Traffic accident prediction using 3-D model-based vehicle tracking

	Traffic accident prediction using 3-D model-based vehicle tracking
	Hu, WM; Xiao, XJ ; Xie, D ; Tan, TN; Maybank, S
	2004-05-01
关键词	activity patterns prediction of traffic accidents three-dimensional (3-D) model-based vehicle tracking
英文摘要	Intelligent visual surveillance for road vehicles is the key to developing autonomous intelligent traffic systems. Recently, traffic incident detection employing computer vision and image processing has attracted much attention. In this paper, a probabilistic model for predicting traffic accidents using three-dimensional (3-D) model-based vehicle tracking is proposed. Sample data including motion trajectories are first obtained by 3-D model-based vehicle tracking. A fuzzy self-organizing neural network algorithm is then applied to learn activity patterns from the sample trajectories. Finally, vehicle activity is predicted by locating and matching each partial trajectory with the learned activity patterns, and the occurrence probability of a traffic accident is determined. Experiments show the effectiveness of the proposed algorithms.
收录类别	SCI
语种	英语
WOS记录号	WOS:000221517200012
内容类型	专利
源URL	[http://ir.ia.ac.cn/handle/173211/7989]
专题	自动化研究所_09年以前成果
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China 2.Univ London Birkbeck Coll, Sch Comp Sci & Informat Syst, London WC1E 7HX, England
推荐引用方式 GB/T 7714	Hu, WM,Xiao, XJ,Xie, D,et al. Traffic accident prediction using 3-D model-based vehicle tracking. 2004-05-01.