Example-based clear path detection assisted by vanishing point estimation

With the goal of avoiding obstacles on the road using only a single camera during autonomous driving, we propose an example-based clear path detection method that also considers the additional perspective cue from the estimated vanishing point. First, because of the benefit that the vanishing point provides knowledge for clear path detection, we apply an example-based method to estimate initial vanishing point candidates. Then, instead of building a 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 illustrate the effectiveness of the proposed method.