Expression-invariant and sparse representation for mesh-based compression for 3-D face models

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

1 Scopus Citations
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Author(s)

  • Junhui Hou
  • Lap-Pui Chau
  • Ying He
  • Nadia Magnenat-Thalmann

Detail(s)

Original languageEnglish
Title of host publicationIEEE VCIP 2013 - 2013 IEEE International Conference on Visual Communications and Image Processing
Publication statusPublished - 2013
Externally publishedYes

Conference

Title2013 IEEE International Conference on Visual Communications and Image Processing, IEEE VCIP 2013
PlaceMalaysia
CityKuching, Sarawak
Period17 - 20 November 2013

Abstract

Compression of mesh-based 3-D models has been an important issue, which ensures efficient storage and transmission. In this paper, we present a very effective compression scheme specifically for expression variation 3-D face models. Firstly, 3-D models are mapped into 2-D parametric domain and corresponded by expression-invariant parameterizaton, leading to 2-D image format representation namely geometry images, which simplifies the 3-D model compression into 2-D image compression. Then, sparse representation with learned dictionaries via K-SVD is applied to each patch from sliced GI so that only few coefficients and their indices are needed to be encoded, leading to low datasize. Experimental results demonstrate that the proposed scheme provides significant improvement in terms of compression performance, especially at low bitrate, compared with existing algorithms. © 2013 IEEE.

Research Area(s)

  • geometry image, K-SVD, Mesh model compression, parameterization, sparse representation

Citation Format(s)

Expression-invariant and sparse representation for mesh-based compression for 3-D face models. / Hou, Junhui; Chau, Lap-Pui; He, Ying; Magnenat-Thalmann, Nadia.

IEEE VCIP 2013 - 2013 IEEE International Conference on Visual Communications and Image Processing. 2013. 6706442.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review