Evaluation of 3D Model Segmentation Techniques Based on Animal Anatomy

3D model decomposition is a challenging and important problem in computer graphics. Several semantically based approaches have been proposed in the literature, however, due to the lack of proper evaluation criteria, comparison of these techniques is almost impossible. In this paper we suggest to use animal anatomy as the ground truth and compare the result of different segmentation techniques based on that. Differing from previous approaches which perform the evaluation based on ground truth databases created subjectively by human observers, we consider expert knowledge on anatomy of various animals. Based on this knowledge we specify the ground truth for different animals and compare alternative algorithms.