Simultaneous estimation of vanishing points and their converging lines using the EM algorithm

This paper introduces a new method for the simultaneous computation of sets of lines meeting at multiple vanishing points through the use of the Expectation-Maximisation (EM) algorithm. The proposed method is based on the formulation of novel error functions in the projective plane between lines and points which involve the use of non-linear optimisation procedures that allow to treat equally finite and infinite vanishing points. These functions are included into the EM framework, which handles the multi-modality of the problem naturally with mixture models. Results show that the proposed method of joint computation of vanishing points and lines converging at such points enhances the robustness and the accuracy of locating these points.

[1]  G. F. McLean,et al.  Vanishing Point Detection by Line Clustering , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  V. Cantoni,et al.  Vanishing point detection: representation analysis and new approaches , 2001, Proceedings 11th International Conference on Image Analysis and Processing.

[3]  Ian D. Reid,et al.  Single View Metrology , 2000, International Journal of Computer Vision.

[4]  Thorsten Suttorp,et al.  Robust vanishing point estimation for driver assistance , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[5]  Guanghui Wang,et al.  What can we learn about the scene structure from three orthogonal vanishing points in images , 2009, Pattern Recognit. Lett..

[6]  Roman Pflugfelder,et al.  Self-Calibrating Cameras in Video Surveillance , 2009 .

[7]  Andrew Zisserman,et al.  Planar grouping for automatic detection of vanishing lines and points , 2000, Image Vis. Comput..

[8]  Alan L. Yuille,et al.  Manhattan World: compass direction from a single image by Bayesian inference , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[9]  Long Quan,et al.  Determining perspective structures using hierarchical Hough transform , 1989, Pattern Recognit. Lett..

[10]  Kang-Hyun Jo,et al.  Image-based Structural Analysis of Building using Line Segments and their Geometrical Vanishing Points , 2006, 2006 SICE-ICASE International Joint Conference.

[11]  Edwin R. Hancock,et al.  Perspective pose from spectral voting , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[12]  B. Caprile,et al.  Using vanishing points for camera calibration , 1990, International Journal of Computer Vision.

[13]  Jake K. Aggarwal,et al.  Determining vanishing points from perspective images , 1984, Comput. Vis. Graph. Image Process..

[14]  Seth J. Teller,et al.  Automatic recovery of relative camera rotations for urban scenes , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[15]  Jaime López-Krahe,et al.  Contribution to the Determination of Vanishing Points Using Hough Transform , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Akihiro Minagawa,et al.  Vanishing point and vanishing line estimation with line clustering , 2000 .

[17]  Agnès Desolneux,et al.  Vanishing Point Detection without Any A Priori Information , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Carsten Rother,et al.  A New Approach for Vanishing Point Detection in Architectural Environments , 2000, BMVC.

[19]  F. Dellaert,et al.  Atlanta world: an expectation maximization framework for simultaneous low-level edge grouping and camera calibration in complex man-made environments , 2004, CVPR 2004.

[20]  Christopher Rasmussen,et al.  Grouping dominant orientations for ill-structured road following , 2004, CVPR 2004.

[21]  Luis Salgado,et al.  Non-linear optimization for robust estimation of vanishing points , 2010, 2010 IEEE International Conference on Image Processing.

[22]  Luc Van Gool,et al.  The cascaded Hough transform , 1997, Proceedings of International Conference on Image Processing.

[23]  Stephen T. Barnard,et al.  Interpreting Perspective Image , 1983, Artif. Intell..

[24]  N. H. C. Yung,et al.  Lane detection by orientation and length discrimination , 2000, IEEE Trans. Syst. Man Cybern. Part B.

[25]  James H. Elder,et al.  Efficient Edge-Based Methods for Estimating Manhattan Frames in Urban Imagery , 2008, ECCV.

[26]  Heung-Moon Choi,et al.  An efficient detection of vanishing points using inverted coordinates image space , 2006, Pattern Recognit. Lett..

[27]  Andrew Zisserman,et al.  Metric rectification for perspective images of planes , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[28]  Narciso García,et al.  Line segment detection using weighted mean shift procedures on a 2D slice sampling strategy , 2011, Pattern Analysis and Applications.

[29]  Wei Zhang,et al.  Video Compass , 2002, ECCV.