Data driven composite shape descriptor design for shape retrieval with a VoR-Tree

作     者：WANG Zi-hao LIN Hong-wei XU Chen-kai 

作者机构：School of Mathematical Science State Key Lab.of CAD&CG Zhejiang University 

基　　金：supported by the National Key R&D Plan of China(2016YFB1001501) 

出 版 物：《Applied Mathematics(A Journal of Chinese Universities)》 (高校应用数学学报（英文版）（B辑）)

年 卷 期：2018年第33卷第1期

页      码：88-106页

摘      要：We develop a data driven method(probability model) to construct a composite shape descriptor by combining a pair of scale-based shape descriptors. The selection of a pair of scale-based shape descriptors is modeled as the computation of the union of two events, i.e.,retrieving similar shapes by using a single scale-based shape descriptor. The pair of scale-based shape descriptors with the highest probability forms the composite shape descriptor. Given a shape database, the composite shape descriptors for the shapes constitute a planar point set.A VoR-Tree of the planar point set is then used as an indexing structure for efficient query operation. Experiments and comparisons show the effectiveness and efficiency of the proposed composite shape descriptor.

主 题 词：shape descriptor shape retrieval shape analysis data-driven model 

学科分类：07[理学] 0701[理学-数学类] 070101[070101] 

核心收录：

D　O　I：10.1007/s11766-018-3536-6

馆 藏 号：203284491...