161 research outputs found

    Loss-resilient Coding of Texture and Depth for Free-viewpoint Video Conferencing

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    Free-viewpoint video conferencing allows a participant to observe the remote 3D scene from any freely chosen viewpoint. An intermediate virtual viewpoint image is commonly synthesized using two pairs of transmitted texture and depth maps from two neighboring captured viewpoints via depth-image-based rendering (DIBR). To maintain high quality of synthesized images, it is imperative to contain the adverse effects of network packet losses that may arise during texture and depth video transmission. Towards this end, we develop an integrated approach that exploits the representation redundancy inherent in the multiple streamed videos a voxel in the 3D scene visible to two captured views is sampled and coded twice in the two views. In particular, at the receiver we first develop an error concealment strategy that adaptively blends corresponding pixels in the two captured views during DIBR, so that pixels from the more reliable transmitted view are weighted more heavily. We then couple it with a sender-side optimization of reference picture selection (RPS) during real-time video coding, so that blocks containing samples of voxels that are visible in both views are more error-resiliently coded in one view only, given adaptive blending will erase errors in the other view. Further, synthesized view distortion sensitivities to texture versus depth errors are analyzed, so that relative importance of texture and depth code blocks can be computed for system-wide RPS optimization. Experimental results show that the proposed scheme can outperform the use of a traditional feedback channel by up to 0.82 dB on average at 8% packet loss rate, and by as much as 3 dB for particular frames

    Rate-distortion optimization for stereoscopic video streaming with unequal error protection

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    We consider an error-resilient stereoscopic streaming system that uses an H.264-based multiview video codec and a rateless Raptor code for recovery from packet losses. One aim of the present work is to suggest a heuristic methodology for modeling the end-to-end rate-distortion (RD) characteristic of such a system. Another aim is to show how to make use of such a model to optimally select the parameters of the video codec and the Raptor code to minimize the overall distortion. Specifically, the proposed system models the RD curve of video encoder and performance of channel codec to jointly derive the optimal encoder bit rates and unequal error protection (UEP) rates specific to the layered stereoscopic video streaming. We define analytical RD curve modeling for each layer that includes the interdependency of these layers. A heuristic analytical model of the performance of Raptor codes is also defined. Furthermore, the distortion on the stereoscopic video quality caused by packet losses is estimated. Finally, analytical models and estimated single-packet loss distortions are used to minimize the end-to-end distortion and to obtain optimal encoder bit rates and UEP rates. The simulation results clearly demonstrate the significant quality gain against the nonoptimized schemes

    Cross-layer Optimized Wireless Video Surveillance

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    A wireless video surveillance system contains three major components, the video capture and preprocessing, the video compression and transmission over wireless sensor networks (WSNs), and the video analysis at the receiving end. The coordination of different components is important for improving the end-to-end video quality, especially under the communication resource constraint. Cross-layer control proves to be an efficient measure for optimal system configuration. In this dissertation, we address the problem of implementing cross-layer optimization in the wireless video surveillance system. The thesis work is based on three research projects. In the first project, a single PTU (pan-tilt-unit) camera is used for video object tracking. The problem studied is how to improve the quality of the received video by jointly considering the coding and transmission process. The cross-layer controller determines the optimal coding and transmission parameters, according to the dynamic channel condition and the transmission delay. Multiple error concealment strategies are developed utilizing the special property of the PTU camera motion. In the second project, the binocular PTU camera is adopted for video object tracking. The presented work studied the fast disparity estimation algorithm and the 3D video transcoding over the WSN for real-time applications. The disparity/depth information is estimated in a coarse-to-fine manner using both local and global methods. The transcoding is coordinated by the cross-layer controller based on the channel condition and the data rate constraint, in order to achieve the best view synthesis quality. The third project is applied for multi-camera motion capture in remote healthcare monitoring. The challenge is the resource allocation for multiple video sequences. The presented cross-layer design incorporates the delay sensitive, content-aware video coding and transmission, and the adaptive video coding and transmission to ensure the optimal and balanced quality for the multi-view videos. In these projects, interdisciplinary study is conducted to synergize the surveillance system under the cross-layer optimization framework. Experimental results demonstrate the efficiency of the proposed schemes. The challenges of cross-layer design in existing wireless video surveillance systems are also analyzed to enlighten the future work. Adviser: Song C

