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Proceedings Paper

Fast quantization and matching of histogram-based image features
Author(s): Yuriy A. Reznik; Vijay Chandrasekhar; Gabriel Takacs; David M. Chen; Sam S. Tsai; Bernd Girod
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Paper Abstract

We review construction of a Compressed Histogram of Gradients (CHoG) image feature descriptor, and study quantization problem that arises in its design. We explain our choice of algorithms for solving it, addressing both complexity and performance aspects. We also study design of algorithms for decoding and matching of compressed descriptors, and offer several techniques for speeding up these operations.

Paper Details

Date Published: 7 September 2010
PDF: 14 pages
Proc. SPIE 7798, Applications of Digital Image Processing XXXIII, 77980L (7 September 2010); doi: 10.1117/12.862362
Show Author Affiliations
Yuriy A. Reznik, Qualcomm Inc. (United States)
Vijay Chandrasekhar, Stanford Univ. (United States)
Gabriel Takacs, Stanford Univ. (United States)
David M. Chen, Stanford Univ. (United States)
Sam S. Tsai, Stanford Univ. (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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