EDA Approach for Model Based Localization and Recognition of Vehicle

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	EDA Approach for Model Based Localization and Recognition of Vehicle
	Zhaoxiang Zhang; Weishan Dong; Kaiqi Huang; Tieniu Tan
	2007
会议日期	2007-06-01
会议地点	Minneapolis, Minnesota, USA
关键词	Evolutionary Computation image Classification image Recognition
页码	1-8
英文摘要	We address the problem of model based recognition. Our aim is to localize and recognize road vehicles from monocular images in calibrated scenes. A deformable 3D geometric vehicle model with 12 parameters is set up as prior information and Bayesian Classification Error is adopted for evaluation of fitness between the model and images. Using a novel evolutionary computing method called EDA (Estimation of Distribution Algorithm), we can not only determine the 3D pose of the vehicle, but also obtain a 12 dimensional vector which corresponds to the 12 shape parameters of the model. By clustering obtained vectors in the parameter space, we can recognize different types of vehicles. Experimental results demonstrate the effectiveness of the approach to vehicles of different types and poses. Thanks to EDA, we can not only localize and recognize vehicles, but also show the whole evolution procedure of the deformable model which gradually fits the image better and better.
会议录	CVPR workshop on the Seventh International Workshop on Visual Surveillance
语种	英语
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/12726]
专题	自动化研究所_智能感知与计算研究中心
通讯作者	Kaiqi Huang
作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Zhaoxiang Zhang,Weishan Dong,Kaiqi Huang,et al. EDA Approach for Model Based Localization and Recognition of Vehicle[C]. 见:. Minneapolis, Minnesota, USA. 2007-06-01.