Vanishing point detection using cascaded 1D Hough Transform from single images
Pattern Recognition Letters
Rotation estimation and vanishing point extraction by omnidirectional vision in urban environment
International Journal of Robotics Research
Geometric Image Parsing in Man-Made Environments
International Journal of Computer Vision
Vanishing points estimation and line classification in a manhattan world
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
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In this paper, we describe the components of a robust algorithm for the detection of vanishing points in man-made environments. We designed our approach to work under quite general conditions (e.g., uncalibrated camera); and in contrast to several other approaches, the assumption of a dominant line-alignment w.r.t. the orthogonal axes of the world coordinate frame (Manhattan world) is not explicitly exploited. Our only premise is, that if a significant number of the imaged line segments meet very accurately in a point, this point is very likely to be a good candidate for a real vanishing point. For finding such points under a wide range of conditions, we propose a flexible algorithmic pipeline that combines accurate line detection techniques with robust statistical candidate initialization and refinement stages. The method was evaluated on a set of images exhibiting largely varying characteristics concerning image quality and scene complexity. Experiments show that the method, despite the variations, works in a stable manner and that its performance compares favorably with the state of the art.