Journal article
Illuminance flow estimation by regression
- Abstract:
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We investigate the estimation of illuminance flow using Histograms of Oriented Gradient features (HOGs). In a regression setting, we found for both ridge regression and support vector machines, that the optimal solution shows close resemblance to the gradient based structure tensor (also known as the second moment matrix).
Theoretical results are presented showing in detail how the structure tensor and the HOGs are connected. This relation will benefit computer vision tasks such as affine invariant texture/object matching using HOGs.
Several properties of HOGs are presented, among others, how many bins are required for a directionality measure, and how to estimate HOGs through spatial averaging that requires no binning.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, pdf, 529.9KB, Terms of use)
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- Publisher copy:
- 10.1007/s11263-010-0353-7
Authors
- Funder identifier:
- https://ror.org/00k4n6c32
- Grant:
- MRTN-CT2004-005439
- Programme:
- VISIONTRAIN
- Publisher:
- Springer
- Journal:
- International Journal of Computer Vision More from this journal
- Volume:
- 90
- Issue:
- 3
- Pages:
- 304-312
- Publication date:
- 2010-06-09
- Acceptance date:
- 2010-05-07
- DOI:
- EISSN:
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1573-1405
- ISSN:
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0920-5691
- Language:
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English
- Keywords:
- Pubs id:
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90952
- Local pid:
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pubs:90952
- Deposit date:
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2024-07-22
- ARK identifier:
Terms of use
- Copyright holder:
- Karlsson et al.
- Copyright date:
- 2010
- Rights statement:
- © The Author(s) 2010. This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
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