Predictive vector quantization of 3-D mesh geometry by representation of vertices in local coordinate systems

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Küçük Resim

Tarih

2007-08

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Elsevier Inc

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Araştırma projeleri

Organizasyon Birimleri

Dergi sayısı

Özet

In predictive 3-D mesh geometry coding, the position of each vertex is predicted from the previously coded neighboring vertices and the resultant prediction error vectors are coded. In this work, the prediction error vectors are represented in a local coordinate system in order to cluster them around a subset of a 2-D planar subspace and thereby increase block coding efficiency. Alphabet entropy constrained vector quantization (AECVQ) of Rao and Pearlman is preferred to the previously employed minimum distortion vector quatitization (MDVQ) for block coding the prediction error vectors with high coding efficiency and low implementation complexity. Estimation and compensation of the bias in the parallelogram prediction rule and partial adaptation of the AECVQ codebook to the encoded vector source by normalization using source statistics, are the other salient features of the proposed coding system. Experimental results verify the advantage of the use of the local coordinate system over the global one. The visual error of the proposed coding system is lower than the predictive coding method of Touma and Gotsman especially at low rates, and lower than the spectral coding method of Karni and Gotsman at medium-to-high rates.

Açıklama

This work was partially supported by and carried out under Project No. 103E004 of TUBITAK (The Scientific & Technological Research Council of Turkey).

Anahtar Kelimeler

Mesh geometry compression, Entropy constrained vector quantization, Local coordinate system, Shannon lower bound, Parallelogram, Prediction, Compression, Connectivity, Design, Error, Codec, Error analysis, Image coding, Mesh generation, Statistical methods, Image representation, Minimum distortion vector quantization, Vector quantization

Kaynak

Journal of Visual Communication and Image Representation

WoS Q Değeri

Q2
Q2

Scopus Q Değeri

Q1

Cilt

18

Sayı

4

Künye

Bayazit, U., Orcay, O., Konur, U., & Gürgen, S. F.(2007). Predictive vector quantization of 3-D mesh geometry by representation of vertices in local coordinate systems. Journal of Visual Communication and Image Representation, 18(4), 341-353. doi:10.1016/j.jvcir.2007.03.001