3D Model Based Vehicle Localization by Optimizing Local Gradient Based Fitness Evaluation

	3D Model Based Vehicle Localization by Optimizing Local Gradient Based Fitness Evaluation
	Zhaoxiang Zhang; Min Li; Kaiqi Huang; Tieniu Tan
	2009-12-08
会议日期	8-11 December 2009
会议地点	Tampa, Florida, USA
关键词	Vehicles Optimization Methods Data Mining Noise Robustness Pixel Laboratories Pattern Recognition Automation Traffic Control Layout
页码	1-4
英文摘要	We address the problem of 3D model based vehicle localization in calibrated traffic scenes. A wire-frame vehicle model is set up as prior information and an efficient local gradient based method is proposed to evaluate the fitness between the projection of 3D model and image data, which illustrates smooth optimization surface and more conspicuous peak with low computational cost. Gradient decent is then applied to optimize the evaluation score for localization. Experimental results demonstrate the accuracy, efficiency and robustness of the proposed method for model based vehicle localization.
会议录	Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
语种	英语
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/12713]
专题	自动化研究所_智能感知与计算研究中心
通讯作者	Zhaoxiang Zhang
推荐引用方式 GB/T 7714	Zhaoxiang Zhang,Min Li,Kaiqi Huang,et al. 3D Model Based Vehicle Localization by Optimizing Local Gradient Based Fitness Evaluation[C]. 见:. Tampa, Florida, USA. 8-11 December 2009.