New method for vanishing point detection
CVGIP: Image Understanding
Statistical analysis of geometric computation
CVGIP: Image Understanding
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Contribution to the Determination of Vanishing Points Using Hough Transform
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Vanishing Point Detection without Any A Priori Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Neural Computation
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Journal of Mathematical Imaging and Vision
Simultaneous vanishing point detection and camera calibration from single images
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
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Signal Processing
Vanishing point detection using cascaded 1D Hough Transform from single images
Pattern Recognition Letters
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Journal of Intelligent and Robotic Systems
Rotation estimation and vanishing point extraction by omnidirectional vision in urban environment
International Journal of Robotics Research
Vanishing point detection by segment clustering on the projective space
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part II
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Computer Vision and Image Understanding
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Vanishing point detection algorithms based on a Gaussian sphere representation have been employed in a variety of computer vision systems, for extracting 3D line orientations as a first step towards object detection. Typically, these algorithms have been applied to imagery with strong perspective effects and with little noise or texture, resulting in good solutions for line orientations. However, these algorithms can fail if perspective effects are weak, or if texture edges are predominant; they also fail to take advantage of knowledge about the objects to be detected. In this paper, two new techniques for robust vanishing point detection on the Gaussian sphere are presented; primitive-based vanishing point analysis and interpretation plane error modeling. The performance of these methods, along with two other existing methods from the literature, are quantitatively evaluated and compared for the task of building detection in complex aerial imagery.