Video Segmentation for Traffic Monitoring Tasks Based on Pixel-Level Snakes

In this paper we address a moving object segmentation technique for a video monitoring system. This is approached by means of active contours which appear to be an efficient tool for the spatio-temporal data analysis from 2D image sequences. Particularly we make use of a new active contour concept: the pixel-level snakes whose characteristics allow a high control on the contour evolution and approach topological transformations with a low computational cost. The proposal is focused in the traffic monitoring and the incident detection systems.

[1]  Levent Onural,et al.  Image sequence analysis for emerging interactive multimedia services-the European COST 211 framework , 1998, IEEE Trans. Circuits Syst. Video Technol..

[2]  King Ngi Ngan,et al.  Automatic segmentation of moving objects for video object plane generation , 1998, IEEE Trans. Circuits Syst. Video Technol..

[3]  Jong Bae Kim,et al.  Efficient region-based motion segmentation for a video monitoring system , 2003, Pattern Recognit. Lett..

[4]  Guillermo Sapiro,et al.  Geodesic Active Contours , 1995, International Journal of Computer Vision.

[5]  Baba C. Vemuri,et al.  Shape Modeling with Front Propagation: A Level Set Approach , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Ángel Rodríguez-Vázquez,et al.  ACE16k: A 128x128 Focal Plane Analog Processor with Digital I/O , 2003, Int. J. Neural Syst..

[7]  Guojun Lu,et al.  Segmentation of moving objects in image sequence: A review , 2001 .

[8]  Xose Manuel Pardo,et al.  Cellular neural networks and active contours: a tool for image segmentation , 2003, Image Vis. Comput..

[9]  Tamás Szirányi,et al.  Motion Segmentation and Tracking with Edge Relaxation and Optimization using Fully Parallel Methods in the Cellular Nonlinear Network Architecture , 2001, Real Time Imaging.

[10]  Lin-Bao Yang,et al.  Cellular neural networks: theory , 1988 .

[11]  Victor M. Brea,et al.  A DTCNN CMOS Implementation of a Pixel-Level Snake Algorithm , 2001 .

[12]  Touradj Ebrahimi,et al.  Video segmentation based on multiple features for interactive multimedia applications , 1998, IEEE Trans. Circuits Syst. Video Technol..

[13]  David López Vilariño,et al.  An Active Contour Algorithm for Continuous-Time Cellular Neural Networks , 1999, J. VLSI Signal Process..

[14]  Xose Manuel Pardo,et al.  Pixel-level snakes , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.