Vanishing Point Detection in Urban Scenes Using Point Alignments
José Lezama, Gregory Randall, Rafael Grompone von Gioi
José Lezama, Gregory Randall, and Rafael Grompone von Gioi, Vanishing Point Detection in Urban Scenes Using Point Alignments, Image Processing On Line, 7 (2017), pp. 131–164.

Communicated by Andrés Almansa
Demo edited by José Lezama


We present a method for the automatic detection of vanishing points in urban scenes based on finding point alignments in a dual space, where converging lines in the image are mapped to aligned points. To compute this mapping the recently introduced PClines transformation is used. A robust point alignment detector is run to detect clusters of aligned points in the dual space. Finally, a post-processing step discriminates relevant from spurious vanishing point detections with two options: using a simple hypothesis of three orthogonal vanishing points (Manhattan-world) or the hypothesis that one vertical and multiple horizontal vanishing points exist. Qualitative and quantitative experimental results are shown. On two public standard datasets, the method achieves state-of-the-art performances. Finally, an optional procedure for accelerating the method is presented.