Fast Lighting Independent Background Subtraction

This paper describes a simple method of fast background subtraction based upon disparity verification that is invariant to arbitrarily rapid run-time changes in illumination. Using two or more cameras, the method requires the off-line construction of disparity fields mapping the primary background images. At runtime, segmentation is performed by checking background image to each of the additional auxiliary color intensity values at corresponding pixels. If more than two cameras are available, more robust segmentation can be achieved and, in particular, the occlusion shadows can be generally eliminated as well. Because the method only assumes fixed background geometry, the technique allows for illumination variation at runtime. Since no disparity search is performed, the algorithm is easily implemented in real-time on conventional hardware.

[1]  Y. Ivanov,et al.  Fast Lighting Independent Background Subtraction , 1998, Proceedings 1998 IEEE Workshop on Visual Surveillance.

[2]  Alex Pentland,et al.  A Bayesian Computer Vision System for Modeling Human Interaction , 1999, ICVS.

[3]  Trevor Darrell,et al.  A novel environment for situated vision and behavior , 1994 .

[4]  Alex Pentland,et al.  Pfinder: real-time tracking of the human body , 1996, Other Conferences.

[5]  Jos,et al.  Ground Plane Obstacle Detection with a Stereo Vision System , 1994 .

[6]  W. Eric L. Grimson,et al.  Adaptive background mixture models for real-time tracking , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[7]  Takeo Kanade,et al.  A Multiple-Baseline Stereo , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  James W. Davis,et al.  The Representation and Recognition of Action Using Temporal Templates , 1997, CVPR 1997.

[9]  Thomas O. Binford,et al.  Ignorance, myopia, and naiveté in computer vision systems , 1991, CVGIP Image Underst..

[10]  Alex Pentland,et al.  Pfinder: real-time tracking of the human body , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.

[11]  Takeo Kanade,et al.  A stereo machine for video-rate dense depth mapping and its new applications , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[12]  A F Bobick,et al.  Movement, activity and action: the role of knowledge in the perception of motion. , 1997, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[13]  James W. Davis,et al.  Real-time closed-world tracking , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[14]  Stuart J. Russell,et al.  Image Segmentation in Video Sequences: A Probabilistic Approach , 1997, UAI.

[15]  Alex Pentland,et al.  A Bayesian Computer Vision System for Modeling Human Interactions , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Claudio S. Pinhanez,et al.  “It/I”: a theater play featuring an autonomous computer graphics character , 1998, MULTIMEDIA '98.