Abnormal event detection in crowded scenes using sparse representation

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	Abnormal event detection in crowded scenes using sparse representation
	Cong Y(丛杨); Yuan JS(袁浚菘); Liu J(刘霁)
刊名	Pattern Recognition
	2013
卷号	46 期号:7 页码:1851-1864
关键词	Convex optimization Security systems
ISSN号	0031-3203
通讯作者	丛杨
产权排序	1
中文摘要	We propose to detect abnormal events via a sparse reconstruction over the normal bases. Given a collection of normal training examples, e.g., an image sequence or a collection of local spatio-temporal patches, we propose the sparse reconstruction cost (SRC) over the normal dictionary to measure the normalness of the testing sample. By introducing the prior weight of each basis during sparse reconstruction, the proposed SRC is more robust compared to other outlier detection criteria. To condense the over-completed normal bases into a compact dictionary, a novel dictionary selection method with group sparsity constraint is designed, which can be solved by standard convex optimization. Observing that the group sparsity also implies a low rank structure, we reformulate the problem using matrix decomposition, which can handle large scale training samples by reducing the memory requirement at each iteration from O( ^k2) to O(k) where k is the number of samples. We use the columnwise coordinate descent to solve the matrix decomposition represented formulation, which empirically leads to a similar solution to the group sparsity formulation. By designing different types of spatio-temporal basis, our method can detect both local and global abnormal events. Meanwhile, as it does not rely on object detection and tracking, it can be applied to crowded video scenes. By updating the dictionary incrementally, our method can be easily extended to online event detection. Experiments on three benchmark datasets and the comparison to the state-of-the-art methods validate the advantages of our method.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
研究领域[WOS]	Computer Science ; Engineering
关键词[WOS]	IMAGES
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000317886600012
公开日期	2013-04-21
内容类型	期刊论文
源URL	[http://ir.sia.cn/handle/173321/10626]
专题	沈阳自动化研究所_机器人学研究室
推荐引用方式 GB/T 7714	Cong Y,Yuan JS,Liu J. Abnormal event detection in crowded scenes using sparse representation[J]. Pattern Recognition,2013,46(7):1851-1864.
APA	Cong Y,Yuan JS,&Liu J.(2013).Abnormal event detection in crowded scenes using sparse representation.Pattern Recognition,46(7),1851-1864.
MLA	Cong Y,et al."Abnormal event detection in crowded scenes using sparse representation".Pattern Recognition 46.7(2013):1851-1864.