ICRA 2011 Paper Abstract


Paper TuP114.1

Wu, Qi (Carnegie Mellon Universtiy), Zhang, Wende (General Motors), Vijaya Kumar, B.V.K (Carnegie Mellon University)

Example-Based Clear Path Detection Assisted by Vanishing Point Estimation

Scheduled for presentation during the Regular Sessions "Visual Navigation III" (TuP114), Tuesday, May 10, 2011, 13:40−13:55, Room 5J

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on March 30, 2020

Keywords Computer Vision for Robotics and Automation, Intelligent Transportation Systems, Visual Learning


To avoid obstacles on the road using only a single camera during autonomous driving, we propose an example-based clear path detection method to find clear path which also considers the additional perspective cue from the estimated vanishing point. First, because of the benefit of knowing the vanishing point in clear path detection, we apply an example-based method to estimate initial vanishing point candidates. Then, instead of building the pre-trained clear path model over the limited training set, we propose an example-based global image matching method to get an approximate idea of clear path candidate regions, and use a Gaussian Mixture Model (GMM) for local image patch modeling to further improve the clear path detection. Finally, we develop an iterative probabilistic refinement to improve performance of both components. Experimental results of real road scenes are presented to substantiate the effectiveness of the proposed method.



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