Recovery method based particle filter for object tracking in complex environment

Object tracking is a key process for various image recognition applications, and many algorithms have been proposed in this field. Especially, particle filter has possibility for tracking objects steadily thanks to prediction using many particles. However, other objects that are a similar color or shape with a tracking object hijack a tracking region if there were such objects nearby the tracking object. It is a critical problem. This paper proposes a recovery method based particle filter by focusing a feature regions attached to an object. This proposal tracks both a feature region and an object including the region at once. This proposal utilizes a recovery method that pulls a tracking region back to an appropriate position using the prior frame's distance and angle between the two tracking regions when the tracking region is hijacked by other objects. Some video sequences including complex environment have been tested for evaluating this proposal. The experimental results show that this proposal can track a specified person in the sequences, while conventional method cannot track the person. This result represents that recovery method of proposal effectively works when other objects hijack the tracking region.