borko

2003-01-01

INTRODUCTIONIntroduction to Video DatabasesOge Marques and Borko FurhtVIDEO MODELING AND REPRESENTATIONModeling Video Using Input/Output Markov Models with Application to Multi-Modal Event DetectionAshutosh Garg, Milind R. Naphade, and Thomas S. HuangStatistical Models of Video Structure and SemanticsNuno VasconcelosFlavor: A Language for Media RepresentationAlexandros Eleftheriadis and Danny HongIntegrating Domain Knowledge and Visual Evidence to Support Highlight Detection in Sports VideosJuergen Assfalg, Marco Bertini, Carlo Colombo, and Alberto Del BimboA Generic Event Model and Sports Vid

Satellite markers: a simple method for ground truth car pose on stereo video

Science.gov (United States)

Gil, Gustavo; Savino, Giovanni; Piantini, Simone; Pierini, Marco

2018-04-01

Artificial prediction of future location of other cars in the context of advanced safety systems is a must. The remote estimation of car pose and particularly its heading angle is key to predict its future location. Stereo vision systems allow to get the 3D information of a scene. Ground truth in this specific context is associated with referential information about the depth, shape and orientation of the objects present in the traffic scene. Creating 3D ground truth is a measurement and data fusion task associated with the combination of different kinds of sensors. The novelty of this paper is the method to generate ground truth car pose only from video data. When the method is applied to stereo video, it also provides the extrinsic camera parameters for each camera at frame level which are key to quantify the performance of a stereo vision system when it is moving because the system is subjected to undesired vibrations and/or leaning. We developed a video post-processing technique which employs a common camera calibration tool for the 3D ground truth generation. In our case study, we focus in accurate car heading angle estimation of a moving car under realistic imagery. As outcomes, our satellite marker method provides accurate car pose at frame level, and the instantaneous spatial orientation for each camera at frame level.

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

Science.gov (United States)

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

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

Video Encryption and Decryption on Quantum Computers

Science.gov (United States)

Yan, Fei; Iliyasu, Abdullah M.; Venegas-Andraca, Salvador E.; Yang, Huamin

2015-08-01

A method for video encryption and decryption on quantum computers is proposed based on color information transformations on each frame encoding the content of the encoding the content of the video. The proposed method provides a flexible operation to encrypt quantum video by means of the quantum measurement in order to enhance the security of the video. To validate the proposed approach, a tetris tile-matching puzzle game video is utilized in the experimental simulations. The results obtained suggest that the proposed method enhances the security and speed of quantum video encryption and decryption, both properties required for secure transmission and sharing of video content in quantum communication.

Least-Square Prediction for Backward Adaptive Video Coding

Directory of Open Access Journals (Sweden)

Li Xin

2006-01-01

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

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.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos

Science.gov (United States)

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods. PMID:29438421

Impulsivity, self-regulation,and pathological video gaming among youth: testing a mediation model.

Science.gov (United States)

Liau, Albert K; Neo, Eng Chuan; Gentile, Douglas A; Choo, Hyekyung; Sim, Timothy; Li, Dongdong; Khoo, Angeline

2015-03-01

Given the potential negative mental health consequences of pathological video gaming, understanding its etiology may lead to useful treatment developments. The purpose of the study was to examine the influence of impulsive and regulatory processes on pathological video gaming. Study 1 involved 2154 students from 6 primary and 4 secondary schools in Singapore. Study 2 involved 191 students from 2 secondary schools. The results of study 1 and study 2 supported the hypothesis that self-regulation is a mediator between impulsivity and pathological video gaming. Specifically, higher levels of impulsivity was related to lower levels of self-regulation, which in turn was related to higher levels of pathological video gaming. The use of impulsivity and self-regulation in predicting pathological video gaming supports the dual-system model of incorporating both impulsive and reflective systems in the prediction of self-control outcomes. The study highlights the development of self-regulatory resources as a possible avenue for future prevention and treatment research. © 2011 APJPH.

A new method for wireless video monitoring of bird nests

Science.gov (United States)

David I. King; Richard M. DeGraaf; Paul J. Champlin; Tracey B. Champlin

2001-01-01

Video monitoring of active bird nests is gaining popularity among researchers because it eliminates many of the biases associated with reliance on incidental observations of predation events or use of artificial nests, but the expense of video systems may be prohibitive. Also, the range and efficiency of current video monitoring systems may be limited by the need to...

Co-viewing supports toddlers' word learning from contingent and noncontingent video.

Science.gov (United States)

Strouse, Gabrielle A; Troseth, Georgene L; O'Doherty, Katherine D; Saylor, Megan M

2018-02-01

Social cues are one way young children determine that a situation is pedagogical in nature-containing information to be learned and generalized. However, some social cues (e.g., contingent gaze and responsiveness) are missing from prerecorded video, a potential reason why toddlers' language learning from video can be inefficient compared with their learning directly from a person. This study explored two methods for supporting children's word learning from video by adding social-communicative cues. A sample of 88 30-month-olds began their participation with a video training phase. In one manipulation, an on-screen actress responded contingently to children through a live video feed (similar to Skype or FaceTime "video chat") or appeared in a prerecorded demonstration. In the other manipulation, parents either modeled responsiveness to the actress's on-screen bids for participation or sat out of their children's view. Children then viewed a labeling demonstration on video, and their knowledge of the label was tested with three-dimensional objects. Results indicated that both on-screen contingency and parent modeling increased children's engagement with the actress during training. However, only parent modeling increased children's subsequent word learning, perhaps by revealing the symbolic (representational) intentions underlying this video. This study highlights the importance of adult co-viewing in helping toddlers to interpret communicative cues from video. Copyright © 2017 Elsevier Inc. All rights reserved.

Micro Expression Recognition Using the Eulerian Video Magnification Method

Directory of Open Access Journals (Sweden)

Elham Zarezadeh

2016-08-01

Full Text Available In this paper we propose a new approach for facial micro expressions recognition. For this purpose the Eulerian Video Magnification (EVM method is used to retrieve the subtle motions of the face. The results of this method are obtained as in the magnified images sequence. In this study the numerical tests are performed on two databases: Spontaneous Micro expression (SMIC and Category and Sourcing Managers Executive (CASME. We evaluate our proposed method in two phases using the eigenface method. In phase 1 we recognize the type of a micro expression, for example emotional versus unemotional in SMIC database. Phase 2 classifies the recognized micro expression as negative versus positive in SMIC database and happiness versus disgust in CASME database. The results show that the eigenface method by the EVM method for the retrieval of subtle motions of the face increases the performance of micro expression recognition. Moreover, the proposed approach is more accurate and promising than the previous works in micro expressions recognition.

Distributed Video Coding for Multiview and Video-plus-depth Coding

DEFF Research Database (Denmark)

Salmistraro, Matteo

The interest in Distributed Video Coding (DVC) systems has grown considerably in the academic world in recent years. With DVC the correlation between frames is exploited at the decoder (joint decoding). The encoder codes the frame independently, performing relatively simple operations. Therefore......, with DVC the complexity is shifted from encoder to decoder, making the coding architecture a viable solution for encoders with limited resources. DVC may empower new applications which can benefit from this reversed coding architecture. Multiview Distributed Video Coding (M-DVC) is the application...... of the to-be-decoded frame. Another key element is the Residual estimation, indicating the reliability of the SI, which is used to calculate the parameters of the correlation noise model between SI and original frame. In this thesis new methods for Inter-camera SI generation are analyzed in the Stereo...

Video Quality Assessment Using Spatio-Velocity Contrast Sensitivity Function

Science.gov (United States)

Hirai, Keita; Tumurtogoo, Jambal; Kikuchi, Ayano; Tsumura, Norimichi; Nakaguchi, Toshiya; Miyake, Yoichi

Due to the development and popularization of high-definition televisions, digital video cameras, Blu-ray discs, digital broadcasting, IP television and so on, it plays an important role to identify and quantify video quality degradations. In this paper, we propose SV-CIELAB which is an objective video quality assessment (VQA) method using a spatio-velocity contrast sensitivity function (SV-CSF). In SV-CIELAB, motion information in videos is effectively utilized for filtering unnecessary information in the spatial frequency domain. As the filter to apply videos, we used the SV-CSF. It is a modulation transfer function of the human visual system, and consists of the relationship among contrast sensitivities, spatial frequencies and velocities of perceived stimuli. In the filtering process, the SV-CSF cannot be directly applied in the spatial frequency domain because spatial coordinate information is required when using velocity information. For filtering by the SV-CSF, we obtain video frames separated in spatial frequency domain. By using velocity information, the separated frames with limited spatial frequencies are weighted by contrast sensitivities in the SV-CSF model. In SV-CIELAB, the criteria are obtained by calculating image differences between filtered original and distorted videos. For the validation of SV-CIELAB, subjective evaluation experiments were conducted. The subjective experimental results were compared with SV-CIELAB and the conventional VQA methods such as CIELAB color difference, Spatial-CIELAB, signal to noise ratio and so on. From the experimental results, it was shown that SV-CIELAB is a more efficient VQA method than the conventional methods.

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

Science.gov (United States)

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

2010-01-01

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

Web-based remote video monitoring system implemented using Java technology

Science.gov (United States)

Li, Xiaoming

2012-04-01

A HTTP based video transmission system has been built upon the p2p(peer to peer) network structure utilizing the Java technologies. This makes the video monitoring available to any host which has been connected to the World Wide Web in any method, including those hosts behind firewalls or in isolated sub-networking. In order to achieve this, a video source peer has been developed, together with the client video playback peer. The video source peer can respond to the video stream request in HTTP protocol. HTTP based pipe communication model is developed to speeding the transmission of video stream data, which has been encoded into fragments using the JPEG codec. To make the system feasible in conveying video streams between arbitrary peers on the web, a HTTP protocol based relay peer is implemented as well. This video monitoring system has been applied in a tele-robotic system as a visual feedback to the operator.

Use of Video Modeling to Teach Adolescents with an Intellectual Disability to Film Their Own Video Prompts

Science.gov (United States)

Shepley, Sally B.; Smith, Katie A.; Ayres, Kevin M.; Alexander, Jennifer L.

2017-01-01

Self-instruction for individuals with an intellectual disability can be viewed as a pivotal skill in that once learned this skill has collateral effects on future behaviors in various environments. This study used a multiple probe across participants design to evaluate video modeling to teach high school students with an intellectual disability to…

Computer-generated video fly-through: an aid to visual impact assessment for windfarms

International Nuclear Information System (INIS)

Neilson, G.; Leeming, T.; Hall, S.

1998-01-01

Computer generated video fly-through provides a new method of assessing the visual impact of wind farms. With a PC, software and digital terrain model of the wind farm it is possible to produce videos ranging from wireframe to realistically shaded models. Using computer generated video fly-through visually sensitive corridors can be explored fully, wind turbine rotors can be seen in motion, critical viewpoints can be identified for photomontages and the context of the wind farm appreciated better. This paper describes the techniques of computer generated video fly through and examines its various applications in visual impact assessment of wind farms. (Author)

Student Teachers' Modeling of Acceleration Using a Video-Based Laboratory in Physics Education: A Multimodal Case Study

Directory of Open Access Journals (Sweden)

Louis Trudel

2016-06-01

Full Text Available This exploratory study intends to model kinematics learning of a pair of student teachers when exposed to prescribed teaching strategies in a video-based laboratory. Two student teachers were chosen from the Francophone B.Ed. program of the Faculty of Education of a Canadian university. The study method consisted of having the participants interact with a video-based laboratory to complete two activities for learning properties of acceleration in rectilinear motion. Time limits were placed on the learning activities during which the researcher collected detailed multimodal information from the student teachers' answers to questions, the graphs they produced from experimental data, and the videos taken during the learning sessions. As a result, we describe the learning approach each one followed, the evidence of conceptual change and the difficulties they face in tackling various aspects of the accelerated motion. We then specify advantages and limits of our research and propose recommendations for further study.

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

OpenAIRE

Ayala, SM; O'Connor, R

2013-01-01

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

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.

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.

The effects of different types of video modelling on undergraduate students’ motivation and learning in an academic writing course

Directory of Open Access Journals (Sweden)

Mariet Raedts

2017-02-01

Full Text Available This study extends previous research on observational learning in writing. It was our objective to enhance students’ motivation and learning in an academic writing course on research synthesis writing. Participants were 162 first-year college students who had no experience with the writing task. Based on Bandura’s Social Cognitive Theory we developed two videos. In the first video a manager (prestige model elaborated on how synthesizing information is important in professional life. In the second video a peer model demonstrated a five-step writing strategy for writing up a research synthesis. We compared two versions of this video. In the explicit-strategy-instruction-video we added visual cues to channel learners’ attention to critical features of the demonstrated task using an acronym in which each letter represented a step of the model’s strategy. In the implicit-strategy-instruction-video these cues were absent. The effects of the videos were tested using a 2x2 factorial between-subjects design with video of the prestige model (yes/no and type of instructional video (implicit versus explicit strategy instruction as factors. Four post-test measures were obtained: task value, self-efficacy beliefs, task knowledge and writing performances. Path analyses revealed that the prestige model did not affect students’ task value. Peer-mediated explicit strategy instruction had no effect on self-efficacy, but a strong effect on task knowledge. Task knowledge – in turn – was found to be predictive of writing performance.

