IEICE TRANSACTIONS on Information
An Efficient Wide-Baseline Dense Matching Descriptor
Summary :
This letter proposes an efficient local descriptor for wide-baseline dense matching. It improves the existing Daisy descriptor by combining intensity-based Haar wavelet response with a new color-based ratio model. The color ratio model is invariant to changes of viewing direction, object geometry, and the direction, intensity and spectral power distribution of the illumination. The experiments show that our descriptor has high discriminative power and robustness.
- Publication
- IEICE TRANSACTIONS on Information Vol.E95-D No.7 pp.2021-2024
- Publication Date
- 2012/07/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E95.D.2021
- Type of Manuscript
- LETTER
- Category
- Image Recognition, Computer Vision
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Yanli WAN, Zhenjiang MIAO, Zhen TANG, Lili WAN, Zhe WANG, "An Efficient Wide-Baseline Dense Matching Descriptor" in IEICE TRANSACTIONS on Information,
vol. E95-D, no. 7, pp. 2021-2024, July 2012, doi: 10.1587/transinf.E95.D.2021.
Abstract: This letter proposes an efficient local descriptor for wide-baseline dense matching. It improves the existing Daisy descriptor by combining intensity-based Haar wavelet response with a new color-based ratio model. The color ratio model is invariant to changes of viewing direction, object geometry, and the direction, intensity and spectral power distribution of the illumination. The experiments show that our descriptor has high discriminative power and robustness.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E95.D.2021/_p
Copy
@ARTICLE{e95-d_7_2021,
author={Yanli WAN, Zhenjiang MIAO, Zhen TANG, Lili WAN, Zhe WANG, },
journal={IEICE TRANSACTIONS on Information},
title={An Efficient Wide-Baseline Dense Matching Descriptor},
year={2012},
volume={E95-D},
number={7},
pages={2021-2024},
abstract={This letter proposes an efficient local descriptor for wide-baseline dense matching. It improves the existing Daisy descriptor by combining intensity-based Haar wavelet response with a new color-based ratio model. The color ratio model is invariant to changes of viewing direction, object geometry, and the direction, intensity and spectral power distribution of the illumination. The experiments show that our descriptor has high discriminative power and robustness.},
keywords={},
doi={10.1587/transinf.E95.D.2021},
ISSN={1745-1361},
month={July},}
Copy
TY - JOUR
TI - An Efficient Wide-Baseline Dense Matching Descriptor
T2 - IEICE TRANSACTIONS on Information
SP - 2021
EP - 2024
AU - Yanli WAN
AU - Zhenjiang MIAO
AU - Zhen TANG
AU - Lili WAN
AU - Zhe WANG
PY - 2012
DO - 10.1587/transinf.E95.D.2021
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2012
AB - This letter proposes an efficient local descriptor for wide-baseline dense matching. It improves the existing Daisy descriptor by combining intensity-based Haar wavelet response with a new color-based ratio model. The color ratio model is invariant to changes of viewing direction, object geometry, and the direction, intensity and spectral power distribution of the illumination. The experiments show that our descriptor has high discriminative power and robustness.
ER -
English
