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Compressive sensing depth video coding via gaussian mixture models and object edges
Wang, Kang1; Lan, Xuguang1; Li, Xiangwei(李翔伟)2; Yang, Meng1; Zheng, Nanning1; Lan, Xuguang (xglan@mail.xjtu.edu.cn)1
2018
Conference Name18th Pacific-Rim Conference on Multimedia, PCM 2017
Source PublicationAdvances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers
Volume10735 LNCS
Pages96-104
Conference Date2017-09-28
Conference PlaceHarbin, China
PublisherSpringer Verlag
Contribution Rank2
Abstract

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. © Springer International Publishing AG, part of Springer Nature 2018.

Department光电测量技术实验室
DOI10.1007/978-3-319-77380-3_10
Indexed ByEI ; CPCI
ISBN9783319773797
Language英语
ISSN03029743
WOS IDWOS:000460422000010
EI Accession Number20182205250165
Citation statistics
Document Type会议论文
Identifierhttp://ir.opt.ac.cn/handle/181661/30321
Collection光电测量技术实验室
Corresponding AuthorLan, Xuguang (xglan@mail.xjtu.edu.cn)
Affiliation1.Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China
2.Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, China
Recommended Citation
GB/T 7714
Wang, Kang,Lan, Xuguang,Li, Xiangwei,et al. Compressive sensing depth video coding via gaussian mixture models and object edges[C]:Springer Verlag,2018:96-104.
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