Image-Based Rendering Using Point Cloud For 2d Video Compression

2018 PICTURE CODING SYMPOSIUM (PCS 2018)(2018)

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摘要
The main idea of this paper is to extract the 3D scene geometry for the observed scene and use it for synthesizing a more precise prediction using Image-Based Rendering (IBR) for motion compensation in a hybrid coding scheme. The proposed method first extracts camera parameters using Structure from Motion (SfM). Then, a Patch-based Multi-View Stereo (PMVS) technique is employed to generate the scene Point-Cloud (PC) only from already decoded key-frames. Since the PC could be really sparse in poorly reconstructed regions, a depth expansion mechanism is also used. This 3D information helps to properly warp textures from the key-frames to the target frame. This IBR-based prediction is then used as an additional reference for motion compensation. In this way, the encoder can choose between the rendered prediction and the regular reference pictures through a rate-distortion optimization. On average, the simulation results show about 2.16% bitrate reduction compared to the reference HEVC implementation, for tested dynamic and static scene video sequences.
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关键词
PC,decoded key-frames,depth expansion mechanism,IBR-based prediction,motion compensation,rendered prediction,static scene video sequences,2D video compression,3D scene geometry,observed scene,hybrid coding scheme,camera parameters,SfM,bitrate reduction,image-based rendering,structure from motion,patch-based multiview stereo technique,PMVS technique,rate- distortion optimization,HEVC implementation,point cloud
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