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Feature tracking in an energy maximization framework

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3 Author(s)
Lappas, P. ; Dept. of Electron. & Comput. Sci., Southampton Univ., UK ; Damper, R.I. ; Carter, J.N.

We describe a robust algorithm for arbitrary object tracking in long image sequences which extends the dynamic Hough transform to detect arbitrary shapes undergoing affine motion. The proposed tracking algorithm processes the whole image sequence globally. First, the object boundary is represented in lookup-table form, and we then perform an operation that estimates the energy of the motion trajectory in the parameter space. We assign an extra term in our cost function to incorporate smoothness of changes due to rotation or scaling of the object. There is no need for training or initialization, and an efficient implementation can be achieved with coarse-to-fine dynamic programming and pruning. The method is shown to be robust under noise and occlusion and capable of tracking multiple objects.

Published in:

Machine Learning and Cybernetics, 2003 International Conference on  (Volume:5 )

Date of Conference:

2-5 Nov. 2003