CASIA OpenIR  > 智能感知与计算研究中心
Practical Camera Auto-Calibration based on Object Appearance and Motion for Traffic Scene Visual Surveillance
Zhaoxiang Zhang; Min Li; Kaiqi Huang; Tieniu Tan
2008-06-24
Conference NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition
Source PublicationIEEE Conference on Computer Vision & Pattern Recognition 2008
Pages1-8
Conference Date24-26 June 2008
Conference PlaceAnchorage, Alaska, USA
AbstractCamera calibration, as a fundamental issue in computer vision, is indispensable in many visual surveillance applications. Firstly, calibrated camera can help to deal with perspective distortion of object appearance on image plane. Secondly, calibrated camera makes it possible to recover metrics from images which are robust to scene or view an gle changes. In addition, with calibrated cameras, we can make use of prior information of 3D models to estimate 3D pose of objects and make object detection or tracking more robust to noise and occlusions. In this paper, we propose an automatic method to recover camera models from traffic scene surveillance videos. With only the camera height H measured, we can completely recover both intrinsic and extrinsic parameters of cameras based on appearance and motion of objects in videos. Experiments are conducted in different scenes and experimental results demonstrate the effectiveness and practicability of our approach, which can be adopted in many traffic scene surveillance applications.
KeywordCameras Layout Surveillance Noise Robustness Videos Calibration Computer Vision Application Software Object Detection Traffic Control
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12711
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. Practical Camera Auto-Calibration based on Object Appearance and Motion for Traffic Scene Visual Surveillance[C],2008:1-8.
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