SmartCom 2017: Smart Computing and Communication pp 427-437 | Cite as

Improved Three-Dimensional Model Feature of Non-rigid Based on HKS

  • Fanzhi Zeng
  • Jiechang Qian
  • Yan Zhou
  • Changqing Yuan
  • Chen Wu
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10699)

Abstract

The recognition and retrieval of 3D models have been a hot spot in the field of computer vision. Since the non-rigid shapes can generate various deformations, the recognition and retrieval of non-rigid 3D models are more complex and challenging than rigid one. Therefore, the key to the recognition and retrieval of non-rigid 3D models is to extract a feature which obtains substantial description ability and stability. An improved HKS feature named NSIHKS (NSIHKS, new scale Invariance heat kernel signature) was used to describe the shape of models in the paper. NSIHKS contains intrinsic invariance, scale transformation invariance, robustness et al. Moreover it has good resistance even under faint noise. Firstly, the NSIHKS features of each model were extracted and processed with clustering algorithm. Secondly, an efficient algorithm of similarity measurement was designed on the basis of Ming distance. Finally, NSIHKS features of each model in the standard data set were compared via the aforementioned distance algorithm. Experimental results of standard data set in this field show that this feature has good effect on the application of non-rigid 3D model retrieval.

Keywords

3D model retrieval 3D non-rigid model Heat kernel signature Shape features Clustering 
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Notes

Acknowledgements

The authors would like to thank the editors and the anonymous reviewers for their constructive comments to further improve the quality of this paper. This work is partially supported by the following projects in China: the National Natural Science Foundation of China (No. 61602116), Natural Science Foundation of Guangdong Province (No. 2015A030313635, No. 2017A030313388), Science and Technology Project of Guangdong Province (No. 2014A010103037), Special Fund for Science and Technology Innovation of Foshan City (No. 2015AG10008, No. 2014AG10001, No. 2016GA10156), Education Department of Guangdong Province (No. 2015KTSCX153) and Outstanding Youth Teacher Training Program of Foshan University (No. FSYQ201411).

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Fanzhi Zeng
    • 1
  • Jiechang Qian
    • 2
  • Yan Zhou
    • 1
  • Changqing Yuan
    • 2
  • Chen Wu
    • 1
  1. 1.Department of ComputerFoshan UniversityFoshanChina
  2. 2.School of AutomationFoshan UniversityFoshanChina

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