View Independent Object Classification Based on Automated Ground Plane Rectification for Traffic Scene Surveillance

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	View Independent Object Classification Based on Automated Ground Plane Rectification for Traffic Scene Surveillance
	Zhaoxiang Zhang; Min Li; Kaiqi Huang; Tieniu Tan
	2008-10-17
会议名称	The Eighth International Workshop on Visual Surveillance
会议录名称	IEEE Conference on Computer Vision & Pattern Recognition 2008
页码	1-9
会议日期	17th October 2008
会议地点	France
摘要	We address the problem of view independent object classification. Our aim is to classify moving objects of traf- fic scene surveillance videos into pedestrians, bicycles and vehicles. However, this problem is very challenging due to large object appearance variance, low resolution videos and limited object size. Especially, perspective distortion of surveillance cameras makes most 2D object features like size and speed related to view angles and not suitable for object classification. In this paper, we adopt the common constraint that most objects of interest in traffic scenes are moving on the ground plane. Firstly, we realize the ground plane rectification based on appearance and motion information of moving objects, which can be applied for normalization of 2D object features. An online learning framework is then described to achieve automatic object classification based on rectified 2D object features. Experimental results demonstrate the effectiveness, efficiency and robustness of the proposed method.
关键词	Traffic Scene Surveillance Object Feature Automated Ground Plane Rectification View Independent Object Classification Online Learning Framework
语种	英语
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/12709
专题	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. View Independent Object Classification Based on Automated Ground Plane Rectification for Traffic Scene Surveillance[C],2008:1-9.