Abstract
Visual object tracking is required by many vision applications such as human-computer interfaces, human-robot interactions and so on. However, in general living spaces where some of such applications are assumed to be used, stable tracking is generally difficult because there are many objects which are possible to cause the visual occlusion. Especially, conventional tracking techniques cannot deal with a complete occlusion over a long time instead of a short-time or partial occlusion. They also cannot handle the case that an occluder such as a box and a bag contains the tracking target and they move as one body. In this paper, to handle these problems, we propose a novel method for visual object tracking using a particle filter, which switches tracking targets autonomously. In our method, when an occlusion occurs in tracking, the model of the occluder is dynamically created and tracking target is switched to this model. Since the original target model is also stored simultaneously, it can return to the tracking target when the original target appears again from behind the occluder. We show the effectiveness of our method through some experiments.
