Visual Tracking via Part-Based Model with Auxiliary Objects

In most model-free tracking algorithms, context of the target is usually taken as source of negative examples for training the appearance model and thus not fully utilized. In fact, the target is embedded in its context, and there are spatial constraints between them with the potential motion correlations and relative locations. This paper presents a part-based model to describe the spatial constraints between the target object and its context. Auxiliary objects are selected as parts of the part based model to represent the context information. These auxiliary objects should have some properties: (i) co-occurrence with the target, (ii) having distinct appearance, and (iii) having homogeneous motion as an invisible visual region. A template-based model concerning about the object appearance is implemented to help estimate the reliability of tracking and make the part-based model updated properly. We test the proposed method on a recent benchmark with 50 video sequences evaluated, and a superior performance is achieved compared with state-of-the-arts.