高速公路动态环境下的摄像机自标定

Automatic Self-Calibration of Expressway Surveillance Camera Under Dynamic Conditions

提出一种动态环境下高速公路监控系统摄像机的自标定方法.首先利用混合高斯背景建模方法从动态视频图像中获取背景图像和目标频繁出现的目标区域;然后利用不同的直线检测算法检测和估计出目标区域内高速公路上大量存在的各种标志线和虚标志线以及水平线,基于这些线状特征计算出摄像机的灭点;最后根据灭点和线特征之间的几何关系计算出摄像机的内外参数,从而实现摄像机自标定.真实场景的实验结果表明,该算法非常合适于各种高速公路监控系统中摄像机的实时自标定,且精度高、稳定性好.

In this paper, a novel method is proposed to automatically calibrate the cameras in expressway surveillance system under dynamic conditions. First, a GMM-based background modeling method is employed to obtain the background image and the region of interest （ROD in which moving objects appear frequently. Then, the real lines （including straight long lines and marker lines）, virtual lines （i. e. linking lines） and horizontal line are respectively detected and evaluated in the ROI by using different methods, and three vanishing points are thus obtained based on these line features. Finally, camera parameters are calculated according to the geometric relationships between the vanishing points and marker lines. Experimental results demonstrate that the proposed method is rather effective for real-time camera self-calibration in various expressway scenes with high precision and stability.