Fast shape re-ranking with neighborhood induced similarity measure

Authors:
Chunyuan Li;Changxin Gao;Sirui Xing;Abdessamad Ben Hamza
Affiliations:
Huazhong University of Science and Technology, China;Huazhong University of Science and Technology, China;Huazhong University of Science and Technology, China;Concordia Institute for Information Systems Engineering, Concordia University, Montréal, QC, Canada
Venue:
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Year:
2011

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Abstract

In this paper, we address the shape retrieval problem by casting it into the task of identifying "authority" nodes in an inferred similarity graph and also by re-ranking the shapes. The main idea is that the average similarity between a node and its neighboring nodes takes into account the local distribution and therefore helps modify the neighborhood edge weight, which guides the re-ranking. The proposed approach is evaluated on both 2D and 3D shape datasets, and the experimental results show that the proposed neighborhood induced similarity measure significantly improves the shape retrieval performance.