Model Based Vehicle Localization for Urban Traffic Surveillance Using Image Gradient Based Matching

CASIA OpenIR > 智能制造技术与系统研究中心 > 多维数据分析（彭思龙）-技术团队

	Model Based Vehicle Localization for Urban Traffic Surveillance Using Image Gradient Based Matching
	Zheng, Yuan; Peng, Silong; Yuan Zheng
	2012
会议名称	2012 15TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC)
会议录名称	IEEE International Conference on Intelligent Transportation Systems (ITSC)
页码	945-950
会议日期	2012
摘要	The matching between 3D model projection and 2D image data is a key technique for model based localization, recognition and tracking problems. Firstly, we propose a fitness function to evaluate the matching degree that uses image gradient information in the neighborhood of model projection. The weighting adjustment and the normalization for visible model projection are involved, which improves the correctness and robustness of fitness function. The fitness function is used for vehicle localization and the 3D pose is reduced to location and orientation. Then, we present a direct search optimization method with 3 3 search kernel for location estimation. The “disturbed particles” is used to avoid falling into local optimum and the coarse-to-fine optimization strategy is adopted to greatly reduce computational cost. Finally, we propose a 3D pose estimator to find location and orientation by optimizing the fitness function within orientation range. Experiments on real traffic surveillance videos reveal that the proposed optimization algorithm is effective and both fitness function and 3D pose estimator are correct and robust against clutter and occlusion.
收录类别	CPCI-T
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/5181
专题	智能制造技术与系统研究中心_多维数据分析（彭思龙）-技术团队
通讯作者	Yuan Zheng
推荐引用方式 GB/T 7714	Zheng, Yuan,Peng, Silong,Yuan Zheng. Model Based Vehicle Localization for Urban Traffic Surveillance Using Image Gradient Based Matching[C],2012:945-950.