Spatiotemporal Group Context for Pedestrian Counting

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 图像与视频分析团队

	Spatiotemporal Group Context for Pedestrian Counting
	Wang, Jinqiao1 ; Fu, Wei 1; Liu, Jingjing 2; Lu, Hanqing1
刊名	IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
	2014-09-01
卷号	24 期号:9 页码:1620-1630
关键词	Group context group correspondence matrix Markov-chain Monte Carlo (MCMC) pedestrian counting
英文摘要	Pedestrian counting has been a challenging topic, especially in video surveillance, for a long time due to the view variations, scale changes, and spatial occlusions. While most of the previous approaches try to count people within one frame, our approach addresses this problem with a group context model, which is to segment individuals into groups and model the spatiotemporal relationships between them. With the basic definitions of the group state, group event, and group relative, a group correspondence matrix is built to model the bidirectional correspondences between the groups in two consecutive frames. Then, a group context is modeled with a sequence of context masks, which encodes not only the spatiotemporal changes within a group, but also the historical relevance and spatial dependency between different groups. Finally, we assemble context masks from multiple frames and formulate the problem of pedestrian counting as a joint maximum a posteriori problem. Markov-chain Monte Carlo is utilized to search for an optimal configuration set to match the group context model. Comprehensive experiments on the PETS2009 data set and UCSD pedestrian data set show the promising performance of the proposed approach.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Engineering, Electrical & Electronic
研究领域[WOS]	Engineering
关键词[WOS]	PART DETECTORS ; CROWDED SCENES ; SEGMENTATION ; MULTIPLE ; TRACKING ; IMAGE
收录类别	SCI
语种	英语
WOS记录号	WOS:000341981900013
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/3340]
专题	自动化研究所_模式识别国家重点实验室_图像与视频分析团队
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Rutgers State Univ, Dept Comp Sci, Piscataway, NJ 08901 USA
推荐引用方式 GB/T 7714	Wang, Jinqiao,Fu, Wei,Liu, Jingjing,et al. Spatiotemporal Group Context for Pedestrian Counting[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2014,24(9):1620-1630.
APA	Wang, Jinqiao,Fu, Wei,Liu, Jingjing,&Lu, Hanqing.(2014).Spatiotemporal Group Context for Pedestrian Counting.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,24(9),1620-1630.
MLA	Wang, Jinqiao,et al."Spatiotemporal Group Context for Pedestrian Counting".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 24.9(2014):1620-1630.