Multiple player tracking in sports video: a dual-mode two-way bayesian inference approach with progressive observation modeling.

Science.gov (United States)

Xing, Junliang; Ai, Haizhou; Liu, Liwei; Lao, Shihong

2011-06-01

Multiple object tracking (MOT) is a very challenging task yet of fundamental importance for many practical applications. In this paper, we focus on the problem of tracking multiple players in sports video which is even more difficult due to the abrupt movements of players and their complex interactions. To handle the difficulties in this problem, we present a new MOT algorithm which contributes both in the observation modeling level and in the tracking strategy level. For the observation modeling, we develop a progressive observation modeling process that is able to provide strong tracking observations and greatly facilitate the tracking task. For the tracking strategy, we propose a dual-mode two-way Bayesian inference approach which dynamically switches between an offline general model and an online dedicated model to deal with single isolated object tracking and multiple occluded object tracking integrally by forward filtering and backward smoothing. Extensive experiments on different kinds of sports videos, including football, basketball, as well as hockey, demonstrate the effectiveness and efficiency of the proposed method.

Perceptual tools for quality-aware video networks

Science.gov (United States)

Bovik, A. C.

2014-01-01

Monitoring and controlling the quality of the viewing experience of videos transmitted over increasingly congested networks (especially wireless networks) is a pressing problem owing to rapid advances in video-centric mobile communication and display devices that are straining the capacity of the network infrastructure. New developments in automatic perceptual video quality models offer tools that have the potential to be used to perceptually optimize wireless video, leading to more efficient video data delivery and better received quality. In this talk I will review key perceptual principles that are, or could be used to create effective video quality prediction models, and leading quality prediction models that utilize these principles. The goal is to be able to monitor and perceptually optimize video networks by making them "quality-aware."

The effects of video games on laparoscopic simulator skills.

Science.gov (United States)

Jalink, Maarten B; Goris, Jetse; Heineman, Erik; Pierie, Jean-Pierre E N; ten Cate Hoedemaker, Henk O

2014-07-01

Recently, there has been a growth in studies supporting the hypothesis that video games have positive effects on basic laparoscopic skills. This review discusses all studies directly related to these effects. A search in the PubMed and EMBASE databases was performed using synonymous terms for video games and laparoscopy. All available articles concerning video games and their effects on skills on any laparoscopic simulator (box trainer, virtual reality, and animal models) were selected. Video game experience has been related to higher baseline laparoscopic skills in different studies. There is currently, however, no standardized method to assess video game experience, making it difficult to compare these studies. Several controlled experiments have, nevertheless, shown that video games cannot only be used to improve laparoscopic basic skills in surgical novices, but are also used as a temporary warming-up before laparoscopic surgery. Copyright © 2014 Elsevier Inc. All rights reserved.

An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.

Science.gov (United States)

Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei

2013-05-01

Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.

Secured web-based video repository for multicenter studies.

Science.gov (United States)

Yan, Ling; Hicks, Matt; Winslow, Korey; Comella, Cynthia; Ludlow, Christy; Jinnah, H A; Rosen, Ami R; Wright, Laura; Galpern, Wendy R; Perlmutter, Joel S

2015-04-01

We developed a novel secured web-based dystonia video repository for the Dystonia Coalition, part of the Rare Disease Clinical Research network funded by the Office of Rare Diseases Research and the National Institute of Neurological Disorders and Stroke. A critical component of phenotypic data collection for all projects of the Dystonia Coalition includes a standardized video of each participant. We now describe our method for collecting, serving and securing these videos that is widely applicable to other studies. Each recruiting site uploads standardized videos to a centralized secured server for processing to permit website posting. The streaming technology used to view the videos from the website does not allow downloading of video files. With appropriate institutional review board approval and agreement with the hosting institution, users can search and view selected videos on the website using customizable, permissions-based access that maintains security yet facilitates research and quality control. This approach provides a convenient platform for researchers across institutions to evaluate and analyze shared video data. We have applied this methodology for quality control, confirmation of diagnoses, validation of rating scales, and implementation of new research projects. We believe our system can be a model for similar projects that require access to common video resources. Copyright © 2015 Elsevier Ltd. All rights reserved.

Online Media Business Models: Lessons from the Video Game Sector

OpenAIRE

Komorowski, Marlen; Delaere, Simon

2016-01-01

Today’s media industry is characterized by disruptive changes and business models have been acknowledged as a driving force for success. Current business model research manages only to grasp static descriptions while in reality media managers are struggling with the dynamics of the industry. This article aims to close this gap by investigating a new paradigm of online media business models. Based on three video game case studies of the massively multiplayer online role-playing game genre, thi...

No-Reference Video Quality Assessment using MPEG Analysis

DEFF Research Database (Denmark)

Søgaard, Jacob; Forchhammer, Søren; Korhonen, Jari

2013-01-01

We present a method for No-Reference (NR) Video Quality Assessment (VQA) for decoded video without access to the bitstream. This is achieved by extracting and pooling features from a NR image quality assessment method used frame by frame. We also present methods to identify the video coding...... and estimate the video coding parameters for MPEG-2 and H.264/AVC which can be used to improve the VQA. The analysis differs from most other video coding analysis methods since it is without access to the bitstream. The results show that our proposed method is competitive with other recent NR VQA methods...

Noise Residual Learning for Noise Modeling in Distributed Video Coding

DEFF Research Database (Denmark)

Luong, Huynh Van; Forchhammer, Søren

2012-01-01

Distributed video coding (DVC) is a coding paradigm which exploits the source statistics at the decoder side to reduce the complexity at the encoder. The noise model is one of the inherently difficult challenges in DVC. This paper considers Transform Domain Wyner-Ziv (TDWZ) coding and proposes...

A Comparison of Video Modeling, Text-Based Instruction, and No Instruction for Creating Multiple Baseline Graphs in Microsoft Excel

Science.gov (United States)

Tyner, Bryan C.; Fienup, Daniel M.

2015-01-01

Graphing is socially significant for behavior analysts; however, graphing can be difficult to learn. Video modeling (VM) may be a useful instructional method but lacks evidence for effective teaching of computer skills. A between-groups design compared the effects of VM, text-based instruction, and no instruction on graphing performance.…

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.

Video self-modeling as a post-treatment fluency recovery strategy for adults.

Science.gov (United States)

Harasym, Jessica; Langevin, Marilyn; Kully, Deborah

2015-06-01

This multiple-baseline across subjects study investigated the effectiveness of video self-modeling (VSM) in reducing stuttering and bringing about improvements in associated self-report measures. Participants' viewing practices and perceptions of the utility of VSM also were explored. Three adult males who had previously completed speech restructuring treatment viewed VSM recordings twice per week for 6 weeks. Weekly speech data, treatment viewing logs, and pre- and post-treatment self-report measures were obtained. An exit interview also was conducted. Two participants showed a decreasing trend in stuttering frequency. All participants appeared to engage in fewer avoidance behaviors and had less expectations to stutter. All participants perceived that, in different ways, the VSM treatment had benefited them and all participants had unique viewing practices. Given the increasing availability and ease in using portable audio-visual technology, VSM appears to offer an economical and clinically useful tool for clients who are motivated to use the technology to recover fluency. Readers will be able to describe: (a) the tenets of video-self modeling; (b) the main components of video-self modeling as a fluency recovery treatment as used in this study; and (c) speech and self-report outcomes. Copyright © 2015 Elsevier Inc. All rights reserved.

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

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

A Retrieval Optimized Surveillance Video Storage System for Campus Application Scenarios

Directory of Open Access Journals (Sweden)

Shengcheng Ma

2018-01-01

Full Text Available This paper investigates and analyzes the characteristics of video data and puts forward a campus surveillance video storage system with the university campus as the specific application environment. Aiming at the challenge that the content-based video retrieval response time is too long, the key-frame index subsystem is designed. The key frame of the video can reflect the main content of the video. Extracted from the video, key frames are associated with the metadata information to establish the storage index. The key-frame index is used in lookup operations while querying. This method can greatly reduce the amount of video data reading and effectively improves the query’s efficiency. From the above, we model the storage system by a stochastic Petri net (SPN and verify the promotion of query performance by quantitative analysis.

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.

Dynamic Power-Saving Method for Wi-Fi Direct Based IoT Networks Considering Variable-Bit-Rate Video Traffic.

Science.gov (United States)

Jin, Meihua; Jung, Ji-Young; Lee, Jung-Ryun

2016-10-12

With the arrival of the era of Internet of Things (IoT), Wi-Fi Direct is becoming an emerging wireless technology that allows one to communicate through a direct connection between the mobile devices anytime, anywhere. In Wi-Fi Direct-based IoT networks, all devices are categorized by group of owner (GO) and client. Since portability is emphasized in Wi-Fi Direct devices, it is essential to control the energy consumption of a device very efficiently. In order to avoid unnecessary power consumed by GO, Wi-Fi Direct standard defines two power-saving methods: Opportunistic and Notice of Absence (NoA) power-saving methods. In this paper, we suggest an algorithm to enhance the energy efficiency of Wi-Fi Direct power-saving, considering the characteristics of multimedia video traffic. Proposed algorithm utilizes the statistical distribution for the size of video frames and adjusts the lengths of awake intervals in a beacon interval dynamically. In addition, considering the inter-dependency among video frames, the proposed algorithm ensures that a video frame having high priority is transmitted with higher probability than other frames having low priority. Simulation results show that the proposed method outperforms the traditional NoA method in terms of average delay and energy efficiency.

Image/video understanding systems based on network-symbolic models

Science.gov (United States)

Kuvich, Gary

2004-03-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/network models is found. Symbols, predicates and grammars naturally emerge in such networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type relational structure created via multilevel hierarchical compression of visual information. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. Spatial logic and topology naturally present in such structures. Mid-level vision processes like perceptual grouping, separation of figure from ground, are special kinds of network transformations. They convert primary image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models combines learning, classification, and analogy together with higher-level model-based reasoning into a single framework, and it works similar to frames and agents. Computational intelligence methods transform images into model-based knowledge representation. Based on such principles, an Image/Video Understanding system can convert images into the knowledge models, and resolve uncertainty and ambiguity. This allows creating intelligent computer vision systems for design and manufacturing.

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

Does teaching method affect students' perceptions regarding communication patterns in pediatric dentistry? A comparison of lecture and video methods.

Science.gov (United States)

Kalwitzki, Matthias; Meller, Christina; Beyer, Christine

2011-08-01

The purpose of this study was to determine whether dental students' perceptions regarding six communication patterns for use in pediatric dentistry differed depending on whether they were taught by lecturing or by video-based teaching. Prior to the introduction of interpersonal skills in a clinical course in pediatric dentistry, four consecutive cohorts of students (n=107) in a German dental school were divided equally into two groups. Group one (n=57) was taught by video sequences and group two (n=50) by conventional lecture. Six communication patterns were presented: involvement of the child's toy(s), speaking in positive phrases, mentioning a personal aspect, recalling positive behavior of the patient, addressing fear verbally, and complimenting the patient. Immediately after the presentation, students were asked by means of a questionnaire about their assessment of and intentions regarding the clinical application of the communication patterns presented. After completion of the course, they were asked about the communication patterns that had been used. There were significant differences for three communication patterns in favor of video-based teaching (pstudents perceived differences between video-based teaching and lecturing regarding ease of use, but they did not seem to benefit from one method over the other regarding clinical application.

System and method for improving video recorder performance in a search mode

NARCIS (Netherlands)

2000-01-01

A method and apparatus wherein video images are recorded on a plurality of tracks of a tape such that, for playback in a search mode at a speed, higher than the recording speed the displayed image will consist of a plurality of contiguous parts, some of the parts being read out from tracks each

System and method for improving video recorder performance in a search mode

NARCIS (Netherlands)

1991-01-01

A method and apparatus wherein video images are recorded on a plurality of tracks of a tape such that, for playback in a search mode at a speed higher than the recording speed the displayed image will consist of a plurality of contiguous parts, some of the parts being read out from tracks each

Improving Video Generation for Multi-functional Applications

OpenAIRE

Kratzwald, Bernhard; Huang, Zhiwu; Paudel, Danda Pani; Dinesh, Acharya; Van Gool, Luc

2017-01-01

In this paper, we aim to improve the state-of-the-art video generative adversarial networks (GANs) with a view towards multi-functional applications. Our improved video GAN model does not separate foreground from background nor dynamic from static patterns, but learns to generate the entire video clip conjointly. Our model can thus be trained to generate - and learn from - a broad set of videos with no restriction. This is achieved by designing a robust one-stream video generation architectur...

