Minimizing the search space for shape retrieval algorithms

Abstract

To provide satisfactory accuracy and flexibility, most of the existing shape retrieval methods make use of different alignments and translations of the objects that introduce much computational complexity. The most computationally expensive part of these algorithms is measuring the degree of match (or mismatch) of the query object with the objects stored in database. In this paper, we present an approach to cut down a large portion of this search space (number of objects in database) that retrieval algorithms need to take into account. This method is applicable in clustering based approaches also. Moreover, this minimization is done keeping the accuracy of the retrieval algorithms intact and its efficiency is not severely affected in high dimensionalities. © Springer-Verlag Berlin Heidelberg 2006.