Section-based object tracking

Multiple-extremum issue including the well-known ¿singularity¿ problem is one of the major defects in kernel-based object tracking. This paper studies this important problem and presents a novel approach called section-based tracking (SBT) that is based on the section information provided by the division of the object´s weight image. This approach serves to eliminate fake extremal points and make the tracking process more robust. Besides, this paper proposes qualitative rules for section-based kernel design, which help create a better kernel within SBT framework. Experiments show that both the SBT method and the kernel design rules conduce to better performance in tracking process.