D.: An improved particle filter approach for real-time pedestrian tracking in surveillance video

Abstract—This paper presents a method for pedestrian tracking in surveillance video, and the method is based on an improved particle filter. In our algorithm, the dynamics is modeled as a second-order autoregressive process. And for the observation model, color histogram features are used for likelihood measure. The proposed color histogram method is operated on a sub-region of the target region and we explore how the background subtraction process affects the color histogram model. We further adopt rectangle filters and pixel-difference cues in the observation model to overcome the limitation of individual cue. Experiments show that the method yields better tracking performance with the improved observation model. Keywords-Pedestrian tracking, particle filter, surveillance video I