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Geometry compression of 3-D mesh models using predictive two-stage quantization

In conventional predictive quantization schemes for 3-D mesh geometry, excessively large residuals or prediction errors, although occasional, lead to visually unacceptable geometric distortion. This is due to the fact that they cannot limit the maximum quantization error within a given bound. In ord...

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Published in:IEEE transactions on circuits and systems for video technology 2000-03, Vol.10 (2), p.312-322
Main Authors: Choi, Jin Soo, Kim, Yong Han, Lee, Ho-Jang, Park, In-Sung, Lee, Myoung Ho, Ahn, Chieteuk
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cited_by cdi_FETCH-LOGICAL-c367t-4767d0d1fde56cfa4f10dd1555bd9842c4aae69211ce376e957bb7c8c61e48463
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creator Choi, Jin Soo
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description In conventional predictive quantization schemes for 3-D mesh geometry, excessively large residuals or prediction errors, although occasional, lead to visually unacceptable geometric distortion. This is due to the fact that they cannot limit the maximum quantization error within a given bound. In order to completely eliminate the visually unacceptable distortion caused by large residuals, we propose a predictive two-stage quantization scheme. This scheme is very similar to the conventional DPCM, except that the embedded quantizer is replaced by a series of two quantizers. Each quantizer output is further compressed by an arithmetic code. When applied to typical 3-D mesh models, the scheme performs much better than the conventional predictive quantization methods and, depending upon the input models, even than the MPEG-4 compression method for 3-D mesh geometry both in rate distortion sense and in subjective viewing.
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ispartof IEEE transactions on circuits and systems for video technology, 2000-03, Vol.10 (2), p.312-322
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1558-2205
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subjects Arithmetic
Circuits
Compressing
Computer graphics
Counters
Distortion
Errors
Finite element method
Geometry
IP networks
Mathematical models
MPEG 4 Standard
Predictive coding
Predictive models
Quantization
Rate-distortion
Solid modeling
title Geometry compression of 3-D mesh models using predictive two-stage quantization
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