3D model metrieval based on volumetric extended gaussian image and hierarchical self organizing map

Jiqi Zhang, Hau-San Wong, Zhiwen Yu

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

9 Citations (Scopus)

Abstract

In this paper, we introduce a novel shape signature, called Volumetric Extended Gaussian Image (VEGI). It captures the volumetric distribution of a 3D mesh model along the latitude-longitude direction without conventional pose normalization and is translation and scaling invariant. Rotation invariance is accomplished by further calculating the spherical harmonic transform of this directional distribution. Due to the completeness and orthonormality properties of spherical harmonics, the VEGI also provides multi-resolution description of a model so that a multi-level indexing scheme based on Hierarchical Self Organizing Map (HSOM) can be established to improve retrieval efficiency. Experimental results show that our retrieval architecture has high discriminative power and outperforms many existing methods.
Original languageEnglish
Title of host publicationProceedings of the 14th Annual ACM International Conference on Multimedia, MM 2006
Pages121-124
DOIs
Publication statusPublished - 2006
Event14th Annual ACM International Conference on Multimedia, MM 2006 - Santa Barbara, CA, United States
Duration: 23 Oct 200627 Oct 2006

Conference

Conference14th Annual ACM International Conference on Multimedia, MM 2006
Country/TerritoryUnited States
CitySanta Barbara, CA
Period23/10/0627/10/06

Research Keywords

  • 3D model retrieval
  • Hierarchical self organizing map
  • Volumetric extended Gaussian image

Fingerprint

Dive into the research topics of '3D model metrieval based on volumetric extended gaussian image and hierarchical self organizing map'. Together they form a unique fingerprint.

Cite this