Article

Non-parametric local transforms for computing visual correspondence

Authors:

Ramin Zabih,

John WoodfillAuthors Info & Claims

ECCV '94: Proceedings of the third European conference on Computer Vision (Vol. II)

Pages 151 - 158

Published: 07 May 1994 Publication History

Abstract

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Liu PChen GLi ZTang HKnoll A(2022)Learning Local Event-based Descriptor for Patch-based Stereo Matching2022 International Conference on Robotics and Automation (ICRA)10.1109/ICRA46639.2022.9811687(412-418)Online publication date: 23-May-2022
https://dl.acm.org/doi/10.1109/ICRA46639.2022.9811687
Jeon HPark JChoe GPark JBok YTai YKweon I(2019)Depth from a Light Field Image with Learning-Based Matching CostsIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2018.279497941:2(297-310)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1109/TPAMI.2018.2794979
Wu WZhu HZhang Q(2019)Oriented-linear-tree based cost aggregation for stereo matchingMultimedia Tools and Applications10.1007/s11042-018-6993-278:12(15779-15800)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1007/s11042-018-6993-2
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Index Terms

Non-parametric local transforms for computing visual correspondence
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision representations

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Published In

ECCV '94: Proceedings of the third European conference on Computer Vision (Vol. II)

May 1994

504 pages

ISBN:0387579575

Editor:
Jan-Olof Eklundh
Royal Institute of Technology, Stockholm, Sweden

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 07 May 1994

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Liu PChen GLi ZTang HKnoll A(2022)Learning Local Event-based Descriptor for Patch-based Stereo Matching2022 International Conference on Robotics and Automation (ICRA)10.1109/ICRA46639.2022.9811687(412-418)Online publication date: 23-May-2022
https://dl.acm.org/doi/10.1109/ICRA46639.2022.9811687
Jeon HPark JChoe GPark JBok YTai YKweon I(2019)Depth from a Light Field Image with Learning-Based Matching CostsIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2018.279497941:2(297-310)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1109/TPAMI.2018.2794979
Wu WZhu HZhang Q(2019)Oriented-linear-tree based cost aggregation for stereo matchingMultimedia Tools and Applications10.1007/s11042-018-6993-278:12(15779-15800)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1007/s11042-018-6993-2
Lai XXu XLv LHuang ZZhang JHuang P(2019)A novel non-parametric transform stereo matching method based on mutual relationshipComputing10.1007/s00607-018-00691-3101:6(621-635)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1007/s00607-018-00691-3
Dong QFeng J(2018)Adaptive disparity computation using local and non-local cost aggregationsMultimedia Tools and Applications10.1007/s11042-018-6236-677:24(31647-31663)Online publication date: 1-Dec-2018
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Shakoor MBoostani R(2018)Radial mean local binary pattern for noisy texture classificationMultimedia Tools and Applications10.1007/s11042-017-5440-077:16(21481-21508)Online publication date: 1-Aug-2018
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Shakoor MBoostani R(2018)A novel advanced local binary pattern for image-based coral reef classificationMultimedia Tools and Applications10.1007/s11042-017-4394-677:2(2561-2591)Online publication date: 1-Jan-2018
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Savinov NLadicky LPollefeys M(2017)Matching neural pathsProceedings of the 31st International Conference on Neural Information Processing Systems10.5555/3294771.3294886(1205-1214)Online publication date: 4-Dec-2017
https://dl.acm.org/doi/10.5555/3294771.3294886
Paget MTarel JMonasse P(2017)Stereo ambiguity index for semi-global matching2017 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2017.8296735(2513-2517)Online publication date: 17-Sep-2017
https://dl.acm.org/doi/10.1109/ICIP.2017.8296735
Song TMeng FWu QLuo BZhang TXu Y(2017)L2SSPNeurocomputing10.1016/j.neucom.2016.12.021230:C(230-242)Online publication date: 22-Mar-2017
https://dl.acm.org/doi/10.1016/j.neucom.2016.12.021
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The integer transforms analogous to discrete trigonometric transforms

Fractional cosine, sine, and Hartley transforms

Computing Transforms Using Their Eigenstructure

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