Progressive Coding of Binary Voxel Models Based on Pattern Code Representation

Bong Gyun ROH; Chang-Su KIM; Sang-Uk LEE

Progressive Coding of Binary Voxel Models Based on Pattern Code Representation

Bong Gyun ROH, Chang-Su KIM, Sang-Uk LEE

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In this paper, we propose a progressive encoding algorithm for binary voxel models, which represent 3D object shapes. For progressive transmission, multi-resolution models are generated by decimating an input voxel model. Then, each resolution model is encoded by employing the pattern code representation(PCR). In PCR, the voxel model is represented with a series of pattern codes. The pattern of a voxel informs of the local shape of the model around that voxel. PCR can achieve a coding gain, since the pattern codes are highly correlated. In the multi-resolution framework, the coding gain can be further improved by exploiting the decimation constraints from the lower resolution models. Furthermore, the shell classification scheme is proposed to reduce the number of pattern codes to represent the whole voxel model. Simulation results show that the proposed algorithm provides about 1.1-1.3 times higher coding gain than the conventional PCR algorithm.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E87-A No.12 pp.3334-3342

Publication Date: 2004/12/01

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Type of Manuscript: PAPER

Category: Digital Signal Processing

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Bong Gyun ROH, Chang-Su KIM, Sang-Uk LEE, "Progressive Coding of Binary Voxel Models Based on Pattern Code Representation" in IEICE TRANSACTIONS on Fundamentals, vol. E87-A, no. 12, pp. 3334-3342, December 2004, doi: .
Abstract: In this paper, we propose a progressive encoding algorithm for binary voxel models, which represent 3D object shapes. For progressive transmission, multi-resolution models are generated by decimating an input voxel model. Then, each resolution model is encoded by employing the pattern code representation(PCR). In PCR, the voxel model is represented with a series of pattern codes. The pattern of a voxel informs of the local shape of the model around that voxel. PCR can achieve a coding gain, since the pattern codes are highly correlated. In the multi-resolution framework, the coding gain can be further improved by exploiting the decimation constraints from the lower resolution models. Furthermore, the shell classification scheme is proposed to reduce the number of pattern codes to represent the whole voxel model. Simulation results show that the proposed algorithm provides about 1.1-1.3 times higher coding gain than the conventional PCR algorithm.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/e87-a_12_3334/_p

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@ARTICLE{e87-a_12_3334,
author={Bong Gyun ROH, Chang-Su KIM, Sang-Uk LEE, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Progressive Coding of Binary Voxel Models Based on Pattern Code Representation},
year={2004},
volume={E87-A},
number={12},
pages={3334-3342},
abstract={In this paper, we propose a progressive encoding algorithm for binary voxel models, which represent 3D object shapes. For progressive transmission, multi-resolution models are generated by decimating an input voxel model. Then, each resolution model is encoded by employing the pattern code representation(PCR). In PCR, the voxel model is represented with a series of pattern codes. The pattern of a voxel informs of the local shape of the model around that voxel. PCR can achieve a coding gain, since the pattern codes are highly correlated. In the multi-resolution framework, the coding gain can be further improved by exploiting the decimation constraints from the lower resolution models. Furthermore, the shell classification scheme is proposed to reduce the number of pattern codes to represent the whole voxel model. Simulation results show that the proposed algorithm provides about 1.1-1.3 times higher coding gain than the conventional PCR algorithm.},
keywords={},
doi={},
ISSN={},
month={December},}

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TY - JOUR
TI - Progressive Coding of Binary Voxel Models Based on Pattern Code Representation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 3334
EP - 3342
AU - Bong Gyun ROH
AU - Chang-Su KIM
AU - Sang-Uk LEE
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E87-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2004
AB - In this paper, we propose a progressive encoding algorithm for binary voxel models, which represent 3D object shapes. For progressive transmission, multi-resolution models are generated by decimating an input voxel model. Then, each resolution model is encoded by employing the pattern code representation(PCR). In PCR, the voxel model is represented with a series of pattern codes. The pattern of a voxel informs of the local shape of the model around that voxel. PCR can achieve a coding gain, since the pattern codes are highly correlated. In the multi-resolution framework, the coding gain can be further improved by exploiting the decimation constraints from the lower resolution models. Furthermore, the shell classification scheme is proposed to reduce the number of pattern codes to represent the whole voxel model. Simulation results show that the proposed algorithm provides about 1.1-1.3 times higher coding gain than the conventional PCR algorithm.
ER -