Does a video displaying a stair climbing model increase stair use in a worksite setting?

Science.gov (United States)

Van Calster, L; Van Hoecke, A-S; Octaef, A; Boen, F

2017-08-01

This study evaluated the effects of improving the visibility of the stairwell and of displaying a video with a stair climbing model on climbing and descending stair use in a worksite setting. Intervention study. Three consecutive one-week intervention phases were implemented: (1) the visibility of the stairs was improved by the attachment of pictograms that indicated the stairwell; (2) a video showing a stair climbing model was sent to the employees by email; and (3) the same video was displayed on a television screen at the point-of-choice (POC) between the stairs and the elevator. The interventions took place in two buildings. The implementation of the interventions varied between these buildings and the sequence was reversed. Improving the visibility of the stairs increased both stair climbing (+6%) and descending stair use (+7%) compared with baseline. Sending the video by email yielded no additional effect on stair use. By contrast, displaying the video at the POC increased stair climbing in both buildings by 12.5% on average. One week after the intervention, the positive effects on stair climbing remained in one of the buildings, but not in the other. These findings suggest that improving the visibility of the stairwell and displaying a stair climbing model on a screen at the POC can result in a short-term increase in both climbing and descending stair use. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

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.

Mixed Methods Approach for Measuring the Impact of Video Telehealth on Outpatient Clinic Triage Nurse Workflow

Science.gov (United States)

Cady, Rhonda G.; Finkelstein, Stanley M.

2015-01-01

Nurse-delivered telephone triage is a common component of outpatient clinic settings. Adding new communication technology to clinic triage has the potential to not only transform the triage process, but also alter triage workflow. Evaluating the impact of new technology on an existing workflow is paramount to maximizing efficiency of the delivery system. This study investigated triage nurse workflow before and after the implementation of video telehealth using a sequential mixed methods protocol that combined ethnography and time-motion study to provide a robust analysis of the implementation environment. Outpatient clinic triage using video telehealth required significantly more time than telephone triage, indicating a reduction in nurse efficiency. Despite the increased time needed to conduct video telehealth, nurses consistently rated it useful in providing triage. Interpretive analysis of the qualitative and quantitative data suggests the increased depth and breadth of data available during video triage alters the assessment triage nurses provide physicians. This in turn could impact the time physicians spend formulating a diagnosis and treatment plan. While the immediate impact of video telehealth is a reduction in triage nurse efficiency, what is unknown is the impact of video telehealth on physician and overall clinic efficiency. Future studies should address this area. PMID:24080753

Handheld Devices and Video Modeling to Enhance the Learning of Self-Help Skills in Adolescents With Autism Spectrum Disorder.

Science.gov (United States)

Campbell, Joseph E; Morgan, Michele; Barnett, Veronica; Spreat, Scott

2015-04-01

The viewing of videos is a much-studied intervention to teach self-help, social, and vocational skills. Many of the studies to date looked at video modeling using televisions, computers, and other large screens. This study looked at the use of video modeling on portable handheld devices to teach hand washing to three adolescent students with an autism spectrum disorder. Three students participated in this 4-week study conducted by occupational therapists. Baseline data were obtained for the first student for 1 week, the second for 2 weeks, and the third for 3 weeks; videos were introduced when the participants each finished the baseline phase. Given the cognitive and motor needs of the participants, the occupational therapist set the player so that the participants only had to press the play button to start the video playing. The participants were able to hold the players and view at distances that were most appropriate for their individual needs and preferences. The results suggest that video modeling on a handheld device improves the acquisition of self-help skills.

Visual fatigue modeling for stereoscopic video shot based on camera motion

Science.gov (United States)

Shi, Guozhong; Sang, Xinzhu; Yu, Xunbo; Liu, Yangdong; Liu, Jing

2014-11-01

As three-dimensional television (3-DTV) and 3-D movie become popular, the discomfort of visual feeling limits further applications of 3D display technology. The cause of visual discomfort from stereoscopic video conflicts between accommodation and convergence, excessive binocular parallax, fast motion of objects and so on. Here, a novel method for evaluating visual fatigue is demonstrated. Influence factors including spatial structure, motion scale and comfortable zone are analyzed. According to the human visual system (HVS), people only need to converge their eyes to the specific objects for static cameras and background. Relative motion should be considered for different camera conditions determining different factor coefficients and weights. Compared with the traditional visual fatigue prediction model, a novel visual fatigue predicting model is presented. Visual fatigue degree is predicted using multiple linear regression method combining with the subjective evaluation. Consequently, each factor can reflect the characteristics of the scene, and the total visual fatigue score can be indicated according to the proposed algorithm. Compared with conventional algorithms which ignored the status of the camera, our approach exhibits reliable performance in terms of correlation with subjective test results.

Method for operating video game with back-feeding a video image of a player, and a video game arranged for practicing the method.

NARCIS (Netherlands)

2006-01-01

In a video gaming environment, a player is enabled to interact with the environment. Further, a score and/or performance of the player in a particular session is machine detected and fed fed back into the gaming environment and a representation of said score and/or performance is displayed in visual

Research of Block-Based Motion Estimation Methods for Video Compression

Directory of Open Access Journals (Sweden)

Tropchenko Andrey

2016-08-01

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

Using video modeling to teach reciprocal pretend play to children with autism.

Science.gov (United States)

MacDonald, Rebecca; Sacramone, Shelly; Mansfield, Renee; Wiltz, Kristine; Ahearn, William H

2009-01-01

The purpose of the present study was to use video modeling to teach children with autism to engage in reciprocal pretend play with typically developing peers. Scripted play scenarios involving various verbalizations and play actions with adults as models were videotaped. Two children with autism were each paired with a typically developing child, and a multiple-probe design across three play sets was used to evaluate the effects of the video modeling procedure. Results indicated that both children with autism and the typically developing peers acquired the sequences of scripted verbalizations and play actions quickly and maintained this performance during follow-up probes. In addition, probes indicated an increase in the mean number of unscripted verbalizations as well as reciprocal verbal interactions and cooperative play. These findings are discussed as they relate to the development of reciprocal pretend-play repertoires in young children with autism.

It's All a Matter of Perspective: Viewing First-Person Video Modeling Examples Promotes Learning of an Assembly Task

Science.gov (United States)

Fiorella, Logan; van Gog, Tamara; Hoogerheide, Vincent; Mayer, Richard E.

2017-01-01

The present study tests whether presenting video modeling examples from the learner's (first-person) perspective promotes learning of an assembly task, compared to presenting video examples from a third-person perspective. Across 2 experiments conducted in different labs, university students viewed a video showing how to assemble an 8-component…

Probabilistic Approaches to Video Retrieval

NARCIS (Netherlands)

Ianeva, Tzvetanka; Boldareva, L.; Westerveld, T.H.W.; Cornacchia, Roberto; Hiemstra, Djoerd; de Vries, A.P.

Our experiments for TRECVID 2004 further investigate the applicability of the so-called “Generative Probabilistic Models to video retrieval��?. TRECVID 2003 results demonstrated that mixture models computed from video shot sequences improve the precision of “query by examples��? results when

Online Nonparametric Bayesian Activity Mining and Analysis From Surveillance Video.

Science.gov (United States)

Bastani, Vahid; Marcenaro, Lucio; Regazzoni, Carlo S

2016-05-01

A method for online incremental mining of activity patterns from the surveillance video stream is presented in this paper. The framework consists of a learning block in which Dirichlet process mixture model is employed for the incremental clustering of trajectories. Stochastic trajectory pattern models are formed using the Gaussian process regression of the corresponding flow functions. Moreover, a sequential Monte Carlo method based on Rao-Blackwellized particle filter is proposed for tracking and online classification as well as the detection of abnormality during the observation of an object. Experimental results on real surveillance video data are provided to show the performance of the proposed algorithm in different tasks of trajectory clustering, classification, and abnormality detection.

Using Portable Video Modeling Technology to Increase the Compliment Behaviors of Children with Autism During Athletic Group Play.

Science.gov (United States)

Macpherson, Kevin; Charlop, Marjorie H; Miltenberger, Catherine A

2015-12-01

A multiple baseline design across participants was used to examine the effects of a portable video modeling intervention delivered in the natural environment on the verbal compliments and compliment gestures demonstrated by five children with autism. Participants were observed playing kickball with peers and adults. In baseline, participants demonstrated few compliment behaviors. During intervention, an iPad(®) was used to implement the video modeling treatment during the course of the athletic game. Viewing the video rapidly increased the verbal compliments participants gave to peers. Participants also demonstrated more response variation after watching the videos. Some generalization to an untrained activity occurred and compliment gestures also occurred. Results are discussed in terms of contributions to the literature.

The effect of online violent video games on levels of aggression.

Directory of Open Access Journals (Sweden)

Jack Hollingdale

Full Text Available BACKGROUND: In recent years the video game industry has surpassed both the music and video industries in sales. Currently violent video games are among the most popular video games played by consumers, most specifically First-Person Shooters (FPS. Technological advancements in game play experience including the ability to play online has accounted for this increase in popularity. Previous research, utilising the General Aggression Model (GAM, has identified that violent video games increase levels of aggression. Little is known, however, as to the effect of playing a violent video game online. METHODS/PRINCIPAL FINDINGS: Participants (N = 101 were randomly assigned to one of four experimental conditions; neutral video game--offline, neutral video game--online, violent video game--offline and violent video game--online. Following this they completed questionnaires to assess their attitudes towards the game and engaged in a chilli sauce paradigm to measure behavioural aggression. The results identified that participants who played a violent video game exhibited more aggression than those who played a neutral video game. Furthermore, this main effect was not particularly pronounced when the game was played online. CONCLUSIONS/SIGNIFICANCE: These findings suggest that both playing violent video games online and offline compared to playing neutral video games increases aggression.

An openstack-based flexible video transcoding framework in live

Science.gov (United States)

Shi, Qisen; Song, Jianxin

2017-08-01

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

Modeling of video traffic in packet networks, low rate video compression, and the development of a lossy+lossless image compression algorithm

Science.gov (United States)

Sayood, K.; Chen, Y. C.; Wang, X.

1992-01-01

During this reporting period we have worked on three somewhat different problems. These are modeling of video traffic in packet networks, low rate video compression, and the development of a lossy + lossless image compression algorithm, which might have some application in browsing algorithms. The lossy + lossless scheme is an extension of work previously done under this grant. It provides a simple technique for incorporating browsing capability. The low rate coding scheme is also a simple variation on the standard discrete cosine transform (DCT) coding approach. In spite of its simplicity, the approach provides surprisingly high quality reconstructions. The modeling approach is borrowed from the speech recognition literature, and seems to be promising in that it provides a simple way of obtaining an idea about the second order behavior of a particular coding scheme. Details about these are presented.

Toy Trucks in Video Analysis

DEFF Research Database (Denmark)

Buur, Jacob; Nakamura, Nanami; Larsen, Rainer Rye

2015-01-01

discovered that using scale-models like toy trucks has a strongly encouraging effect on developers/designers to collaboratively make sense of field videos. In our analysis of such scale-model sessions, we found some quite fundamental patterns of how participants utilise objects; the participants build shared......Video fieldstudies of people who could be potential users is widespread in design projects. How to analyse such video is, however, often challenging, as it is time consuming and requires a trained eye to unlock experiential knowledge in people’s practices. In our work with industrialists, we have...... narratives by moving the objects around, they name them to handle the complexity, they experience what happens in the video through their hands, and they use the video together with objects to create alternative narratives, and thus alternative solutions to the problems they observe. In this paper we claim...

Photogrammetric Applications of Immersive Video Cameras

Science.gov (United States)

Kwiatek, K.; Tokarczyk, R.

