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	Pursuing detector efficiency for simple scene pedestrian detection
	Yuan, De-Do ; Dong, J ; Su, Song-Zhi ; Li, Shao-Zi ; Ji, Rong-Rong ; Su SZ(苏松志) ; Li SZ(李绍滋) ; Ji RR(纪荣嵘)
	2014
关键词	Feature extraction Image retrieval
英文摘要	Conference Name:20th Anniversary International Conference on MultiMedia Modeling, MMM 2014. Conference Address: Dublin, Ireland. Time:January 6, 2014 - January 10, 2014.; Dublin City University; Science Foundation Ireland; Failte Ireland; Google; ISCA; Detector accuracy is by any means the key focus in most existing pedestrian detection algorithms especially for clutter scenes. However, it is not always necessary, while sometimes over-fitted, to directly leverage such detectors in scenarios with simple scene compositions. To this end, limited work has done on a systematic detector simplification towards balancing its speed and accuracy. In this paper, we study this problem by investigating two mutually correlated issues, i.e. fast edge-based feature extraction and detector score computation. For handling the first issue, a simple Structured Local Edge Pattern (SLEP) is proposed to extract and encode local edge cues, extremely effectively, into a histogram. For the second, an integral image based acceleration is proposed toward fast classifier score computation by transforming the classifier score into a linear sum of weights. Experimental results on CASIA gait recognition dataset show that our proposed method is highly efficient than most existing detectors, which even faster than the practical OpenCV pedestrian detector. ? 2014 Springer International Publishing.
语种	英语
出处	http://dx.doi.org/10.1007/978-3-319-04117-9_13
出版者	Springer Verlag
内容类型	其他
源URL	[http://dspace.xmu.edu.cn/handle/2288/86956]
专题	信息技术－会议论文
推荐引用方式 GB/T 7714	Yuan, De-Do,Dong, J,Su, Song-Zhi,et al. Pursuing detector efficiency for simple scene pedestrian detection. 2014-01-01.

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