|Practical Camera Auto-Calibration based on Object Appearance and Motion for Traffic Scene Visual Surveillance|
|Zhaoxiang Zhang; Min Li; Kaiqi Huang; Tieniu Tan
|Conference Name||IEEE Computer Society Conference on Computer Vision and Pattern Recognition
|Source Publication||IEEE Conference on Computer Vision & Pattern Recognition 2008
|Conference Date||24-26 June 2008
|Conference Place||Anchorage, Alaska, USA
|Abstract||Camera 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.|
|Corresponding Author||Zhaoxiang Zhang|
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.
|Files in This Item:||
||There are no files associated with this item.
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.