2014-05-01

The paper investigates immersive videography and its application in close-range photogrammetry. Immersive video involves the capture of a live-action scene that presents a 360° field of view. It is recorded simultaneously by multiple cameras or microlenses, where the principal point of each camera is offset from the rotating axis of the device. This issue causes problems when stitching together individual frames of video separated from particular cameras, however there are ways to overcome it and applying immersive cameras in photogrammetry provides a new potential. The paper presents two applications of immersive video in photogrammetry. At first, the creation of a low-cost mobile mapping system based on Ladybug®3 and GPS device is discussed. The amount of panoramas is much too high for photogrammetric purposes as the base line between spherical panoramas is around 1 metre. More than 92 000 panoramas were recorded in one Polish region of Czarny Dunajec and the measurements from panoramas enable the user to measure the area of outdoors (adverting structures) and billboards. A new law is being created in order to limit the number of illegal advertising structures in the Polish landscape and immersive video recorded in a short period of time is a candidate for economical and flexible measurements off-site. The second approach is a generation of 3d video-based reconstructions of heritage sites based on immersive video (structure from immersive video). A mobile camera mounted on a tripod dolly was used to record the interior scene and immersive video, separated into thousands of still panoramas, was converted from video into 3d objects using Agisoft Photoscan Professional. The findings from these experiments demonstrated that immersive photogrammetry seems to be a flexible and prompt method of 3d modelling and provides promising features for mobile mapping systems.

Evaluating user preferences for video transfer methods from a mobile device to a TV screen

DEFF Research Database (Denmark)

Fleury, Alexandre; Pedersen, Jakob Schou; Larsen, Lars Bo

2013-01-01

This article reports on the evaluation of four methods for transferring video content from a mobile device to a fixed television. The methods have been investigated in a Wizard-of-Oz approach through two consecutive studies. The first experiment aimed at collecting general opinions toward such a ...

Fast detection and modeling of human-body parts from monocular video

NARCIS (Netherlands)

Lao, W.; Han, Jungong; With, de P.H.N.; Perales, F.J.; Fisher, R.B.

2009-01-01

This paper presents a novel and fast scheme to detect different body parts in human motion. Using monocular video sequences, trajectory estimation and body modeling of moving humans are combined in a co-operating processing architecture. More specifically, for every individual person, features of

Probabilistic recognition of human faces from video

DEFF Research Database (Denmark)

Zhou, Saohua; Krüger, Volker; Chellappa, Rama

2003-01-01

Recognition of human faces using a gallery of still or video images and a probe set of videos is systematically investigated using a probabilistic framework. In still-to-video recognition, where the gallery consists of still images, a time series state space model is proposed to fuse temporal...... of the identity variable produces the recognition result. The model formulation is very general and it allows a variety of image representations and transformations. Experimental results using videos collected by NIST/USF and CMU illustrate the effectiveness of this approach for both still-to-video and video-to-video...... information in a probe video, which simultaneously characterizes the kinematics and identity using a motion vector and an identity variable, respectively. The joint posterior distribution of the motion vector and the identity variable is estimated at each time instant and then propagated to the next time...

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.

A Super-resolution Reconstruction Algorithm for Surveillance Video

Directory of Open Access Journals (Sweden)

Jian Shao

2017-01-01

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

Hybrid Modeling of Intra-DCT Coefficients for Real-Time Video Encoding

Directory of Open Access Journals (Sweden)

Li Jin

2008-01-01

Full Text Available Abstract The two-dimensional discrete cosine transform (2-D DCT and its subsequent quantization are widely used in standard video encoders. However, since most DCT coefficients become zeros after quantization, a number of redundant computations are performed. This paper proposes a hybrid statistical model used to predict the zeroquantized DCT (ZQDCT coefficients for intratransform and to achieve better real-time performance. First, each pixel block at the input of DCT is decomposed into a series of mean values and a residual block. Subsequently, a statistical model based on Gaussian distribution is used to predict the ZQDCT coefficients of the residual block. Then, a sufficient condition under which each quantized coefficient becomes zero is derived from the mean values. Finally, a hybrid model to speed up the DCT and quantization calculations is proposed. Experimental results show that the proposed model can reduce more redundant computations and achieve better real-time performance than the reference in the literature at the cost of negligible video quality degradation. Experiments also show that the proposed model significantly reduces multiplications for DCT and quantization. This is particularly suitable for processors in portable devices where multiplications consume more power than additions. Computational reduction implies longer battery lifetime and energy economy.

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...

Video Self-Modeling: A Promising Strategy for Noncompliant Children.

Science.gov (United States)

Axelrod, Michael I; Bellini, Scott; Markoff, Kimberly

2014-07-01

The current study investigated the effects of a Video Self-Modeling (VSM) intervention on the compliance and aggressive behavior of three children placed in a psychiatric hospital. Each participant viewed brief video clips of himself following simple adult instructions just prior to the school's morning session and the unit's afternoon free period. A multiple baseline design across settings was used to evaluate the effects of the VSM intervention on compliance with staff instructions and aggressive behavior on the hospital unit and in the hospital-based classroom. All three participants exhibited higher levels of compliance and fewer aggressive episodes during the intervention condition, and the effects were generally maintained when the intervention was withdrawn. Hospital staff reported at the conclusion of the study that the VSM intervention was easy to implement and beneficial for all participants. Taken altogether, the results suggest VSM is a promising, socially acceptable, and proactive intervention approach for improving the behavior of noncompliant children. © The Author(s) 2014.

Video context-dependent recall.

Science.gov (United States)

Smith, Steven M; Manzano, Isabel

2010-02-01

In two experiments, we used an effective new method for experimentally manipulating local and global contexts to examine context-dependent recall. The method included video-recorded scenes of real environments, with target words superimposed over the scenes. In Experiment 1, we used a within-subjects manipulation of video contexts and compared the effects of reinstatement of a global context (15 words per context) with effects of less overloaded context cues (1 and 3 words per context) on recall. The size of the reinstatement effects in Experiment 1 show how potently video contexts can cue recall. A strong effect of cue overload was also found; reinstatement effects were smaller, but still quite robust, in the 15 words per context condition. The powerful reinstatement effect was replicated for local contexts in Experiment 2, which included a no-contexts-reinstated group, a control condition used to determine whether reinstatement of half of the cues caused biased output interference for uncued targets. The video context method is a potent way to investigate context-dependent memory.

Light-reflection random-target method for measurement of the modulation transfer function of a digital video-camera

Science.gov (United States)

Pospisil, J.; Jakubik, P.; Machala, L.

2005-11-01

This article reports the suggestion, realization and verification of the newly developed measuring means of the noiseless and locally shift-invariant modulation transfer function (MTF) of a digital video camera in a usual incoherent visible region of optical intensity, especially of its combined imaging, detection, sampling and digitizing steps which are influenced by the additive and spatially discrete photodetector, aliasing and quantization noises. Such means relates to the still camera automatic working regime and static two-dimensional spatially continuous light-reflection random target of white-noise property. The introduced theoretical reason for such a random-target method is also performed under exploitation of the proposed simulation model of the linear optical intensity response and possibility to express the resultant MTF by a normalized and smoothed rate of the ascertainable output and input power spectral densities. The random-target and resultant image-data were obtained and processed by means of a processing and evaluational PC with computation programs developed on the basis of MATLAB 6.5E The present examples of results and other obtained results of the performed measurements demonstrate the sufficient repeatability and acceptability of the described method for comparative evaluations of the performance of digital video cameras under various conditions.

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.

The Ethics of Video-Game Monetization Modelling: A Discussion on Ethics and Legitimacy of Micro-transactions

OpenAIRE

Khan, Arun Rashid

2017-01-01

The purpose of the paper is to present an insight and elaboration of the growing Gaming Industry. As the video-game industry has enjoyed immense growth in both consumers that part-take / consume the product of video-games and increases in profits, current research discourse has been focussed around the emergence of micro-transactions and their role in business model development of the firm. Furthermore research has also been focussed around the sociological aspects of video-games in terms of ...

Teaching Social-Communication Skills to Preschoolers with Autism: Efficacy of Video versus in Vivo Modeling in the Classroom

Science.gov (United States)

Wilson, Kaitlyn P.

2013-01-01

Video modeling is a time- and cost-efficient intervention that has been proven effective for children with autism spectrum disorder (ASD); however, the comparative efficacy of this intervention has not been examined in the classroom setting. The present study examines the relative efficacy of video modeling as compared to the more widely-used…

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

OpenAIRE

Ayala, Sandra M

2010-01-01

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

Reviews in instructional video

NARCIS (Netherlands)

van der Meij, Hans

2017-01-01

This study investigates the effectiveness of a video tutorial for software training whose construction was based on a combination of insights from multimedia learning and Demonstration-Based Training. In the videos, a model of task performance was enhanced with instructional features that were

Video Modeling and Prompting: A Comparison of Two Strategies for Teaching Cooking Skills to Students with Mild Intellectual Disabilities

Science.gov (United States)

Taber-Doughty, Teresa; Bouck, Emily C.; Tom, Kinsey; Jasper, Andrea D.; Flanagan, Sara M.; Bassette, Laura

2011-01-01

Self-operated video prompting and video modeling was compared when used by three secondary students with mild intellectual disabilities as they completed novel recipes during cooking activities. Alternating between video systems, students completed twelve recipes within their classroom kitchen. An alternating treatment design with a follow-up and…

The effects of video modeling with voiceover instruction on accurate implementation of discrete-trial instruction.

Science.gov (United States)

Vladescu, Jason C; Carroll, Regina; Paden, Amber; Kodak, Tiffany M

2012-01-01

The present study replicates and extends previous research on the use of video modeling (VM) with voiceover instruction to train staff to implement discrete-trial instruction (DTI). After staff trainees reached the mastery criterion when teaching an adult confederate with VM, they taught a child with a developmental disability using DTI. The results showed that the staff trainees' accurate implementation of DTI remained high, and both child participants acquired new skills. These findings provide additional support that VM may be an effective method to train staff members to conduct DTI.

An On-Line Method for Thermal Diffusivity Detection of Thin Films Using Infrared Video

Directory of Open Access Journals (Sweden)

Dong Huilong

2016-03-01

Full Text Available A novel method for thermal diffusivity evolution of thin-film materials with pulsed Gaussian beam and infrared video is reported. Compared with common pulse methods performed in specialized labs, the proposed method implements a rapid on-line measurement without producing the off-centre detection error. Through mathematical deduction of the original heat conduction model, it is discovered that the area s, which is encircled by the maximum temperature curve rTMAX(θ, increases linearly over elapsed time. The thermal diffusivity is acquired from the growth rate of the area s. In this study, the off-centre detection error is avoided by performing the distance regularized level set evolution formulation. The area s was extracted from the binary images of temperature variation rate, without inducing errors from determination of the heat source centre. Thermal diffusivities of three materials, 304 stainless steel, titanium, and zirconium have been measured with the established on-line detection system, and the measurement errors are: −2.26%, −1.07%, and 1.61% respectively.

Diavideos: a diabetes health video portal.

Science.gov (United States)

Sánchez-Bocanegra, C L; Rivero-Rodriguez, A; Fernández-Luque, L; Sevillano, J L

2013-01-01

Diavideos is a web platform that collects trustworthy diabetes health videos from YouTube and offers them in a easy way. YouTube is a big repository of health videos, but good content is sometimes mixed with misleading and harmful videos such as promoting anorexia [1]. Diavideos is a web portal that provides easy access to a repository of trustworthy diabetes videos. This poster describes Diavideos and explains the crawling method used to retrieve these videos from trusted channels.

A robust fusion method for multiview distributed video coding

DEFF Research Database (Denmark)

Salmistraro, Matteo; Ascenso, Joao; Brites, Catarina

2014-01-01

Distributed video coding (DVC) is a coding paradigm which exploits the redundancy of the source (video) at the decoder side, as opposed to predictive coding, where the encoder leverages the redundancy. To exploit the correlation between views, multiview predictive video codecs require the encoder...... with a robust fusion system able to improve the quality of the fused SI along the decoding process through a learning process using already decoded data. We shall here take the approach to fuse the estimated distributions of the SIs as opposed to a conventional fusion algorithm based on the fusion of pixel...... values. The proposed solution is able to achieve gains up to 0.9 dB in Bjøntegaard difference when compared with the best-performing (in a RD sense) single SI DVC decoder, chosen as the best of an inter-view and a temporal SI-based decoder one....

Video media-induced aggressiveness in children.

Science.gov (United States)

Cardwell, Michael Steven

2013-09-01

Transmission of aggressive behaviors to children through modeling by adults has long been a commonly held psychological concept; however, with the advent of technological innovations during the last 30 years, video media-television, movies, video games, and the Internet-has become the primary model for transmitting aggressiveness to children. This review explores the acquisition of aggressive behaviors by children through modeling behaviors in violent video media. The impact of aggressive behaviors on the child, the family, and society is addressed. Suggestive action plans to curb this societal ill are presented.

