Vanishing point detection using cascaded 1D Hough Transform from single images

Authors:
Bo Li;Kun Peng;Xianghua Ying;Hongbin Zha
Affiliations:
The Key Lab of Machine Perception (Ministry of Education), School of Electrical Engineering and Computer Science, Peking University, Beijing 100871, PR China;The Key Lab of Machine Perception (Ministry of Education), School of Electrical Engineering and Computer Science, Peking University, Beijing 100871, PR China;The Key Lab of Machine Perception (Ministry of Education), School of Electrical Engineering and Computer Science, Peking University, Beijing 100871, PR China;The Key Lab of Machine Perception (Ministry of Education), School of Electrical Engineering and Computer Science, Peking University, Beijing 100871, PR China
Venue:
Pattern Recognition Letters
Year:
2012

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Abstract

Vanishing point detection algorithms based on 2D histogramming techniques have been employed in a variety of computer vision systems. Previous algorithms achieved some good results but still failed to maintain a balanced performance in both accuracy and time. Recent research (Li et al., 2010) shows that, vanishing point detection could be converted to a 1D histogram search problem, which largely accelerates the procedure. In this paper, we further improve this idea and propose a complete scheme for vanishing point detection from images of the so called ''Manhattan world''. We test our algorithm and some commonly used vanishing point detection methods on public database YorkUrbanDB and our own implemented database PKUCampusDB. Our algorithm shows significant performance improvements.