Article

Signal-specialized parameterization for piecewise linear reconstruction

Authors:

Geetika Tewari,

Pedro V. Sander,

Steven J. Gortler,

Hugues HoppeAuthors Info & Claims

SGP '04: Proceedings of the 2004 Eurographics/ACM SIGGRAPH symposium on Geometry processing

Pages 55 - 64

https://doi.org/10.1145/1057432.1057440

Published: 08 July 2004 Publication History

Abstract

We propose a metric for surface parameterization specialized to its signal that can be used to create more efficient, high-quality texture maps. Derived from Taylor expansion of signal error, our metric predicts the signal approximation error - the difference between the original surface signal and its reconstruction from the sampled texture. Unlike previous methods, our metric assumes piecewise-linear reconstruction, and thus makes a good approximation to bilinear reconstruction employed in graphics hardware. We achieve significant savings in texture area for a desired signal accuracy compared to the signal-specialized parameterization metric proposed by Sander et al. in the 2002 Eurographics Workshop on Rendering.

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Cited By

Knodt JPan ZWu KGao X(2023)Joint UV Optimization and Texture BakingACM Transactions on Graphics10.1145/361768343:1(1-20)Online publication date: 28-Sep-2023
https://dl.acm.org/doi/10.1145/3617683
Sun HWang SWu WJin YBao HHuang J(2023)Efficient Texture Parameterization Driven by Perceptual‐Loss‐on‐ScreenComputer Graphics Forum10.1111/cgf.1469641:7(507-518)Online publication date: 20-Mar-2023
https://doi.org/10.1111/cgf.14696
Li JZhang Y(2022)Time Series Segmentation and Clustering Method Based on Cloud Model2022 12th International Conference on Information Science and Technology (ICIST)10.1109/ICIST55546.2022.9926837(153-160)Online publication date: 14-Oct-2022
https://doi.org/10.1109/ICIST55546.2022.9926837
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Index Terms

Signal-specialized parameterization for piecewise linear reconstruction
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition
        3D imaging
  2. Computer graphics
    1. Animation

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cover image ACM Other conferences

SGP '04: Proceedings of the 2004 Eurographics/ACM SIGGRAPH symposium on Geometry processing

July 2004

259 pages

ISBN:3905673134

DOI:10.1145/1057432

Conference Chairs:
Jean-Daniel Boissonnat
INRIA, France
,
Pierre Alliez
INRIA, France

Copyright © 2004 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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EUROGRAPHICS: The European Association for Computer Graphics

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 July 2004

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SGP04: Symposium on Geometry Processing

July 8 - 10, 2004

Nice, France

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Overall Acceptance Rate 64 of 240 submissions, 27%

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Cited By

Knodt JPan ZWu KGao X(2023)Joint UV Optimization and Texture BakingACM Transactions on Graphics10.1145/361768343:1(1-20)Online publication date: 28-Sep-2023
https://dl.acm.org/doi/10.1145/3617683
Sun HWang SWu WJin YBao HHuang J(2023)Efficient Texture Parameterization Driven by Perceptual‐Loss‐on‐ScreenComputer Graphics Forum10.1111/cgf.1469641:7(507-518)Online publication date: 20-Mar-2023
https://doi.org/10.1111/cgf.14696
Li JZhang Y(2022)Time Series Segmentation and Clustering Method Based on Cloud Model2022 12th International Conference on Information Science and Technology (ICIST)10.1109/ICIST55546.2022.9926837(153-160)Online publication date: 14-Oct-2022
https://doi.org/10.1109/ICIST55546.2022.9926837
Zhou KHu S(2018)An improved morphological weighted dynamic similarity measurement algorithm for time series dataInternational Journal of Intelligent Computing and Cybernetics10.1108/IJICC-12-2016-005911:4(486-495)Online publication date: 12-Nov-2018
https://doi.org/10.1108/IJICC-12-2016-0059
Shi LKong DWang SYin B(2017)Adaptive Geometry Images for RemeshingInternational Journal of Digital Multimedia Broadcasting10.1155/2017/27241842017Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1155/2017/2724184
Gao ZZou TZhang LChen JGuo JJi W(2017)Rapidly Generate and Visualize the Digest of Massive Time Series Data2017 IEEE Third International Conference on Big Data Computing Service and Applications (BigDataService)10.1109/BigDataService.2017.25(157-164)Online publication date: Apr-2017
https://doi.org/10.1109/BigDataService.2017.25
Limper MBrandherm FFellner DKuijper AJia JHamza-Lup FSchreck T(2015)Evaluating 3D thumbnails for virtual object galleriesProceedings of the 20th International Conference on 3D Web Technology10.1145/2775292.2775314(17-24)Online publication date: 18-Jun-2015
https://dl.acm.org/doi/10.1145/2775292.2775314
Panozzo DDiamanti OParis STarini MSorkine ESorkine-Hornung OAugsdörfer UWallner J(2015)Texture mapping real-world objects with hydrographicsProceedings of the Eurographics Symposium on Geometry Processing10.1111/cgf.12697(65-75)Online publication date: 6-Jul-2015
https://dl.acm.org/doi/10.1111/cgf.12697
de Goes FLiu BBudninskiy MTong YDesbrun MLai YMartin R(2014)Discrete 2-tensor fields on triangulationsProceedings of the Symposium on Geometry Processing10.1111/cgf.12427(13-24)Online publication date: 9-Jul-2014
https://dl.acm.org/doi/10.1111/cgf.12427
Gomes LRegina Pereira Bellon OSilva L(2014)3D reconstruction methods for digital preservation of cultural heritagePattern Recognition Letters10.1016/j.patrec.2014.03.02350:C(3-14)Online publication date: 1-Dec-2014
https://dl.acm.org/doi/10.1016/j.patrec.2014.03.023
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