Video Quality Prediction over Wireless 4G

KAUST Repository

Lau, Chun Pong

2013-04-14

In this paper, we study the problem of video quality prediction over the wireless 4G network. Video transmission data is collected from a real 4G SCM testbed for investigating factors that affect video quality. After feature transformation and selection on video and network parameters, video quality is predicted by solving as regression problem. Experimental results show that the dominated factor on video quality is the channel attenuation and video quality can be well estimated by our models with small errors.

Video Quality Prediction over Wireless 4G

KAUST Repository

Lau, Chun Pong; Zhang, Xiangliang; Shihada, Basem

2013-01-01

In this paper, we study the problem of video quality prediction over the wireless 4G network. Video transmission data is collected from a real 4G SCM testbed for investigating factors that affect video quality. After feature transformation and selection on video and network parameters, video quality is predicted by solving as regression problem. Experimental results show that the dominated factor on video quality is the channel attenuation and video quality can be well estimated by our models with small errors.

The Effect of Video-Assisted Inquiry Modified Learning Model on Student’s Achievement on 1st Fundamental Physics Practice

Directory of Open Access Journals (Sweden)

T W Maduretno

2017-12-01

Full Text Available The purpose of research are: (1 to know the effect of video-assisted inquiry modified learning model on student’s achievement; (2 to improve the student’s achievement in 1st Fundamental Physics Practice through video-assisted inquiry modified learning model. The student’s achievement as dependent variables includes the aspects of knowledge, skill, and attitude. The sampling technique did not choose at random. The Mathematics Education as the control group and the Science Education as the experimental group. The experimental group used video-assisted inquiry modified learning model and the control group used inquiry learning model. The collecting data technique used observation, questionnaire, and test. The researcher used the independent t-test that purposed to compare the average of achievement of control and experiment group. The results of research were: (1 there was an effect of video-assisted inquiry modified learning model on the knowledge and skill aspect but there was not on the attitude aspect; (2 The average of learning outcome of the experimental group higher than the control group’s; (3 The video-assisted inquiry modified learning model helped more skilled and trained student to discovery, inquiry the scientific principle, experiment and observation, and explain the experiment and observation’s result so that the students be able to understand the materials on the 1st Fundamental Physics Practice.

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.

Enhancing conflict negotiation strategies of adolescents with autism spectrum disorder using video modeling.

Science.gov (United States)

Hochhauser, M; Weiss, P L; Gal, E

2018-01-01

Adolescents with autism spectrum disorder (ASD) have particular difficulty in negotiating conflict. A randomized control trial (RCT) was carried out to determine whether the negotiation strategies of adolescents with ASD would be enhanced via a 6-week intervention based on a video modeling application. Adolescents with ASD, aged 12-18 years, were randomly divided into an intervention group (n = 36) and a non-treatment control group (n = 25). Participants' negotiating strategies prior to and following the intervention were measured using the Five Factor Negotiation Scale (FFNS; Nakkula & Nikitopoulos, 1999) and the ConflicTalk questionnaire (Kimsey & Fuller, 2003). The results suggest that video modeling is an effective intervention for improving and maintaining conflict negotiation strategies of adolescents with ASD.

Automated Analysis of Facial Cues from Videos as a Potential Method for Differentiating Stress and Boredom of Players in Games

Directory of Open Access Journals (Sweden)

Fernando Bevilacqua

2018-01-01

Full Text Available Facial analysis is a promising approach to detect emotions of players unobtrusively; however approaches are commonly evaluated in contexts not related to games or facial cues are derived from models not designed for analysis of emotions during interactions with games. We present a method for automated analysis of facial cues from videos as a potential tool for detecting stress and boredom of players behaving naturally while playing games. Computer vision is used to automatically and unobtrusively extract 7 facial features aimed at detecting the activity of a set of facial muscles. Features are mainly based on the Euclidean distance of facial landmarks and do not rely on predefined facial expressions, training of a model, or the use of facial standards. An empirical evaluation was conducted on video recordings of an experiment involving games as emotion elicitation sources. Results show statistically significant differences in the values of facial features during boring and stressful periods of gameplay for 5 of the 7 features. We believe our approach is more user-tailored, convenient, and better suited for contexts involving games.

Preliminary study on effects of 60Co γ-irradiation on video quality and the image de-noising methods

International Nuclear Information System (INIS)

Yuan Mei; Zhao Jianbin; Cui Lei

2011-01-01

There will be variable noises appear on images in video once the play device irradiated by γ-rays, so as to affect the image clarity. In order to eliminate the image noising, the affection mechanism of γ-irradiation on video-play device was studied in this paper and the methods to improve the image quality with both hardware and software were proposed by use of protection program and de-noising algorithm. The experimental results show that the scheme of video de-noising based on hardware and software can improve effectively the PSNR by 87.5 dB. (authors)

On the relationship between perceptual impact of source and channel distortions in video sequences

DEFF Research Database (Denmark)

Korhonen, Jari; Reiter, Ulrich; You, Junyong

2010-01-01

It is known that peak signal-to-noise ratio (PSNR) can be used for assessing the relative qualities of distorted video sequences meaningfully only if the compared sequences contain similar types of distortions. In this paper, we propose a model for rough assessment of the bias in PSNR results, when...... video sequences with both channel and source distortion are compared against video sequences with source distortion only. The proposed method can be used to compare the relative perceptual quality levels of video sequences with different distortion types more reliably than using plain PSNR....

Is video gaming, or video game addiction, associated with depression, academic achievement, heavy episodic drinking, or conduct problems?

Science.gov (United States)

Brunborg, Geir Scott; Mentzoni, Rune Aune; Frøyland, Lars Roar

2014-01-01

Background and aims: While the relationships between video game use and negative consequences are debated, the relationships between video game addiction and negative consequences are fairly well established. However, previous studies suffer from methodological weaknesses that may have caused biased results. There is need for further investigation that benefits from the use of methods that avoid omitted variable bias. Methods: Two wave panel data was used from two surveys of 1,928 Norwegian adolescents aged 13 to 17 years. The surveys included measures of video game use, video game addiction, depression, heavy episodic drinking, academic achievement, and conduct problems. The data was analyzed using first-differencing, a regression method that is unbiased by time invariant individual factors. Results: Video game addiction was related to depression, lower academic achievement, and conduct problems, but time spent on video games was not related to any of the studied negative outcomes. Discussion: The findings were in line with a growing number of studies that have failed to find relationships between time spent on video games and negative outcomes. The current study is also consistent with previous studies in that video game addiction was related to other negative outcomes, but it made the added contribution that the relationships are unbiased by time invariant individual effects. However, future research should aim at establishing the temporal order of the supposed causal effects. Conclusions: Spending time playing video games does not involve negative consequences, but adolescents who experience problems related to video games are likely to also experience problems in other facets of life. PMID:25215212

'People like me don't make things like that': Participatory video as a method for reducing leprosy-related stigma.

Science.gov (United States)

Peters, R M H; Zweekhorst, M B M; van Brakel, W H; Bunders, J F G; Irwanto

2016-01-01

The Stigma Assessment and Reduction of Impact project aims to assess the effectiveness of stigma-reduction interventions in the field of leprosy. Participatory video seemed to be a promising approach to reducing stigma among stigmatized individuals (in this study the video makers) and the stigmatisers (video audience). This study focuses on the video makers and seeks to assess the impact on them of making a participatory video and to increase understanding of how to deal with foreseeable difficulties. Participants were selected on the basis of criteria and in collaboration with the community health centre. This study draws on six qualitative methods including interviews with the video makers and participant observation. Triangulation was used to increase the validity of the findings. Two videos were produced. The impact on participants ranged from having a good time to a greater sense of togetherness, increased self-esteem, individual agency and willingness to take action in the community. Concealment of leprosy is a persistent challenge, and physical limitations and group dynamics are also areas that require attention. Provided these three areas are properly taken into account, participatory video has the potential to address stigma at least at three levels - intrapersonal, interpersonal and community - and possibly more.

Research of Video Steganalysis Algorithm Based on H265 Protocol

Directory of Open Access Journals (Sweden)

Wu Kaicheng

2015-01-01

This paper researches LSB matching VSA based on H265 protocol with the research background of 26 original Video sequences, it firstly extracts classification features out from training samples as input of SVM, and trains in SVM to obtain high-quality category classification model, and then tests whether there is suspicious information in the video sample. The experimental results show that VSA algorithm based on LSB matching can be more practical to obtain all frame embedded secret information and carrier and video of local frame embedded. In addition, VSA adopts the method of frame by frame with a strong robustness in resisting attack in the corresponding time domain.

Video self-modeling in children with autism: a pilot study validating prerequisite skills and extending the utilization of VSM across skill sets.

Science.gov (United States)

Williamson, Robert L; Casey, Laura B; Robertson, Janna Siegel; Buggey, Tom

2013-01-01

Given the recent interest in the use of video self-modeling (VSM) to provide instruction within iPod apps and other pieces of handheld mobile assistive technologies, investigating appropriate prerequisite skills for effective use of this intervention is particularly timely and relevant. To provide additional information regarding the efficacy of VSM for students with autism and to provide insights into any possible prerequisite skills students may require for such efficacy, the authors investigated the use of VSM in increasing the instances of effective initiations of interpersonal greetings for three students with autism that exhibited different pre-intervention abilities. Results showed that only one of the three participants showed an increase in self-initiated greetings following the viewing of videos edited to show each participant self-modeling a greeting when entering his or her classroom. Due to the differences in initial skill sets between the three children, this finding supports anecdotally observed student prerequisite abilities mentioned in previous studies that may be required to effectively utilize video based teaching methods.

Using of Video Modeling in Teaching a Simple Meal Preparation Skill for Pupils of Down Syndrome

Science.gov (United States)

AL-Salahat, Mohammad Mousa

2016-01-01

The current study aimed to identify the impact of video modeling upon teaching three pupils with Down syndrome the skill of preparing a simple meal (sandwich), where the training was conducted in a separate classroom in schools of normal students. The training consisted of (i) watching the video of an intellectually disabled pupil, who is…

Transcoding method from H.264/AVC to high efficiency video coding based on similarity of intraprediction, interprediction, and motion vector

Science.gov (United States)

Liu, Mei-Feng; Zhong, Guo-Yun; He, Xiao-Hai; Qing, Lin-Bo

2016-09-01

Currently, most video resources on line are encoded in the H.264/AVC format. More fluent video transmission can be obtained if these resources are encoded in the newest international video coding standard: high efficiency video coding (HEVC). In order to improve the video transmission and storage on line, a transcoding method from H.264/AVC to HEVC is proposed. In this transcoding algorithm, the coding information of intraprediction, interprediction, and motion vector (MV) in H.264/AVC video stream are used to accelerate the coding in HEVC. It is found through experiments that the region of interprediction in HEVC overlaps that in H.264/AVC. Therefore, the intraprediction for the region in HEVC, which is interpredicted in H.264/AVC, can be skipped to reduce coding complexity. Several macroblocks in H.264/AVC are combined into one PU in HEVC when the MV difference between two of the macroblocks in H.264/AVC is lower than a threshold. This method selects only one coding unit depth and one prediction unit (PU) mode to reduce the coding complexity. An MV interpolation method of combined PU in HEVC is proposed according to the areas and distances between the center of one macroblock in H.264/AVC and that of the PU in HEVC. The predicted MV accelerates the motion estimation for HEVC coding. The simulation results show that our proposed algorithm achieves significant coding time reduction with a little loss in bitrates distortion rate, compared to the existing transcoding algorithms and normal HEVC coding.

