Evaluation of a hypothesizer for silhouette-based 3-D object recognition

Shape retrieval and shape-based object recognition are closely related problems; however, they have different task contexts, performance criteria, and database characteristics. In previous work, we proposed a method for similarity-based 2-D shape retrieval using scale-space part decompositions, part-frequency distributions, and structural indexing. In this paper, we evaluate the use of that shape retrieval method as the hypothesis generation component of silhouette-based 3-D object recognition systems, using a performance criterion and test database appropriate for the new application.