General object tracking with a component-based target descriptor

In this paper, we present a component-based visual object tracker for mobile platforms. The core of the technique is a component-based descriptor that captures the structure and appearance of a target in a flexible way. This descriptor can be learned quickly from a single training image and is easily adaptable to different objects. The descriptor is integrated into the observation model of a visual tracker based on the well known Condensation algorithm. We show that the approach is applicable to a large variety of objects and in different environments with cluttered backgrounds and a moving camera. The method is robust to illumination and viewpoint changes and applicable to indoor as well as outdoor scenes.