Robust object tracking using a context based on the relation of object and background

Object tracking is complicated by perspective changes to both the object and background caused by object and the camera motion, object-to-object and object-to-background occlusion and illumination changes. Conventional object tracking method focus on distinguishing the target from the background. Adopting a new perspective, we propose a context aware tracking by a collaborative model of both the object and its surrounding background. In this model we introduce the “probability of tracking failure” that determines the feature similarity and the spatial relationship of the target and the surrounding background, as the “target-surrounding context”, which appears effective to predict the likelihood of a tracking failure. This target-surrounding context can be used to prevent tracking failure where the background has similar objects. In the experimental of the scene which occurs occlusion by similar objects, the proposed method outperformed most of the conventional methods.