CASIA OpenIR  > 智能感知与计算研究中心
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
Conference NameThe Eighth International Workshop on Visual Surveillance
Source PublicationIEEE Conference on Computer Vision & Pattern Recognition 2008
Pages1-9
Conference Date17th October 2008
Conference PlaceFrance
AbstractWe 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.
KeywordTraffic Scene Surveillance Object Feature Automated Ground Plane Rectification View Independent Object Classification Online Learning Framework
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12709
Collection智能感知与计算研究中心
Corresponding AuthorZhaoxiang Zhang
Recommended Citation
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.
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