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Open AccessJournal ArticleDOI

Loss-Resilient Coding of Texture and Depth for Free-Viewpoint Video Conferencing

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TLDR
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 to contain the adverse effects of network packet losses during texture and depth video transmission.
Abstract
Free-viewpoint video conferencing allows a participant to observe the remote 3D scene from any freely chosen viewpoint. An intermediate virtual viewpoint image is typically 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 goal, 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 pixel samples of voxels that are visible in both views are more error-resiliently coded in one view only, given adaptive blending will mitigate 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. Finally, quantization parameter (QP) is adaptively selected per frame, optimally trading off source distortion due to compression with channel distortion due to potential packet losses. Experimental results show that the proposed scheme can outperform previous work by up to 2.9 dB at 5% packet loss rate.

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Citations
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Journal ArticleDOI

Depth Sensation Enhancement for Multiple Virtual View Rendering

TL;DR: A novel depth sensation enhancement method is proposed to address the problems in multiple virtual view rendering and is extended to video applications with a newly designed energy function with energy term of temporal consistency preservation.
Journal ArticleDOI

Depth Map Super-Resolution Considering View Synthesis Quality

TL;DR: Experimental results demonstrate that the proposed method outperforms state-of-the-art depth SR methods for both super-resolved depth maps and synthesized views and achieves promising results under noise-corruption conditions.
Journal ArticleDOI

Frame Loss Concealment for Multiview Video Transmission Over Wireless Multimedia Sensor Networks

TL;DR: This paper proposes a new technique, which is capable of dealing with the problem of concealing lost whole frames for multiview 3-D video transmission over WMSNs and significantly outperforms other techniques in both objective and subjective quality measurements.
Journal ArticleDOI

Estimation of Virtual View Synthesis Distortion Toward Virtual View Position

TL;DR: An analytical model to estimate the depth-error-induced virtual view synthesis distortion (VVSD) in 3D video, taking the distance between reference and virtual views (virtual view position) into account is proposed.
Journal ArticleDOI

Collaborative Wireless Freeview Video Streaming With Network Coding

TL;DR: PAFV (Peer-Assisted Freeview Video) is proposed, a scalable and effective algorithm that outperforms other algorithms, achieving substantially lower video distortion with significantly less redundancy with significantly more redundancy.
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TL;DR: In this paper, a review of error control and concealment in video communication is presented, which are described in three categories according to the roles that the encoder and decoder play in the underlying approaches.
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