    Cross-layer Optimized Wireless Video Surveillance

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    A wireless video surveillance system contains three major components, the video capture and preprocessing, the video compression and transmission over wireless sensor networks (WSNs), and the video analysis at the receiving end. The coordination of different components is important for improving the end-to-end video quality, especially under the communication resource constraint. Cross-layer control proves to be an efficient measure for optimal system configuration. In this dissertation, we address the problem of implementing cross-layer optimization in the wireless video surveillance system. The thesis work is based on three research projects. In the first project, a single PTU (pan-tilt-unit) camera is used for video object tracking. The problem studied is how to improve the quality of the received video by jointly considering the coding and transmission process. The cross-layer controller determines the optimal coding and transmission parameters, according to the dynamic channel condition and the transmission delay. Multiple error concealment strategies are developed utilizing the special property of the PTU camera motion. In the second project, the binocular PTU camera is adopted for video object tracking. The presented work studied the fast disparity estimation algorithm and the 3D video transcoding over the WSN for real-time applications. The disparity/depth information is estimated in a coarse-to-fine manner using both local and global methods. The transcoding is coordinated by the cross-layer controller based on the channel condition and the data rate constraint, in order to achieve the best view synthesis quality. The third project is applied for multi-camera motion capture in remote healthcare monitoring. The challenge is the resource allocation for multiple video sequences. The presented cross-layer design incorporates the delay sensitive, content-aware video coding and transmission, and the adaptive video coding and transmission to ensure the optimal and balanced quality for the multi-view videos. In these projects, interdisciplinary study is conducted to synergize the surveillance system under the cross-layer optimization framework. Experimental results demonstrate the efficiency of the proposed schemes. The challenges of cross-layer design in existing wireless video surveillance systems are also analyzed to enlighten the future work. Adviser: Song C

    Providing 3D video services: the challenge from 2D to 3DTV quality of experience

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    Recently, three-dimensional (3D) video has decisively burst onto the entertainment industry scene, and has arrived in households even before the standardization process has been completed. 3D television (3DTV) adoption and deployment can be seen as a major leap in television history, similar to previous transitions from black and white (B&W) to color, from analog to digital television (TV), and from standard definition to high definition. In this paper, we analyze current 3D video technology trends in order to define a taxonomy of the availability and possible introduction of 3D-based services. We also propose an audiovisual network services architecture which provides a smooth transition from two-dimensional (2D) to 3DTV in an Internet Protocol (IP)-based scenario. Based on subjective assessment tests, we also analyze those factors which will influence the quality of experience in those 3D video services, focusing on effects of both coding and transmission errors. In addition, examples of the application of the architecture and results of assessment tests are provided

    QoE Enhancement for Stereoscopic 3DVideo Quality Based on Depth and Color Transmission over IP Networks: A Review

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    In this review paper we focus on the enhancement of Quality of Experience (QoE) for stereoscopic 3D video based on depth information. We focus on stereoscopic video format because it takes less bandwidth than other format when 3D video is transmitted over an error channel but it is easily affected by the network parameters such as packets loss, delay and jitter. The packet loss on 3D video has more impact in the depth information than other 3D video factors such as comfort, motion, disparity and discomfort. The packet loss on depth information causes undesired effect on color and depth maps. Therefore, in order to minimize quality degradation, the application of frame loss concealment technique is preferred. This technique is expected to improve the QoE for end users. In this paper we will also review 3D video factors and their challenges, methods of measuring the QOE, algorithms used for packets loss recovery.

    Error resilient stereoscopic video streaming using model-based fountain codes

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    Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Science of Bilkent University, 2009.Thesis (Ph.D.) -- Bilkent University, 2009.Includes bibliographical references leaves 101-110.Error resilient digital video streaming has been a challenging problem since the introduction and deployment of early packet switched networks. One of the most recent advances in video coding is observed on multi-view video coding which suggests methods for the compression of correlated multiple image sequences. The existing multi-view compression techniques increase the loss sensitivity and necessitate the use of efficient loss recovery schemes. Forward Error Correction (FEC) is an efficient, powerful and practical tool for the recovery of lost data. A novel class of FEC codes is Fountain codes which are suitable to be used with recent video codecs, such as H.264/AVC, and LT and Raptor codes are practical examples of this class. Although there are many studies on monoscopic video, transmission of multi-view video through lossy channels with FEC have not been explored yet. Aiming at this deficiency, an H.264-based multi-view video codec and a model-based Fountain code are combined to generate an effi- cient error resilient stereoscopic streaming system. Three layers of stereoscopic video with unequal importance are defined in order to exploit the benefits of Unequal Error Protection (UEP) with FEC. Simply, these layers correspond to intra frames of left view, predicted frames of left view and predicted frames of right view. The Rate-Distortion (RD) characteristics of these dependent layers are de- fined by extending the RD characteristics of monoscopic video. The parameters of the models are obtained with curve fitting using the RD samples of the video, and satisfactory results are achieved where the average difference between the analytical models and RD samples is between 1.00% and 9.19%. An heuristic analytical model of the performance of Raptor codes is used to obtain the residual number of lost packets for given channel bit rate, loss rate, and protection rate. This residual number is multiplied with the estimated average distortion of the loss of a single Network Abstraction Layer (NAL) unit to obtain the total transmission distortion. All these models are combined to minimize the end-toend distortion and obtain optimal encoder bit rates and UEP rates. When the proposed system is used, the simulation results demonstrate up to 2dB increase in quality compared to equal error protection and only left view error protection. Furthermore, Fountain codes are analyzed in the finite length region, and iterative performance models are derived without any assumptions or asymptotical approximations. The performance model of the belief-propagation (BP) decoder approximates either the behavior of a single simulation results or their average depending on the parameters of the LT code. The performance model of the maximum likelihood decoder approximates the average of simulation results more accurately compared to the model of the BP decoder. Raptor codes are modeled heuristically based on the exponential decay observed on the simulation results, and the model parameters are obtained by line of best fit. The analytical models of systematic and non-systematic Raptor codes accurately approximate the experimental average performance.Tan, A SerdarPh.D
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