An evaluation of local feature encodings for shape retrieval

Local features are successfully used in 3D shape retrieval by encoding features descriptors into global shape signatures. Previous 3D retrieval systems use different encoding methods, such as histogram encoding and Fisher encodings, making it difficult to evaluate one encoding technique against another. We perform a comparative analysis of four recent encoding methods when used in shape retrieval. The analysis shows that Vector of Locally Aggregated Descriptors (VLAD) encoding is the best method of the four tested, since it offers the best trade-off between precision and computational cost.