Availability and performance of image/video-based vital signs monitoring methods: a systematic review protocol

Directory of Open Access Journals (Sweden)

Mirae Harford

2017-10-01

Full Text Available Abstract Background For many vital signs, monitoring methods require contact with the patient and/or are invasive in nature. There is increasing interest in developing still and video image-guided monitoring methods that are non-contact and non-invasive. We will undertake a systematic review of still and video image-based monitoring methods. Methods We will perform searches in multiple databases which include MEDLINE, Embase, CINAHL, Cochrane library, IEEE Xplore and ACM Digital Library. We will use OpenGrey and Google searches to access unpublished or commercial data. We will not use language or publication date restrictions. The primary goal is to summarise current image-based vital signs monitoring methods, limited to heart rate, respiratory rate, oxygen saturations and blood pressure. Of particular interest will be the effectiveness of image-based methods compared to reference devices. Other outcomes of interest include the quality of the method comparison studies with respect to published reporting guidelines, any limitations of non-contact non-invasive technology and application in different populations. Discussion To the best of our knowledge, this is the first systematic review of image-based non-contact methods of vital signs monitoring. Synthesis of currently available technology will facilitate future research in this highly topical area. Systematic review registration PROSPERO CRD42016029167

Penyembunyian Data pada File Video Menggunakan Metode LSB dan DCT

Directory of Open Access Journals (Sweden)

Mahmuddin Yunus

2014-01-01

Full Text Available Abstrak Penyembunyian data pada file video dikenal dengan istilah steganografi video. Metode steganografi yang dikenal diantaranya metode Least Significant Bit (LSB dan Discrete Cosine Transform (DCT. Dalam penelitian ini dilakukan penyembunyian data pada file video dengan menggunakan metode LSB, metode DCT, dan gabungan metode LSB-DCT. Sedangkan kualitas file video yang dihasilkan setelah penyisipan dihitung dengan menggunakan Mean Square Error (MSE dan Peak Signal to Noise Ratio (PSNR.Uji eksperimen dilakukan berdasarkan ukuran file video, ukuran file berkas rahasia yang disisipkan, dan resolusi video. Hasil pengujian menunjukkan tingkat keberhasilan steganografi video dengan menggunakan metode LSB adalah 38%, metode DCT adalah 90%, dan gabungan metode LSB-DCT adalah 64%. Sedangkan hasil perhitungan MSE, nilai MSE metode DCT paling rendah dibandingkan metode LSB dan gabungan metode LSB-DCT. Sedangkan metode LSB-DCT mempunyai nilai yang lebih kecil dibandingkan metode LSB. Pada pengujian PSNR diperoleh databahwa nilai PSNR metode DCTlebih tinggi dibandingkan metode LSB dan gabungan metode LSB-DCT. Sedangkan nilai PSNR metode gabungan LSB-DCT lebih tinggi dibandingkan metode LSB.   Kata Kunci— Steganografi, Video, Least Significant Bit (LSB, Discrete Cosine Transform (DCT, Mean Square Error (MSE, Peak Signal to Noise Ratio (PSNR                             Abstract Hiding data in video files is known as video steganography. Some of the well known steganography methods areLeast Significant Bit (LSB and Discrete Cosine Transform (DCT method. In this research, data will be hidden on the video file with LSB method, DCT method, and the combined method of LSB-DCT. While the quality result of video file after insertion is calculated using the Mean Square Error (MSE and Peak Signal to Noise Ratio (PSNR. The experiments were conducted based on the size of the video file, the file size of the inserted secret files, and

Research on quality metrics of wireless adaptive video streaming

Science.gov (United States)

Li, Xuefei

2018-04-01

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

Content-Aware Video Adaptation under Low-Bitrate Constraint

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Hsiao Ming-Ho

2007-01-01

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

Hierarchical Spatio-Temporal Probabilistic Graphical Model with Multiple Feature Fusion for Binary Facial Attribute Classification in Real-World Face Videos.

Science.gov (United States)

Demirkus, Meltem; Precup, Doina; Clark, James J; Arbel, Tal

2016-06-01

Recent literature shows that facial attributes, i.e., contextual facial information, can be beneficial for improving the performance of real-world applications, such as face verification, face recognition, and image search. Examples of face attributes include gender, skin color, facial hair, etc. How to robustly obtain these facial attributes (traits) is still an open problem, especially in the presence of the challenges of real-world environments: non-uniform illumination conditions, arbitrary occlusions, motion blur and background clutter. What makes this problem even more difficult is the enormous variability presented by the same subject, due to arbitrary face scales, head poses, and facial expressions. In this paper, we focus on the problem of facial trait classification in real-world face videos. We have developed a fully automatic hierarchical and probabilistic framework that models the collective set of frame class distributions and feature spatial information over a video sequence. The experiments are conducted on a large real-world face video database that we have collected, labelled and made publicly available. The proposed method is flexible enough to be applied to any facial classification problem. Experiments on a large, real-world video database McGillFaces [1] of 18,000 video frames reveal that the proposed framework outperforms alternative approaches, by up to 16.96 and 10.13%, for the facial attributes of gender and facial hair, respectively.

Algorithm for Video Summarization of Bronchoscopy Procedures

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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

3D video

CERN Document Server

Lucas, Laurent; Loscos, Céline

2013-01-01

While 3D vision has existed for many years, the use of 3D cameras and video-based modeling by the film industry has induced an explosion of interest for 3D acquisition technology, 3D content and 3D displays. As such, 3D video has become one of the new technology trends of this century.The chapters in this book cover a large spectrum of areas connected to 3D video, which are presented both theoretically and technologically, while taking into account both physiological and perceptual aspects. Stepping away from traditional 3D vision, the authors, all currently involved in these areas, provide th

A video-based approach to calibrating car-following parameters in VISSIM for urban traffic

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Zhengyang Lu

2016-08-01

Full Text Available Microscopic simulation models need to be calibrated to represent realistic local traffic conditions. Traditional calibration methods are conducted by searching for the model parameter set that minimizes the discrepancies of certain macroscopic metrics between simulation results and field observations. However, this process could easily lead to inappropriate selection of calibration parameters and thus erroneous simulation results. This paper proposes a video-based approach to incorporate direct measurements of car-following parameters into the process of VISSIM model calibration. The proposed method applies automated video processing techniques to extract vehicle trajectory data and utilizes the trajectory data to determine values of certain car-following parameters in VISSIM. This paper first describes the calibration procedure step by step, and then applies the method to a case study of simulating traffic at a signalized intersection in VISSIM. From the field-collected video footage, trajectories of 1229 through-movement vehicles were extracted and analyzed to calibrate three car-following parameters regarding desired speed, desired acceleration, and safe following distance, respectively. The case study demonstrates the advantages and feasibility of the proposed approach.

Online Detection of Abnormal Events in Video Streams

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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.

Availability and performance of image/video-based vital signs monitoring methods: a systematic review protocol.

Science.gov (United States)

Harford, Mirae; Catherall, Jacqueline; Gerry, Stephen; Young, Duncan; Watkinson, Peter

2017-10-25

For many vital signs, monitoring methods require contact with the patient and/or are invasive in nature. There is increasing interest in developing still and video image-guided monitoring methods that are non-contact and non-invasive. We will undertake a systematic review of still and video image-based monitoring methods. We will perform searches in multiple databases which include MEDLINE, Embase, CINAHL, Cochrane library, IEEE Xplore and ACM Digital Library. We will use OpenGrey and Google searches to access unpublished or commercial data. We will not use language or publication date restrictions. The primary goal is to summarise current image-based vital signs monitoring methods, limited to heart rate, respiratory rate, oxygen saturations and blood pressure. Of particular interest will be the effectiveness of image-based methods compared to reference devices. Other outcomes of interest include the quality of the method comparison studies with respect to published reporting guidelines, any limitations of non-contact non-invasive technology and application in different populations. To the best of our knowledge, this is the first systematic review of image-based non-contact methods of vital signs monitoring. Synthesis of currently available technology will facilitate future research in this highly topical area. PROSPERO CRD42016029167.

Use of Video Modeling to Teach Extinguishing of Cooking Related Fires to Individuals with Moderate Intellectual Disabilities

Science.gov (United States)

Mechling, Linda C.; Gast, David L.; Gustafson, Melissa R.

2009-01-01

This study evaluated the effectiveness of video modeling to teach fire extinguishing behaviors to three young adults with moderate intellectual disabilities. A multiple probe design across three fire extinguishing behaviors and replicated across three students was used to evaluate the effectiveness of the video-based program. Results indicate that…

Kalman Filter Based Tracking in an Video Surveillance System

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SULIMAN, C.

2010-05-01

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

Video-documentation: 'The Pannonic ozon project'

International Nuclear Information System (INIS)

Loibl, W.; Cabela, E.; Mayer, H. F.; Schmidt, M.

1998-07-01

Goal of the project was the production of a video film as documentation of the Pannonian Ozone Project- POP. The main part of the video describes the POP-model consisting of the modules meteorology, emissions and chemistry, developed during the POP-project. The model considers the European emission patterns of ozone precursors and the actual wind fields. It calculates ozone build up and depletion within air parcels due to emission and weather situation along trajectory routes. Actual ozone concentrations are calculated during model runs simulating the photochemical processes within air parcels moving along 4 day trajectories before reaching the Vienna region. The model computations were validated during extensive ground and aircraft-based measurements of ozone precursors and ozone concentration within the POP study area. Scenario computations were used to determine how much ozone can be reduced in north-eastern Austria by emissions control measures. The video lasts 12:20 minutes and consists of computer animations and life video scenes, presenting the ozone problem in general, the POP model and the model results. The video was produced in co-operation by the Austrian Research Center Seibersdorf - Department of Environmental Planning (ARCS) and Joanneum Research - Institute of Informationsystems (JR). ARCS was responsible for idea, concept, storyboard and text while JR was responsible for computer animation and general video production. The speaker text was written with scientific advice by the POP - project partners: Institute of Meteorology and Physics, University of Agricultural Sciences- Vienna, Environment Agency Austria - Air Quality Department, Austrian Research Center Seibersdorf- Environmental Planning Department/System Research Division. The film was produced as German and English version. (author)

Video Tutorial of Continental Food

Science.gov (United States)

Nurani, A. S.; Juwaedah, A.; Mahmudatussa'adah, A.

2018-02-01

This research is motivated by the belief in the importance of media in a learning process. Media as an intermediary serves to focus on the attention of learners. Selection of appropriate learning media is very influential on the success of the delivery of information itself both in terms of cognitive, affective and skills. Continental food is a course that studies food that comes from Europe and is very complex. To reduce verbalism and provide more real learning, then the tutorial media is needed. Media tutorials that are audio visual can provide a more concrete learning experience. The purpose of this research is to develop tutorial media in the form of video. The method used is the development method with the stages of analyzing the learning objectives, creating a story board, validating the story board, revising the story board and making video tutorial media. The results show that the making of storyboards should be very thorough, and detailed in accordance with the learning objectives to reduce errors in video capture so as to save time, cost and effort. In video capturing, lighting, shooting angles, and soundproofing make an excellent contribution to the quality of tutorial video produced. In shooting should focus more on tools, materials, and processing. Video tutorials should be interactive and two-way.

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 model linking video gaming, sleep quality, sweet drinks consumption and obesity among children and youth.

Science.gov (United States)

Turel, O; Romashkin, A; Morrison, K M

2017-08-01

There is a growing need to curb paediatric obesity. The aim of this study is to untangle associations between video-game-use attributes and obesity as a first step towards identifying and examining possible interventions. Cross-sectional time-lagged cohort study was employed using parent-child surveys (t1) and objective physical activity and physiological measures (t2) from 125 children/adolescents (mean age = 13.06, 9-17-year-olds) who play video games, recruited from two clinics at a Canadian academic children's hospital. Structural equation modelling and analysis of covariance were employed for inference. The results of the study are as follows: (i) self-reported video-game play duration in the 4-h window before bedtime is related to greater abdominal adiposity (waist-to-height ratio) and this association may be mediated through reduced sleep quality (measured with the Pittsburgh Sleep Quality Index); and (ii) self-reported average video-game session duration is associated with greater abdominal adiposity and this association may be mediated through higher self-reported sweet drinks consumption while playing video games and reduced sleep quality. Video-game play duration in the 4-h window before bedtime, typical video-game session duration, sweet drinks consumption while playing video games and poor sleep quality have aversive associations with abdominal adiposity. Paediatricians and researchers should further explore how these factors can be altered through behavioural or pharmacological interventions as a means to reduce paediatric obesity. © 2017 World Obesity Federation.

Video quality pooling adaptive to perceptual distortion severity.

Science.gov (United States)

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

2013-02-01

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

Subjective video quality comparison of HDTV monitors

Science.gov (United States)

Seo, G.; Lim, C.; Lee, S.; Lee, C.

2009-01-01

HDTV broadcasting services have become widely available. Furthermore, in the upcoming IPTV services, HDTV services are important and quality monitoring becomes an issue, particularly in IPTV services. Consequently, there have been great efforts to develop video quality measurement methods for HDTV. On the other hand, most HDTV programs will be watched on digital TV monitors which include LCD and PDP TV monitors. In general, the LCD and PDP TV monitors have different color characteristics and response times. Furthermore, most commercial TV monitors include post-processing to improve video quality. In this paper, we compare subjective video quality of some commercial HD TV monitors to investigate the impact of monitor type on perceptual video quality. We used the ACR method as a subjective testing method. Experimental results show that the correlation coefficients among the HDTV monitors are reasonable high. However, for some video sequences and impairments, some differences in subjective scores were observed.

Code domain steganography in video tracks

Science.gov (United States)

Rymaszewski, Sławomir

2008-01-01

This article is dealing with a practical method of hiding secret information in video stream. Method is dedicated for MPEG-2 stream. The algorithm takes to consider not only MPEG video coding scheme described in standard but also bits PES-packets encapsulation in MPEG-2 Program Stream (PS). This modification give higher capacity and more effective bit rate control for output stream than previously proposed methods.

