计算机工程与应用Issue(4)：12-17,6.DOI:10.3778/j.issn.1002-8331.1308-0201
SR-SIHKS：一种非刚体全局形状特征
SR-SIHKS:global shape descriptor for non-rigid 3D object
摘要
Abstract
Non-rigid 3D objects have plenty of shape deformations because of posture variations, so non-rigid shape retrieval is more challenging than rigid shape retrieval. Shape descriptor is especially important to non-rigid shape retrieval. In order to improve the retrieval accuracy, a new global shape descriptor for non-rigid 3D object is proposed in this paper. The key idea of the approach is to represent the SIHKS(Scale Invariant Heat Kernel Signature)local shape descriptors by means of the sparse representation theory, so it is called SR-SIHKS. The computation of SIHKS is improved by adaptively deducing the time parameters from the non-rigid benchmark. K-SVD algorithm is adopted to train a dictionary, and the sparse repre-sentations of local shape descriptors are gained by Batch-OMP algorithm. The sparse representations of all local shape descriptors are integrated over the entire shape to form a global shape descriptor. Experimental results show SR-SIHKS has obviously better retrieval performance than SIHKS and HKS on some non-rigid shape retrieval benchmarks.关键词
三维模型检索/非刚体/形状特征/热核特征/稀疏表示Key words
3D model retrieval/non-rigid object/shape descriptor/heat kernel signature/sparse representation分类
信息技术与安全科学引用本文复制引用
万丽莉,苗振江,岑翼刚..SR-SIHKS：一种非刚体全局形状特征[J].计算机工程与应用,2014,(4):12-17,6.基金项目
北京市自然科学基金资助项目（No.4123104）；中央高校基本科研业务费专项资金（No.2011JBM224）；国家自然科学基金（No.61273274，No.61272028）；国家973重点基础研究发展计划（No.2011CB302203）。 （）
