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Compressive sensing depth video coding via gaussian mixture models and object edges

  • Xi'an Jiaotong University
  • CAS - Xi'an Institute of Optics and Precision Mechanics

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

In this paper, we propose a novel compressive sensing depth video (CSDV) coding scheme based on Gaussian mixture models (GMM) and object edges. We first compress several depth videos to get CSDV frames in the temporal direction. A whole CSDV frame is divided into a set of non-overlap patches in which object edges is detected by Canny operator to reduce the computational complexity of quantization. Then, we allocate variable bits for different patches based on the percentages of non-zero pixels in every patch. The GMM is used to model the CSDV frame patches and design product vector quantizers to quantize CSDV frames. The experimental results show that our compression scheme achieves a significant Bjontegaard Delta (BD)-PSNR improvement about 2–10 dB when compared to the standard video coding schemes, e.g. Uniform Scalar Quantization-Differential Pulse Code Modulation (USQ-DPCM) and H.265/HEVC.

源语言英语
主期刊名Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers
编辑Bing Zeng, Hongliang Li, Abdulmotaleb El Saddik, Xiaopeng Fan, Shuqiang Jiang, Qingming Huang
出版商Springer Verlag
96-104
页数9
ISBN(印刷版)9783319773797
DOI
出版状态已出版 - 2018
活动18th Pacific-Rim Conference on Multimedia, PCM 2017 - Harbin, 中国
期限: 28 9月 201729 9月 2017

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10735 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议18th Pacific-Rim Conference on Multimedia, PCM 2017
国家/地区中国
Harbin
时期28/09/1729/09/17

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