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	Research on branch and bound for pedestrian detection
	Ye, Zhi-Qin ; Su, Song-Zhi ; Li, Shao-Zi ; Su SZ(苏松志) ; Li SZ(李绍滋)
	2011
关键词	Computer science Computer vision Linear programming Object recognition
英文摘要	Conference Name:2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011. Conference Address: Shanghai, China. Time:June 10, 2011 - June 12, 2011.; IEEE Beijing Section; Pudong New Area Association for Computer; Pudong New Area Science and Technology Development Fund; Tongji University; Xiamen University; Object detection and localization is an important research subject in computer vision. In pedestrian detection, the task of classification is to decide whether an object is present or not in current scanning window, while location focusing on more difficult problem. Sliding window approach is still the main approach now, but its computational cost strongly increases with the image size. In order to perform location as soon as possible, this paper introduce a method for pedestrian detection that relied on branch and bound search proposed by Lampert et al. Compare to sliding window, it can find a globally optimal classifier functions over all candidate subwindows in linear time. For feature vectors, we used HIK(histogram intersection kernel) to calculate the the similarity, and voting according to their values. Compare to others, the approach used few trainging samples, experimental showing the result. ? 2011 IEEE.
语种	英语
出处	http://dx.doi.org/10.1109/CSAE.2011.5952489
出版者	IEEE Computer Society
内容类型	其他
源URL	[http://dspace.xmu.edu.cn/handle/2288/86957]
专题	信息技术－会议论文
推荐引用方式 GB/T 7714	Ye, Zhi-Qin,Su, Song-Zhi,Li, Shao-Zi,et al. Research on branch and bound for pedestrian detection. 2011-01-01.

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