Predictive Generalized Graph Fourier Transform for Attribute Compression of Dynamic Point Clouds

doi:10.1109/TCSVT.2020.3015901

	Predictive Generalized Graph Fourier Transform for Attribute Compression of Dynamic Point Clouds
	Xu, Yiqun 1,2,3; Hu, Wei 4; Wang, Shanshe 3; Zhang, Xinfeng 2; Wang, Shiqi 5; Ma, Siwei 3; Guo, Zongming 4; Gao, Wen 3
	2021-05-01
发表期刊	IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
ISSN	1051-8215
卷号	31 期号:5 页码:1968-1982
摘要	As 3D scanning devices and depth sensors advance, dynamic point clouds have attracted increasing attention as a format for 3D objects in motion, with applications in various fields such as immersive telepresence, navigation for autonomous driving and gaming. Nevertheless, the tremendous amount of data in dynamic point clouds significantly burden transmission and storage. To this end, we propose a complete compression framework for attributes of 3D dynamic point clouds, focusing on optimal inter-coding. Firstly, we derive the optimal inter-prediction and predictive transform coding assuming the Gaussian Markov Random Field model with respect to a spatio-temporal graph underlying the attributes of dynamic point clouds. The optimal predictive transform proves to be the Generalized Graph Fourier Transform in terms of spatio-temporal decorrelation. Secondly, we propose refined motion estimation via efficient registration prior to inter-prediction, which searches the temporal correspondence between adjacent frames of irregular point clouds. Finally, we present a complete framework based on the optimal inter-coding and our previously proposed intra-coding, where we determine the optimal coding mode from rate-distortion optimization with the proposed offline-trained lambda-Q model. Experimental results show that we achieve around 17% bit rate reduction on average over competitive dynamic point cloud compression methods.
关键词	Dynamic point clouds attribute coding inter-coding generalized graph Fourier transform
DOI	10.1109/TCSVT.2020.3015901
收录类别	SCI
语种	英语
资助项目	National Research and Development Project of China[2018YFB1003504] ; National Natural Science Foundation of China[61972009] ; National Natural Science Foundation of China[8201200601] ; Beijing Natural Science Foundation[4194080] ; High-Performance Computing Platform of Peking University
WOS研究方向	Engineering
WOS类目	Engineering, Electrical & Electronic
WOS记录号	WOS:000647394100023
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：30[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/17742
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Hu, Wei; Ma, Siwei
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 100049, Peoples R China 3.Peking Univ, Natl Engn Lab Video Technol, Beijing 100871, Peoples R China 4.Peking Univ, Wangxuan Inst Comp Technol, Beijing 100871, Peoples R China 5.City Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China
推荐引用方式 GB/T 7714	Xu, Yiqun,Hu, Wei,Wang, Shanshe,et al. Predictive Generalized Graph Fourier Transform for Attribute Compression of Dynamic Point Clouds[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2021,31(5):1968-1982.
APA	Xu, Yiqun.,Hu, Wei.,Wang, Shanshe.,Zhang, Xinfeng.,Wang, Shiqi.,...&Gao, Wen.(2021).Predictive Generalized Graph Fourier Transform for Attribute Compression of Dynamic Point Clouds.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,31(5),1968-1982.
MLA	Xu, Yiqun,et al."Predictive Generalized Graph Fourier Transform for Attribute Compression of Dynamic Point Clouds".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 31.5(2021):1968-1982.