A graph cut based active contour without edges with relaxed homogeneity constraint

The paper presents a graph cut based active contour without edges segmentation model to track pedestrian in thermal images. The deformable model is based on the Mumford- Shah piecewise constant energy formulation. However, the model presented here relaxes the global homogeneity assumption of the Mumford- Shah functional. A discrete energy formulation is presented and the optimization is performed using graph cuts. The major advantages of our approach are; 1) The optimization using graph cuts makes the segmentation process much faster than solving it using level sets. 2) Relaxing the global homogeneity assumption makes the model more practical.

[1]  Vladimir Kolmogorov,et al.  An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision , 2004, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  D. Mumford,et al.  Optimal approximations by piecewise smooth functions and associated variational problems , 1989 .

[3]  Vladimir Kolmogorov,et al.  An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision , 2001, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Vladimir Kolmogorov,et al.  Computing geodesics and minimal surfaces via graph cuts , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[5]  Tony F. Chan,et al.  A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model , 2002, International Journal of Computer Vision.

[6]  James W. Davis,et al.  A Two-Stage Template Approach to Person Detection in Thermal Imagery , 2005, 2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05) - Volume 1.

[7]  Tony F. Chan,et al.  Active contours without edges , 2001, IEEE Trans. Image Process..

[8]  Jérôme Darbon,et al.  A Note on the Discrete Binary Mumford-Shah Model , 2007, MIRAGE.

[9]  Adel Said Elmaghraby,et al.  Graph cut optimization for the Mumford-Shah model , 2007 .

[10]  Vladimir Kolmogorov,et al.  What energy functions can be minimized via graph cuts? , 2002, IEEE Transactions on Pattern Analysis and Machine Intelligence.