Modulation-domain particle filter for template tracking

Particle filters provide a robust framework for nonlinear and non-Gaussian estimation problems. In this paper, we present a method to incorporate dominant modulation-domain (amplitude modulation-frequency modulation) features into particle filter based template tracking. The dominant AM-FM features capture the local texture structure of an image. Tracking is performed based on correlations of these AM-FM features. We propose an adaptive method that weights these correlations based on the significance of the features for tracking. The performance of the tracker is demonstrated on a few standard test sequences.