CASIA OpenIR  > 智能感知与计算研究中心
Robust Automated Ground Plane Rectification Based on Moving Vehicles for Traffic Scene Surveillance
Zhaoxiang Zhang; Min Li; Kaiqi Huang; Tieniu Tan
2008-10-12
Conference Name15th IEEE International Conference on Image Processing
Source PublicationIEEE International Conference on Image Processing 2008
Pages1364-1367
Conference Date12-15 October 2008
Conference PlaceSan Diego, California, USA
AbstractMost outdoor visual surveillance scenes involve objects of interest moving on the ground plane. However, perspective distortion introduces many difficulties to various applications like object classification and activity recognition. In this paper, we propose a robust automated method for both affine and metric rectification of the ground plane based on appearance and motion of vehicles in traffic scene surveillance videos. This rectification enables normalization of object properties like size, length and velocity. Various useful applications are presented and experimental results demonstrate the effectiveness and robustness of the proposed method.
KeywordRobustness Land Vehicles Road Vehicles Layout Surveillance Videos Cameras Vehicle Detection Humans Calibration
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12712
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. Robust Automated Ground Plane Rectification Based on Moving Vehicles for Traffic Scene Surveillance[C],2008:1364-1367.
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