Article

TensorTextures: multilinear image-based rendering

Authors:

M. Alex O. Vasilescu,

Demetri TerzopoulosAuthors Info & Claims

SIGGRAPH '04: ACM SIGGRAPH 2004 Papers

Pages 336 - 342

https://doi.org/10.1145/1186562.1015725

Published: 01 August 2004 Publication History

Abstract

This paper introduces a tensor framework for image-based rendering. In particular, we develop an algorithm called TensorTextures that learns a parsimonious model of the bidirectional texture function (BTF) from observational data. Given an ensemble of images of a textured surface, our nonlinear, generative model explicitly represents the multifactor interaction implicit in the detailed appearance of the surface under varying photometric angles, including local (per-texel) reflectance, complex mesostructural self-occlusion, interreflection and self-shadowing, and other BTF-relevant phenomena. Mathematically, TensorTextures is based on multilinear algebra, the algebra of higher-order tensors, hence its name. It is computed through a decomposition known as the N-mode SVD, an extension to tensors of the conventional matrix singular value decomposition (SVD). We demonstrate the application of TensorTextures to the image-based rendering of natural and synthetic textured surfaces under continuously varying viewpoint and illumination conditions.

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Cited By

Wang XMo CQiao SWei Y(2022)Predefined-time convergent neural networks for solving the time-varying nonsingular multi-linear tensor equationsNeurocomputing10.1016/j.neucom.2021.11.108472:C(68-84)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1016/j.neucom.2021.11.108
Dana K(2021)Bidirectional Texture Function and 3D TextureComputer Vision10.1007/978-3-030-63416-2_263(79-83)Online publication date: 13-Oct-2021
https://doi.org/10.1007/978-3-030-63416-2_263
Le NWang JLe DWang CNguyen T(2020)Fingerprint Enhancement Based on Tensor of Wavelet Subbands for ClassificationIEEE Access10.1109/ACCESS.2020.29640358(6602-6615)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2964035
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Index Terms

TensorTextures: multilinear image-based rendering
1. Computing methodologies
  1. Computer graphics
    1. Image manipulation
      1. Texturing
    2. Rendering

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cover image ACM Conferences

SIGGRAPH '04: ACM SIGGRAPH 2004 Papers

August 2004

684 pages

ISBN:9781450378239

DOI:10.1145/1186562

Editor:
Joe Marks
Mitsubishi Electric Research Laboratories (MERL)

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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Published: 01 August 2004

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SIGGRAPH04: Special Interest Group on Computer Graphics and Interactive Techniques

August 8 - 12, 2004

California, Los Angeles

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SIGGRAPH '04 Paper Acceptance Rate 83 of 478 submissions, 17%;

Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

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Cited By

Wang XMo CQiao SWei Y(2022)Predefined-time convergent neural networks for solving the time-varying nonsingular multi-linear tensor equationsNeurocomputing10.1016/j.neucom.2021.11.108472:C(68-84)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1016/j.neucom.2021.11.108
Dana K(2021)Bidirectional Texture Function and 3D TextureComputer Vision10.1007/978-3-030-63416-2_263(79-83)Online publication date: 13-Oct-2021
https://doi.org/10.1007/978-3-030-63416-2_263
Le NWang JLe DWang CNguyen T(2020)Fingerprint Enhancement Based on Tensor of Wavelet Subbands for ClassificationIEEE Access10.1109/ACCESS.2020.29640358(6602-6615)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2964035
Le NWang JWang CNguyen T(2019)Novel Framework Based on HOSVD for Ski Goggles Defect Detection and ClassificationSensors10.3390/s1924553819:24(5538)Online publication date: 14-Dec-2019
https://doi.org/10.3390/s19245538
Dana K(2016)Bidirectional Texture Function and 3D TextureComputer Vision10.1007/978-0-387-31439-6_263(46-50)Online publication date: 5-Feb-2016
https://doi.org/10.1007/978-0-387-31439-6_263
Liţă LPelican E(2015)A low-rank tensor-based algorithm for face recognitionApplied Mathematical Modelling10.1016/j.apm.2014.08.00339:3-4(1266-1274)Online publication date: Feb-2015
https://doi.org/10.1016/j.apm.2014.08.003
Hillar CLim L(2013)Most Tensor Problems Are NP-HardJournal of the ACM10.1145/251232960:6(1-39)Online publication date: 1-Nov-2013
https://dl.acm.org/doi/10.1145/2512329
Gao JXing JHu WMaybank S(2013)Discriminant Tracking Using Tensor Representation with Semi-supervised Improvement2013 IEEE International Conference on Computer Vision10.1109/ICCV.2013.198(1569-1576)Online publication date: Dec-2013
https://doi.org/10.1109/ICCV.2013.198
Orjuela Vargas SYañez Puentes JPhilips W(2013)The Geometric Local Textural Patterns (GLTP)Local Binary Patterns: New Variants and Applications10.1007/978-3-642-39289-4_4(85-112)Online publication date: 1-Sep-2013
https://doi.org/10.1007/978-3-642-39289-4_4
Haindl MFilip JSander P(2011)Advanced textural representation of materials appearanceSIGGRAPH Asia 2011 Courses10.1145/2077434.2077435(1-84)Online publication date: 12-Dec-2011
https://dl.acm.org/doi/10.1145/2077434.2077435
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