Motion-Based Hierarchical Active Contour Model for Deformable Object Tracking

This paper proposed a novel scheme for combined contour extraction and deformable object tracking. In order to track fast moving objects, we first add the motion estimation term to the energy function of the conventional snake. Then, a hierarchical approach using wavelet analysis is applied. Although the proposed wavelet-based method can track objects with large motion, the proposed method requires less computational load than the conventional one. By using a training procedure, the proposed method overcomes occlusion problems and local minima due to strong edges in the background. The proposed algorithm has been tested for various images including a sequence of human motion to demonstrate the improved performance of object tracking.

[1]  Joonki Paik,et al.  Color active shape models for tracking non-rigid objects , 2003, Pattern Recognit. Lett..

[2]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[3]  Timothy F. Cootes,et al.  Training Models of Shape from Sets of Examples , 1992, BMVC.

[4]  Jerry L. Prince,et al.  Snakes, shapes, and gradient vector flow , 1998, IEEE Trans. Image Process..

[5]  Frederic Fol Leymarie,et al.  Tracking Deformable Objects in the Plane Using an Active Contour Model , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Mubarak Shah,et al.  A Fast algorithm for active contours and curvature estimation , 1992, CVGIP Image Underst..