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Proceedings Paper

Permutable descriptors for orientation-invariant image matching
Author(s): Gabriel Takacs; Vijay Chandrasekhar; Huizhong Chen; David Chen; Sam Tsai; Radek Grzeszczuk; Bernd Girod
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Paper Abstract

Orientation-invariant feature descriptors are widely used for image matching. We propose a new method of computing and comparing Histogram of Gradients (HoG) descriptors which allows for re-orientation through permutation. We do so by moving the orientation processing to the distance comparison, rather than the descriptor computation. This improves upon prior work by increasing spatial distinctiveness. Our method method allows for very fast descriptor computation, which is advantageous since many mobile applications of HoG descriptors require fast descriptor computation on hand-held devices.

Paper Details

Date Published: 7 September 2010
PDF: 8 pages
Proc. SPIE 7798, Applications of Digital Image Processing XXXIII, 77980M (7 September 2010); doi: 10.1117/12.863993
Show Author Affiliations
Gabriel Takacs, Stanford Univ. (United States)
Vijay Chandrasekhar, Stanford Univ. (United States)
Huizhong Chen, Stanford Univ. (United States)
David Chen, Stanford Univ. (United States)
Sam Tsai, Stanford Univ. (United States)
Radek Grzeszczuk, Nokia Research Ctr. (United States)
Bernd Girod, Stanford Univ. (United States)


Published in SPIE Proceedings Vol. 7798:
Applications of Digital Image Processing XXXIII
Andrew G. Tescher, Editor(s)

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