A Robust Vanishing Point Estimation Method for Lane Detection
Vanishing points are often used as constraints in lane detection or road following systems of intelligent vehicles.This paper proposes a new method for vanishing point estimation in consecutive frames based on computer vision.Parallel lines in the real world converge to vanishing points on an image plane,caused by the perspective projection.According to the duality between points and lines,estimation of vanishing points can be converted to a problem of line parameter estimation in a parameter space.Firstly,straight lines are detected from an extracted edge map of a road image by the Progressive Probability Hough Transform(PPHT)incorporated with gradient orientation constraints.Then,vanishing points are estimated via the Maximum A Posteriori(MAP)estimate,integrating information at the current frame and the vanishing point estimated at the previous frame into a probabilistic framework.For the detected lines are noisy,a weight is put on each line to indicate the probability of being an inlier.But the weights are unknown,which are regarded as hidden variables here.Thus the Expectation Maximum(EM)algorithm is adopted to solve the MAP problem with hidden variables.Experimental results show the efficiency and robustness of the proposed method.
Vanishing point estimation lane detection MAP estimate EM algorithm
Yuan Jun Tang Shuming Pan Xiuqin Zhang Hong
Institute of Automation,Chinese Academy of Sciences,Beijing 100190 School of Information Engineering,Minzu University of China,Beijing 100081
国际会议
The 33th Chinese Control Conference第33届中国控制会议
南京
英文
4887-4892
2014-07-28（万方平台首次上网日期，不代表论文的发表时间）