铁路视频序列的FOE的估计

Estimation of FOE for Railway Video Sequences

在结构化场景的轨道交通中,车载视频观测因相机平移运动而呈现出图像内容以某点为中心向四周扩散的现象,该点被称为FOE(Focus of Expansion)。当前计算FOE的算法对噪声敏感且计算量大,不能准确地计算铁路场景中的FOE。鉴于此,文中提出一种铁路视频序列的FOE估计方法。该方法首先利用金字塔光流法对检测的Harris角点进行跟踪和粗匹配,并在此基础上利用RANSAC算法进行精确的匹配,求得基础矩阵,然后提取图像中的极线束并计算FOE。实验结果表明,所提算法比Hough直线求得的FOE误差小,适于实时应用。

In the rail transit of the structured scene,due to the movement of camera,the objects in the image captured by the on-board camera will spread around the center of this image,which is called FOE（Focus of Expansion）.In view of the current technology based on FOE,which is sensitive to noise and has a large amount of computation,it can not accurately calculate the FOE in the railway scene.This paper presented a method for estimating the FOE of railway video sequences.This method uses the Pyramid optical flow method to track and coarsely match the detected Harris corner points,and makes accurately matching with RANSAC algorithm based on the computation of fundamental matrix.Then the epipolar lines are extracted in the image,and the FOE is obtained at last.The experimental results show that the FOE error of this algorithm is smaller than that of the Hough line,and the proposed algorithm is suitable for real-time application.