Spatiotemporal Group Context for Pedestrian Counting

	Spatiotemporal Group Context for Pedestrian Counting
	Wang, Jinqiao1 ; Fu, Wei 1; Liu, Jingjing 2; Lu, Hanqing1
发表期刊	IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
	2014-09-01
卷号	24 期号:9 页码:1620-1630
文章类型	Article
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.
关键词	Group Context Group Correspondence Matrix Markov-chain Monte Carlo (Mcmc) Pedestrian Counting
WOS标题词	Science & Technology ; Technology
关键词[WOS]	PART DETECTORS ; CROWDED SCENES ; SEGMENTATION ; MULTIPLE ; TRACKING ; IMAGE
收录类别	SCI
语种	英语
WOS研究方向	Engineering
WOS类目	Engineering, Electrical & Electronic
WOS记录号	WOS:000341981900013
引用统计	被引频次：18[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/3340
专题	紫东太初大模型研究中心_图像与视频分析
通讯作者	Wang, Jinqiao
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
第一作者单位	模式识别国家重点实验室
通讯作者单位	模式识别国家重点实验室
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.

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Spatiotemporal Group（3404KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览