Prior-based vanishing point estimation through global perspective structure matching
In this paper, we describe a prior-based vanishing point estimation method through global perspective structure matching (GPSM). In contrast to the traditional approaches which require an undistorted image with straight roads for vanishing point estimation, our method first infers vanishing point candidates of an input image from an image database with pre-labeled vanishing points. An image-based retrieval method is used to identify the best candidate images in the database by matching image's perspective structure. The initial estimation of input image's vanishing point is calculated from the pre-labeled vanishing points of the best candidates. Probabilistic refinement (PR) is then used to optimize the vanishing point estimate. Experimental results show that the proposed method works well in a variety of on-road driving environments (e.g., in urban, highway and country-side areas), especially with traffic captured by a fish-eye back-aid camera.