Plane rectification through robust vanishing point tracking using the Expectation-Maximization algorithm

This paper introduces a new strategy for plane rectification in sequences of images, based on the Expectation-Maximization (EM) algorithm. Our approach is able to compute simultaneously the parameters of the dominant vanishing point in the image plane and the most significant lines passing through it. It is based on a novel definition of the likelihood distribution of the gradient image considering both the position and the orientation of the gradient pixels. Besides, the mixture model in which the EM algorithm operates is extended, compared to other works, to consider an additional component to control the presence of outliers. Some synthetic data tests are described to show the robustness and efficiency of the proposed method. The plane rectification results show that the method is able to remove the perspective and affine distortion of real traffic sequences without the need to compute two vanishing points.

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

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

[3]  Paulo Peixoto,et al.  Estimation of vehicle velocity and traffic intensity using rectified images , 2008, 2008 15th IEEE International Conference on Image Processing.

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

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

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

[7]  Massimo Bertozzi,et al.  GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection , 1998, IEEE Trans. Image Process..

[8]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[9]  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).

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

[11]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .