sr-sihks：一种非刚体全局形状特征 sr-sihksglobal shape descriptor for non-rigid 3d object.pdfVIP

12 2014 ，50（4 ） Computer Engineering and Applications 计算机工程与应用 SR-SIHKS ：一种非刚体全局形状特征 1，2 ，3 1，2 1，2 万丽莉 ，苗振江 ，岑翼刚 WAN Lili1，2 ，3 , MIAO Zhenjiang1，2 , CEN Yigang1，2 1.北京交通大学 计算机与信息技术学院 信息科学研究所，北京 100044 2.北京交通大学 现代信息科学与网络技术北京市重点实验室，北京 100044 3.北京航空航天大学 虚拟现实技术与系统国家重点实验室，北京 100191 1.Institute of Information Science, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China 2.Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing 100044, China 3.State Key Laboratory of Virtual Reality Technology and Systems ，Beihang University, Beijing 100191, China WAN Lili, MIAO Zhenjiang, CEN Yigang. SR-SIHKS ：global shape descriptor for non-rigid 3D object. Computer Engineering and Applications, 2014, 50 （4 ）：12-17. 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. Key words ：3D model retr