Geodesic Shape Retrieval via Optimal Mass Transport

This paper presents a new method for 2-D and 3-D shape retrieval based on geodesic signatures. These signatures are high dimensional statistical distributions computed by extracting several features from the set of geodesic distance maps to each point. The resulting high dimensional distributions are matched to perform retrieval using a fast approximate Wasserstein metric. This allows to propose a unifying framework for the compact description of planar shapes and 3-D surfaces.

• Type: Conference
• Year: 2010
• Where: ECCV
• Authors: Julien Rabin, Gabriel Peyré, Laurent D. Cohen
• Keywords: 3-D Shape Retrieval, Computer Vision, ECCV 2010, Fast Approximate Wasserstein, Geodesic Signatures