Learning computer science by watching video games

OpenAIRE

Nagataki, Hiroyuki

2014-01-01

This paper proposes a teaching method that utilizes video games in computer science education. The primary characteristic of this approach is that it utilizes video games as observational materials. The underlying idea is that by observing the computational behavior of a wide variety of video games, learners will easily grasp the fundamental architecture, theory, and technology of computers. The results of a case study conducted indicate that the method enhances the motivation of students for...

Efficient Delivery of Scalable Video Using a Streaming Class Model

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Jason J. Quinlan

2018-03-01

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

Theory and practice of perceptual video processing in broadcast encoders for cable, IPTV, satellite, and internet distribution

Science.gov (United States)

McCarthy, S.

2014-02-01

This paper describes the theory and application of a perceptually-inspired video processing technology that was recently incorporated into professional video encoders now being used by major cable, IPTV, satellite, and internet video service providers. We will present data that show that this perceptual video processing (PVP) technology can improve video compression efficiency by up to 50% for MPEG-2, H.264, and High Efficiency Video Coding (HEVC). The PVP technology described in this paper works by forming predicted eye-tracking attractor maps that indicate how likely it might be that a free viewing person would look at particular area of an image or video. We will introduce in this paper the novel model and supporting theory used to calculate the eye-tracking attractor maps. We will show how the underlying perceptual model was inspired by electrophysiological studies of the vertebrate retina, and will explain how the model incorporates statistical expectations about natural scenes as well as a novel method for predicting error in signal estimation tasks. Finally, we will describe how the eye-tracking attractor maps are created in real time and used to modify video prior to encoding so that it is more compressible but not noticeably different than the original unmodified video.

How the “Understanding Research Evidence” Web-Based Video Series From the National Collaborating Centre for Methods and Tools Contributes to Public Health Capacity to Practice Evidence-Informed Decision Making: Mixed-Methods Evaluation

Science.gov (United States)

Chan, Linda; Mackintosh, Jeannie

2017-01-01

Background The National Collaborating Centre for Methods and Tools (NCCMT) offers workshops and webinars to build public health capacity for evidence-informed decision-making. Despite positive feedback for NCCMT workshops and resources, NCCMT users found key terms used in research papers difficult to understand. The Understanding Research Evidence (URE) videos use plain language, cartoon visuals, and public health examples to explain complex research concepts. The videos are posted on the NCCMT website and YouTube channel. Objective The first four videos in the URE web-based video series, which explained odds ratios (ORs), confidence intervals (CIs), clinical significance, and forest plots, were evaluated. The evaluation examined how the videos affected public health professionals’ practice. A mixed-methods approach was used to examine the delivery mode and the content of the videos. Specifically, the evaluation explored (1) whether the videos were effective at increasing knowledge on the four video topics, (2) whether public health professionals were satisfied with the videos, and (3) how public health professionals applied the knowledge gained from the videos in their work. Methods A three-part evaluation was conducted to determine the effectiveness of the first four URE videos. The evaluation included a Web-based survey, telephone interviews, and pretest and posttests, which evaluated public health professionals’ experience with the videos and how the videos affected their public health work. Participants were invited to participate in this evaluation through various open access, public health email lists, through informational flyers and posters at the Canadian Public Health Association (CPHA) conference, and through targeted recruitment to NCCMT’s network. Results In the Web-based surveys (n=46), participants achieved higher scores on the knowledge assessment questions from watching the OR (P=.04), CI (P=.04), and clinical significance (P=.05) videos but

Consumer-based technology for distribution of surgical videos for objective evaluation.

Science.gov (United States)

Gonzalez, Ray; Martinez, Jose M; Lo Menzo, Emanuele; Iglesias, Alberto R; Ro, Charles Y; Madan, Atul K

2012-08-01

The Global Operative Assessment of Laparoscopic Skill (GOALS) is one validated metric utilized to grade laparoscopic skills and has been utilized to score recorded operative videos. To facilitate easier viewing of these recorded videos, we are developing novel techniques to enable surgeons to view these videos. The objective of this study is to determine the feasibility of utilizing widespread current consumer-based technology to assist in distributing appropriate videos for objective evaluation. Videos from residents were recorded via a direct connection from the camera processor via an S-video output via a cable into a hub to connect to a standard laptop computer via a universal serial bus (USB) port. A standard consumer-based video editing program was utilized to capture the video and record in appropriate format. We utilized mp4 format, and depending on the size of the file, the videos were scaled down (compressed), their format changed (using a standard video editing program), or sliced into multiple videos. Standard available consumer-based programs were utilized to convert the video into a more appropriate format for handheld personal digital assistants. In addition, the videos were uploaded to a social networking website and video sharing websites. Recorded cases of laparoscopic cholecystectomy in a porcine model were utilized. Compression was required for all formats. All formats were accessed from home computers, work computers, and iPhones without difficulty. Qualitative analyses by four surgeons demonstrated appropriate quality to grade for these formats. Our preliminary results show promise that, utilizing consumer-based technology, videos can be easily distributed to surgeons to grade via GOALS via various methods. Easy accessibility may help make evaluation of resident videos less complicated and cumbersome.

Sunglass detection method for automation of video surveillance system

Science.gov (United States)

Sikandar, Tasriva; Samsudin, Wan Nur Azhani W.; Hawari Ghazali, Kamarul; Mohd, Izzeldin I.; Fazle Rabbi, Mohammad

2018-04-01

Wearing sunglass to hide face from surveillance camera is a common activity in criminal incidences. Therefore, sunglass detection from surveillance video has become a demanding issue in automation of security systems. In this paper we propose an image processing method to detect sunglass from surveillance images. Specifically, a unique feature using facial height and width has been employed to identify the covered region of the face. The presence of covered area by sunglass is evaluated using facial height-width ratio. Threshold value of covered area percentage is used to classify the glass wearing face. Two different types of glasses have been considered i.e. eye glass and sunglass. The results of this study demonstrate that the proposed method is able to detect sunglasses in two different illumination conditions such as, room illumination as well as in the presence of sunlight. In addition, due to the multi-level checking in facial region, this method has 100% accuracy of detecting sunglass. However, in an exceptional case where fabric surrounding the face has similar color as skin, the correct detection rate was found 93.33% for eye glass.

Digital video transcoding for transmission and storage

CERN Document Server

Sun, Huifang; Chen, Xuemin

2004-01-01

Professionals in the video and multimedia industries need a book that explains industry standards for video coding and how to convert the compressed information between standards. Digital Video Transcoding for Transmission and Storage answers this demand while also supplying the theories and principles of video compression and transcoding technologies. Emphasizing digital video transcoding techniques, this book summarizes its content via examples of practical methods for transcoder implementation. It relates almost all of its featured transcoding technologies to practical applications.This vol

Rate-distortion optimization for compressive video sampling

Science.gov (United States)

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

2014-05-01

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

Multimodal Semantics Extraction from User-Generated Videos

Directory of Open Access Journals (Sweden)

Francesco Cricri

2012-01-01

Full Text Available User-generated video content has grown tremendously fast to the point of outpacing professional content creation. In this work we develop methods that analyze contextual information of multiple user-generated videos in order to obtain semantic information about public happenings (e.g., sport and live music events being recorded in these videos. One of the key contributions of this work is a joint utilization of different data modalities, including such captured by auxiliary sensors during the video recording performed by each user. In particular, we analyze GPS data, magnetometer data, accelerometer data, video- and audio-content data. We use these data modalities to infer information about the event being recorded, in terms of layout (e.g., stadium, genre, indoor versus outdoor scene, and the main area of interest of the event. Furthermore we propose a method that automatically identifies the optimal set of cameras to be used in a multicamera video production. Finally, we detect the camera users which fall within the field of view of other cameras recording at the same public happening. We show that the proposed multimodal analysis methods perform well on various recordings obtained in real sport events and live music performances.

Video Modeling: A Visually Based Intervention for Children with Autism Spectrum Disorder

Science.gov (United States)

Ganz, Jennifer B.; Earles-Vollrath, Theresa L.; Cook, Katherine E.

2011-01-01

Visually based interventions such as video modeling have been demonstrated to be effective with students with autism spectrum disorder (ASD). This approach has wide utility, is appropriate for use with students of a range of ages and abilities, promotes independent functioning, and can be used to address numerous learner objectives, including…

Using Video Models to Teach Students with Disabilities to Play the Wii

Science.gov (United States)

Sherrow, Lauren A.; Spriggs, Amy D.; Knight, Victoria F.

2016-01-01

This study investigated effects of video modeling (VM) when teaching recreation and leisure skills to three high school students with moderate intellectual disabilities and autism spectrum disorder. Results, evaluated via a multiple probe across participants design, indicated that VM was effective for teaching all students to play the Wii.…

Low complexity video encoding for UAV inspection

DEFF Research Database (Denmark)

Søgaard, Jacob; Zhang, Ruo; Forchhammer, Søren

2016-01-01

In this work we present several methods for fast integer motion estimation of videos recorded aboard an Unmanned Aerial Vehicle (UAV). Different from related work, the field depth is not considered to be consistent. The novel methods designed for low complexity MV prediction in H.264/AVC and anal......In this work we present several methods for fast integer motion estimation of videos recorded aboard an Unmanned Aerial Vehicle (UAV). Different from related work, the field depth is not considered to be consistent. The novel methods designed for low complexity MV prediction in H.264/AVC...... for UAV infrared (IR) video are also provided....

The effects of video modeling in teaching functional living skills to persons with ASD: A meta-analysis of single-case studies.

Science.gov (United States)

Hong, Ee Rea; Ganz, Jennifer B; Mason, Rose; Morin, Kristi; Davis, John L; Ninci, Jennifer; Neely, Leslie C; Boles, Margot B; Gilliland, Whitney D

2016-10-01

Many individuals with autism spectrum disorders (ASD) show deficits in functional living skills, leading to low independence, limited community involvement, and poor quality of life. With development of mobile devices, utilizing video modeling has become more feasible for educators to promote functional living skills of individuals with ASD. This article aims to review the single-case experimental literature and aggregate results across studies involving the use of video modeling to improve functional living skills of individuals with ASD. The authors extracted data from single-case experimental studies and evaluated them using the Tau-U effect size measure. Effects were also differentiated by categories of potential moderators and other variables, including age of participants, concomitant diagnoses, types of video modeling, and outcome measures. Results indicate that video modeling interventions are overall moderately effective with this population and dependent measures. While significant differences were not found between categories of moderators and other variables, effects were found to be at least moderate for most of them. It is apparent that more single-case experiments are needed in this area, particularly with preschool and secondary-school aged participants, participants with ASD-only and those with high-functioning ASD, and for video modeling interventions addressing community access skills. Copyright © 2016 Elsevier Ltd. All rights reserved.

No-Reference Video Quality Assessment by HEVC Codec Analysis

DEFF Research Database (Denmark)

Huang, Xin; Søgaard, Jacob; Forchhammer, Søren

2015-01-01

This paper proposes a No-Reference (NR) Video Quality Assessment (VQA) method for videos subject to the distortion given by High Efficiency Video Coding (HEVC). The proposed assessment can be performed either as a BitstreamBased (BB) method or as a Pixel-Based (PB). It extracts or estimates...... the transform coefficients, estimates the distortion, and assesses the video quality. The proposed scheme generates VQA features based on Intra coded frames, and then maps features using an Elastic Net to predict subjective video quality. A set of HEVC coded 4K UHD sequences are tested. Results show...... that the quality scores computed by the proposed method are highly correlated with the subjective assessment....

Training Self-Regulated Learning Skills with Video Modeling Examples: Do Task-Selection Skills Transfer?

Science.gov (United States)

Raaijmakers, Steven F.; Baars, Martine; Schaap, Lydia; Paas, Fred; van Merriënboer, Jeroen; van Gog, Tamara

2018-01-01

Self-assessment and task-selection skills are crucial in self-regulated learning situations in which students can choose their own tasks. Prior research suggested that training with video modeling examples, in which another person (the model) demonstrates and explains the cyclical process of problem-solving task performance, self-assessment, and…

ABOUT SOUNDS IN VIDEO GAMES

Directory of Open Access Journals (Sweden)

Denikin Anton A.

2012-12-01

Full Text Available The article considers the aesthetical and practical possibilities for sounds (sound design in video games and interactive applications. Outlines the key features of the game sound, such as simulation, representativeness, interactivity, immersion, randomization, and audio-visuality. The author defines the basic terminology in study of game audio, as well as identifies significant aesthetic differences between film sounds and sounds in video game projects. It is an attempt to determine the techniques of art analysis for the approaches in study of video games including aesthetics of their sounds. The article offers a range of research methods, considering the video game scoring as a contemporary creative practice.

