Video object tracking using graph cuts and location-dependent appearance models

In this paper we present a generic video object tracking scheme that combines a feature point tracker with a graph cut based image segmentation algorithm. The system deals with deformable objects in dynamic scenes and is initialized by a ground truth of the object region in the first frame. Hence colour models representing the appearance of the foreground object and background can be estimated. Starting from a holistic approach, we extend these models by the incorporation of spatial information resulting in a section-based background and a part-based object model. The displacement vectors obtained by the feature point tracker allow for the propagation of these location-dependent appearance models into the next frame. Subsequently a graph-cut based image segmentation algorithm segments the current frame based on these models. That way a gradual tracking and segmentation of the object can be performed. Quantitative and qualitative findings demonstrate the validity of this approach.