An object tracking method using particle filter and scale space model

In this paper, we propose and object tracking algorithm to track an object on IR image sequences, which has appearance changes. In our framework based on particle filter, histograms of intensity and orientation on scale space are used as observation models. Histogram of intensity is robust to shape variation but lack of distinction between target and similar background due to loss of spatial information. Histogram of gradient orientation complements the spatial information. Because the histogram models are extracted from scale space, target model maintains consistency with initial model in different scales. We also propose an efficient method of model update and demonstrate the proposed method for several sequences in which a target changes largely in size and appearance.