This paper aims to propose a robust and efficient method for vanishing point detection in unstructured road scenes.
The proposed method includes two main stages: drivable region estimation and vanishing point detection. In drivable region estimation stage, the road image is segmented into a set of patches; then the drivable region is estimated by the patch-wise manifold ranking. In vanishing point detection stage, the LSD method is used to extract the straight lines; then a series of principles are proposed to remove the noise lines. Finally, the vanishing point is detected by a novel voting strategy.
The proposed method is validated on various unstructured road images collected from the real world. It is more robust and more efficient than the state-of-the-art method and the other three recent methods. Experimental results demonstrate that the detected vanishing point is practical for vision-sensor-based navigation in complex unstructured road scenes.
This paper proposes a patch-wise manifold ranking method to estimate the drivable region that contains most of the informative clues for vanishing point detection. Based on the removal of the noise lines through a series of principles, a novel voting strategy is proposed to detect the vanishing point.