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Proceedings Paper

Multi-features association-based local HOG description for image matching
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Paper Abstract

Image matching has always been a very important research areas in computer vision. The performance will directly affect the matching results. Among local descriptors, the Scale Invariant Feature Transform(SIFT) is a milestone in image matching, while HOG as an excellent descriptor is widely used in 2D object detection, but it seldom used as a descriptor for matching. In this article, we suppose to pool these algorithms and we use a simple modification of the Rotation- Invariant HOG(RI-HOG) to describe the feature domain detected by SIFT. The RI-HOG is Fourier analyzed in the polar/spherical coordinates. Later in our experiment, we test the performance of our method on a datasets. We are surprised to find that the method outperforms other descriptors in image matching in accuracy.

Paper Details

Date Published: 14 December 2015
PDF: 7 pages
Proc. SPIE 9813, MIPPR 2015: Pattern Recognition and Computer Vision, 981311 (14 December 2015); doi: 10.1117/12.2209096
Show Author Affiliations
Bingbing Wu, National Univ. of Defense Technology (China)
Shilin Zhou, National Univ. of Defense Technology (China)
Lin Lei, National Univ. of Defense Technology (China)
Kefeng Ji, National Univ. of Defense Technology (China)

Published in SPIE Proceedings Vol. 9813:
MIPPR 2015: Pattern Recognition and Computer Vision
Tianxu Zhang; Jianguo Liu, Editor(s)

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