View-Dependent Dynamic Point Cloud Compression
Dynamic point cloud (DPC) captures 3D object and scene with realistic appearance to mimic the natural reality. It inherently offers the six-degree-of-freedom (6DoF) for content consumption, which motivates us to facilitate the network-friendly view-dependent DPC streaming by leveraging the limited f...
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| Vydáno v: | IEEE transactions on circuits and systems for video technology Ročník 31; číslo 2; s. 765 - 781 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York
IEEE
01.02.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1051-8215, 1558-2205 |
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| Abstract | Dynamic point cloud (DPC) captures 3D object and scene with realistic appearance to mimic the natural reality. It inherently offers the six-degree-of-freedom (6DoF) for content consumption, which motivates us to facilitate the network-friendly view-dependent DPC streaming by leveraging the limited field of view of the human visual system (HVS) at specific moments, for significant network bandwidth reduction without the quality of experience (QoE) loss. Therefore, in this work, we propose the view-dependent DPC compression, noted as View-PCC, by which we can enable instantaneous and complete view reconstruction from partial streams, and 6DoF navigation by stream adaptation. These functionalities are offered by the hybrid global and local projection to effectively map 3D points to five perpendicular 2D image planes of a cube. Multi-view and multi-layer based global projection is first applied progressively and followed by the patch-based local projection with both intra-frame displaced arrangement and inter-frame temporal alignment, so as to maximize the number of effectively projected points and preserve the spatio-temporal coherency for better compression. Boundary padding is then augmented for each image plane that will be encoded using the successful 2D video coding standard - High-Efficiency Video Coding (HEVC). Our extensive simulations have shown the noticeable objective compression gains of View-PCC when compared with the typical octree-based approach and global-projection-based method. The subjective quality assessment suggests the better reconstruction quality of View-PCC, in comparison to the MPEG video-based point cloud compression (V-PCC). |
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| AbstractList | Dynamic point cloud (DPC) captures 3D object and scene with realistic appearance to mimic the natural reality. It inherently offers the six-degree-of-freedom (6DoF) for content consumption, which motivates us to facilitate the network-friendly view-dependent DPC streaming by leveraging the limited field of view of the human visual system (HVS) at specific moments, for significant network bandwidth reduction without the quality of experience (QoE) loss. Therefore, in this work, we propose the view-dependent DPC compression, noted as View-PCC, by which we can enable instantaneous and complete view reconstruction from partial streams, and 6DoF navigation by stream adaptation. These functionalities are offered by the hybrid global and local projection to effectively map 3D points to five perpendicular 2D image planes of a cube. Multi-view and multi-layer based global projection is first applied progressively and followed by the patch-based local projection with both intra-frame displaced arrangement and inter-frame temporal alignment, so as to maximize the number of effectively projected points and preserve the spatio-temporal coherency for better compression. Boundary padding is then augmented for each image plane that will be encoded using the successful 2D video coding standard - High-Efficiency Video Coding (HEVC). Our extensive simulations have shown the noticeable objective compression gains of View-PCC when compared with the typical octree-based approach and global-projection-based method. The subjective quality assessment suggests the better reconstruction quality of View-PCC, in comparison to the MPEG video-based point cloud compression (V-PCC). |
| Author | Li, Li Ma, Zhan Li, Zhu Xu, Yiling Zhu, Wenjie |
| Author_xml | – sequence: 1 givenname: Wenjie orcidid: 0000-0003-3121-6181 surname: Zhu fullname: Zhu, Wenjie email: rebecca28@sjtu.edu.cn organization: Cooperative Medianet Innovation Center, Shanghai Jiao Tong University, Shanghai, China – sequence: 2 givenname: Zhan orcidid: 0000-0003-3686-4057 surname: Ma fullname: Ma, Zhan email: mazhan@nju.edu.cn organization: School of Electronic Science and Engineering, Nanjing University, Jiangsu, China – sequence: 3 givenname: Yiling orcidid: 0000-0002-4942-5232 surname: Xu fullname: Xu, Yiling email: yl.xu@sjtu.edu.cn organization: Cooperative Medianet Innovation Center, Shanghai Jiao Tong University, Shanghai, China – sequence: 4 givenname: Li orcidid: 0000-0002-7163-6263 surname: Li fullname: Li, Li email: lil1@umkc.edu organization: Department of Computer Science and Electrical Engineering, University of Missouri-Kansas City, Kansas City, MO, USA – sequence: 5 givenname: Zhu orcidid: 0000-0002-8246-177X surname: Li fullname: Li, Zhu email: lizhu@umkc.edu organization: Department of Computer Science and Electrical Engineering, University of Missouri-Kansas City, Kansas City, MO, USA |
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| SubjectTerms | Bandwidth Coding Coding standards dimensional reduction Dynamic point cloud Field of view Image compression Image reconstruction Multilayers Octrees patch-based local projection Projection Quality assessment Quality of experience Streaming media Three dimensional models Three-dimensional displays Two dimensional displays Video coding Video compression view-based global projection view-dependent |
| Title | View-Dependent Dynamic Point Cloud Compression |
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