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	Front-view vehicle detection by Markov chain Monte Carlo method
	Jia, Yangqing ; Zhang, Changshui
	2010-05-06 ; 2010-05-06
关键词	Vehicle detection Bayesian method Maximizing a posteriori Markov chain Monte Carlo Computer Science, Artificial Intelligence Engineering, Electrical & Electronic
中文摘要	In this paper, we propose a new vehicle detection approach based on Markov chain Monte Carlo (MCMC). We mainly discuss the detection of vehicles in front-view static images with frequent occlusions. Models of roads and vehicles based on edge information are presented, the Bayesian problem's formulations are constructed, and a Markov chain is designed to sample proposals to detect vehicles. Using the Monte Carlo technique, we detect vehicles sequentially based on the idea of maximizing a posterior probability (MAP), performing vehicle segmentation in the meantime. Our method does not require complex preprocessing steps such as background extraction or shadow elimination, which are required in many existing methods. Experimental results show that the method has a high detection rate on vehicles and can perform successful segmentation, and reduce the influence caused by vehicle occlusion. (C) 2008 Elsevier Ltd. All rights reserved.
语种	英语 ; 英语
出版者	PERGAMON-ELSEVIER SCIENCE LTD ; OXFORD ; THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/9327]
专题	清华大学
推荐引用方式 GB/T 7714	Jia, Yangqing,Zhang, Changshui. Front-view vehicle detection by Markov chain Monte Carlo method[J],2010, 2010.
APA	Jia, Yangqing,&Zhang, Changshui.(2010).Front-view vehicle detection by Markov chain Monte Carlo method..
MLA	Jia, Yangqing,et al."Front-view vehicle detection by Markov chain Monte Carlo method".(2010).

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