Improving 3D shape retrieval with SVM

In this paper we propose a technique that combines a classification method from the statistical learning literature with a conventional approach to shape retrieval. The idea that we pursue is to improve both results and performance by filtering the database of shapes before retrieval with a shape classifier, which allows us to keep only the shapes belonging to the classes most similar to the query shape. The experimental analysis that we report shows that our approach improves the computational cost in the average case, and leads to better results