A Fast Method for Vanishing Point Estimation and Tracking and Its Application in Road Images

A fast method for vanishing point (VP) estimation and tracking in road images and its application for lane detection are investigated in this paper. After determine the region of interest of the road images, we use 'Sobel' operator to detect boundaries. Then the boundary image is transformed to the Hough space by Hough transform. We proposed a Gaussian predication model on the basis of the latest vanishing point to predicate the current VP, and we constructed an objective function including the linear segment intensity and the predicated VP, subsequently the optimal position of the VP is estimated through the least square method. The computational complexity of the estimation algorithm is O(n), which can operate in real time. We test our algorithm on many structured road and semi-structured road images, the results show that it can robustly determine the VP position regardless the disturbance of around pedestrian, crowd and vehicles. Moreover, experiments on PETS2001 dataset show its application to the road lane detection for the driver assistant system