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
Author(s)
Detail(s)
Original language | English |
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Title of host publication | IEEE VCIP 2013 - 2013 IEEE International Conference on Visual Communications and Image Processing |
Publication status | Published - 2013 |
Externally published | Yes |
Conference
Title | 2013 IEEE International Conference on Visual Communications and Image Processing, IEEE VCIP 2013 |
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Place | Malaysia |
City | Kuching, Sarawak |
Period | 17 - 20 November 2013 |
Link(s)
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 et al.
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