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.
The authors would like to thank the anonymous reviewers for their valuable comments. This research was supported in part by the National Science Foundation of China (Grant No. 61473144), the Aeronautical Science Foundation of China (Key Laboratory) (Grant No. 20162852031), the Jiangsu Postdoctoral Founding (Grant No. 1402036C) and the Special scientific instrument development of Ministry of science and technology of China (Grant No. 2016YFF0103702).
Han, J., Yang, Z., Hu, G., Fang, T. and Xu, H. (2019), "Robust and efficient vanishing point detection in unstructured road scenes for assistive navigation", Sensor Review, Vol. 39 No. 1, pp. 137-146. https://doi.org/10.1108/SR-02-2018-0024
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