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.

Roadside video data analysis deep learning

CERN Document Server

Verma, Brijesh; Stockwell, David

2017-01-01

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

Improving Listening And Speaking Skills By Using Animation Videos And Discussion Method

OpenAIRE

Amalia, Rizka

2014-01-01

Listening and speaking are the important skills that have to be mastered by the students. By having these skills, the students can communicate with others easily. There are many strategies that can be used to teach listening and speaking skills. One of the strategies is by using animation videos. Many students of all ages still like watching animation videos for they are interesting. Animation videos can help the students more understand because they present visual context aids that assist th...

Face Recognition and Tracking in Videos

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Swapnil Vitthal Tathe

2017-07-01

Full Text Available Advancement in computer vision technology and availability of video capturing devices such as surveillance cameras has evoked new video processing applications. The research in video face recognition is mostly biased towards law enforcement applications. Applications involves human recognition based on face and iris, human computer interaction, behavior analysis, video surveillance etc. This paper presents face tracking framework that is capable of face detection using Haar features, recognition using Gabor feature extraction, matching using correlation score and tracking using Kalman filter. The method has good recognition rate for real-life videos and robust performance to changes due to illumination, environmental factors, scale, pose and orientations.

Real-time CT-video registration for continuous endoscopic guidance

Science.gov (United States)

Merritt, Scott A.; Rai, Lav; Higgins, William E.

2006-03-01

Previous research has shown that CT-image-based guidance could be useful for the bronchoscopic assessment of lung cancer. This research drew upon the registration of bronchoscopic video images to CT-based endoluminal renderings of the airway tree. The proposed methods either were restricted to discrete single-frame registration, which took several seconds to complete, or required non-real-time buffering and processing of video sequences. We have devised a fast 2D/3D image registration method that performs single-frame CT-Video registration in under 1/15th of a second. This allows the method to be used for real-time registration at full video frame rates without significantly altering the physician's behavior. The method achieves its speed through a gradient-based optimization method that allows most of the computation to be performed off-line. During live registration, the optimization iteratively steps toward the locally optimal viewpoint at which a CT-based endoluminal view is most similar to a current bronchoscopic video frame. After an initial registration to begin the process (generally done in the trachea for bronchoscopy), subsequent registrations are performed in real-time on each incoming video frame. As each new bronchoscopic video frame becomes available, the current optimization is initialized using the previous frame's optimization result, allowing continuous guidance to proceed without manual re-initialization. Tests were performed using both synthetic and pre-recorded bronchoscopic video. The results show that the method is robust to initialization errors, that registration accuracy is high, and that continuous registration can proceed on real-time video at >15 frames per sec. with minimal user-intervention.

Photometric Calibration of Consumer Video Cameras

Science.gov (United States)

Suggs, Robert; Swift, Wesley, Jr.

2007-01-01

Equipment and techniques have been developed to implement a method of photometric calibration of consumer video cameras for imaging of objects that are sufficiently narrow or sufficiently distant to be optically equivalent to point or line sources. Heretofore, it has been difficult to calibrate consumer video cameras, especially in cases of image saturation, because they exhibit nonlinear responses with dynamic ranges much smaller than those of scientific-grade video cameras. The present method not only takes this difficulty in stride but also makes it possible to extend effective dynamic ranges to several powers of ten beyond saturation levels. The method will likely be primarily useful in astronomical photometry. There are also potential commercial applications in medical and industrial imaging of point or line sources in the presence of saturation.This development was prompted by the need to measure brightnesses of debris in amateur video images of the breakup of the Space Shuttle Columbia. The purpose of these measurements is to use the brightness values to estimate relative masses of debris objects. In most of the images, the brightness of the main body of Columbia was found to exceed the dynamic ranges of the cameras. A similar problem arose a few years ago in the analysis of video images of Leonid meteors. The present method is a refined version of the calibration method developed to solve the Leonid calibration problem. In this method, one performs an endto- end calibration of the entire imaging system, including not only the imaging optics and imaging photodetector array but also analog tape recording and playback equipment (if used) and any frame grabber or other analog-to-digital converter (if used). To automatically incorporate the effects of nonlinearity and any other distortions into the calibration, the calibration images are processed in precisely the same manner as are the images of meteors, space-shuttle debris, or other objects that one seeks to

Video Waterscrambling: Towards a Video Protection Scheme Based on the Disturbance of Motion Vectors

Science.gov (United States)

Bodo, Yann; Laurent, Nathalie; Laurent, Christophe; Dugelay, Jean-Luc

2004-12-01

With the popularity of high-bandwidth modems and peer-to-peer networks, the contents of videos must be highly protected from piracy. Traditionally, the models utilized to protect this kind of content are scrambling and watermarking. While the former protects the content against eavesdropping (a priori protection), the latter aims at providing a protection against illegal mass distribution (a posteriori protection). Today, researchers agree that both models must be used conjointly to reach a sufficient level of security. However, scrambling works generally by encryption resulting in an unintelligible content for the end-user. At the moment, some applications (such as e-commerce) may require a slight degradation of content so that the user has an idea of the content before buying it. In this paper, we propose a new video protection model, called waterscrambling, whose aim is to give such a quality degradation-based security model. This model works in the compressed domain and disturbs the motion vectors, degrading the video quality. It also allows embedding of a classical invisible watermark enabling protection against mass distribution. In fact, our model can be seen as an intermediary solution to scrambling and watermarking.

Video Waterscrambling: Towards a Video Protection Scheme Based on the Disturbance of Motion Vectors

Directory of Open Access Journals (Sweden)

Yann Bodo

2004-10-01

Full Text Available With the popularity of high-bandwidth modems and peer-to-peer networks, the contents of videos must be highly protected from piracy. Traditionally, the models utilized to protect this kind of content are scrambling and watermarking. While the former protects the content against eavesdropping (a priori protection, the latter aims at providing a protection against illegal mass distribution (a posteriori protection. Today, researchers agree that both models must be used conjointly to reach a sufficient level of security. However, scrambling works generally by encryption resulting in an unintelligible content for the end-user. At the moment, some applications (such as e-commerce may require a slight degradation of content so that the user has an idea of the content before buying it. In this paper, we propose a new video protection model, called waterscrambling, whose aim is to give such a quality degradation-based security model. This model works in the compressed domain and disturbs the motion vectors, degrading the video quality. It also allows embedding of a classical invisible watermark enabling protection against mass distribution. In fact, our model can be seen as an intermediary solution to scrambling and watermarking.

Teaching Generalized Imitation Skills to a Preschooler with Autism Using Video Modeling

Science.gov (United States)

Kleeberger, Vickie; Mirenda, Pat

2010-01-01

This study examined the effectiveness of video modeling to teach a preschooler with autism to imitate previously mastered and not mastered actions during song and toy play activities. A general case approach was used to examine the instructional universe of preschool songs and select exemplars that were most likely to facilitate generalization.…

Comparative study of methods for recognition of an unknown person's action from a video sequence

Science.gov (United States)

Hori, Takayuki; Ohya, Jun; Kurumisawa, Jun

2009-02-01

This paper proposes a Tensor Decomposition Based method that can recognize an unknown person's action from a video sequence, where the unknown person is not included in the database (tensor) used for the recognition. The tensor consists of persons, actions and time-series image features. For the observed unknown person's action, one of the actions stored in the tensor is assumed. Using the motion signature obtained from the assumption, the unknown person's actions are synthesized. The actions of one of the persons in the tensor are replaced by the synthesized actions. Then, the core tensor for the replaced tensor is computed. This process is repeated for the actions and persons. For each iteration, the difference between the replaced and original core tensors is computed. The assumption that gives the minimal difference is the action recognition result. For the time-series image features to be stored in the tensor and to be extracted from the observed video sequence, the human body silhouette's contour shape based feature is used. To show the validity of our proposed method, our proposed method is experimentally compared with Nearest Neighbor rule and Principal Component analysis based method. Experiments using 33 persons' seven kinds of action show that our proposed method achieves better recognition accuracies for the seven actions than the other methods.

Is video gaming, or video game addiction, associated with depression, academic achievement, heavy episodic drinking, or conduct problems?

Science.gov (United States)

Brunborg, Geir Scott; Mentzoni, Rune Aune; Frøyland, Lars Roar

2014-03-01

While the relationships between video game use and negative consequences are debated, the relationships between video game addiction and negative consequences are fairly well established. However, previous studies suffer from methodological weaknesses that may have caused biased results. There is need for further investigation that benefits from the use of methods that avoid omitted variable bias. Two wave panel data was used from two surveys of 1,928 Norwegian adolescents aged 13 to 17 years. The surveys included measures of video game use, video game addiction, depression, heavy episodic drinking, academic achievement, and conduct problems. The data was analyzed using first-differencing, a regression method that is unbiased by time invariant individual factors. Video game addiction was related to depression, lower academic achievement, and conduct problems, but time spent on video games was not related to any of the studied negative outcomes. The findings were in line with a growing number of studies that have failed to find relationships between time spent on video games and negative outcomes. The current study is also consistent with previous studies in that video game addiction was related to other negative outcomes, but it made the added contribution that the relationships are unbiased by time invariant individual effects. However, future research should aim at establishing the temporal order of the supposed causal effects. Spending time playing video games does not involve negative consequences, but adolescents who experience problems related to video games are likely to also experience problems in other facets of life.

Attention to the Model's Face When Learning from Video Modeling Examples in Adolescents with and without Autism Spectrum Disorder

Science.gov (United States)

van Wermeskerken, Margot; Grimmius, Bianca; van Gog, Tamara

2018-01-01

We investigated the effects of seeing the instructor's (i.e., the model's) face in video modeling examples on students' attention and their learning outcomes. Research with university students suggested that the model's face attracts students' attention away from what the model is doing, but this did not hamper learning. We aimed to investigate…

It’s all a matter of perspective : Viewing first-person video modeling examples promotes learning of an assembly task

NARCIS (Netherlands)

Fiorella, Logan; van Gog, T.; Hoogerheide, V.; Mayer, Richard

2017-01-01

The present study tests whether presenting video modeling examples from the learner’s (first-person) perspective promotes learning of an assembly task, compared to presenting video examples from a third-person perspective. Across 2 experiments conducted in different labs, university students viewed

Sending Safety Video over WiMAX in Vehicle Communications

Directory of Open Access Journals (Sweden)

Jun Steed Huang

2013-10-01

Full Text Available This paper reports on the design of an OPNET simulation platform to test the performance of sending real-time safety video over VANET (Vehicular Adhoc NETwork using the WiMAX technology. To provide a more realistic environment for streaming real-time video, a video model was created based on the study of video traffic traces captured from a realistic vehicular camera, and different design considerations were taken into account. A practical controller over real-time streaming protocol is implemented to control data traffic congestion for future road safety development. Our driving video model was then integrated with the WiMAX OPNET model along with a mobility model based on real road maps. Using this simulation platform, different mobility cases have been studied and the performance evaluated in terms of end-to-end delay, jitter and visual experience.

Video Modeling of SBIRT for Alcohol Use Disorders Increases Student Empathy in Standardized Patient Encounters.

Science.gov (United States)

Crisafio, Anthony; Anderson, Victoria; Frank, Julia

2018-04-01

The purpose of this study was to assess the usefulness of adding video models of brief alcohol assessment and counseling to a standardized patient (SP) curriculum that covers and tests acquisition of this skill. The authors conducted a single-center, retrospective cohort study of third- and fourth-year medical students between 2013 and 2015. All students completed a standardized patient (SP) encounter illustrating the diagnosis of alcohol use disorder, followed by an SP exam on the same topic. Beginning in August 2014, the authors supplemented the existing formative SP exercise on problem drinking with one of two 5-min videos demonstrating screening, brief intervention, and referral for treatment (SBIRT). P values and Z tests were performed to evaluate differences between students who did and did not see the video in knowledge and skills related to alcohol use disorders. One hundred ninety-four students were included in this analysis. Compared to controls, subjects did not differ in their ability to uncover and accurately characterize an alcohol problem during a standardized encounter (mean exam score 41.29 vs 40.93, subject vs control, p = 0.539). However, the SPs' rating of students' expressions of empathy were significantly higher for the group who saw the video (81.63 vs 69.79%, p videos would improve students' recognition and knowledge of alcohol-related conditions. However, feedback from the SPs produced the serendipitous finding that the communication skills demonstrated in the videos had a sustained effect in enhancing students' professional behavior.

THE DETERMINATION OF THE SHARPNESS DEPTH BORDERS AND CORRESPONDING PHOTOGRAPHY AND VIDEO RECORDING PARAMETERS FOR CONTEMPORARY VIDEO TECHNOLOGY