Skip to Main Content
In this paper, we present a novel method for template simplification, where the template is used to find interesting objects within an image. In this way, we improve computational performance since less template points are matched using a simplified template. Moreover, we increase the reliability of the matching as we keep template points with focusing on the main shape behavior (skeleton) of the template. The theoretical background of the simplification is derived through the centroidal Voronoi tessellation framework. The efficiency of the proposed approach is demonstrated with detecting human appearance in thermal images.