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Proceedings Paper

Rotation invariant fast features for large-scale recognition
Author(s): Gabriel Takacs; Vijay Chandrasekhar; Sam Tsai; David Chen; Radek Grzeszczuk; Bernd Girod
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Paper Abstract

We present an end-to-end feature description pipeline which uses a novel interest point detector and Rotation- Invariant Fast Feature (RIFF) descriptors. The proposed RIFF algorithm is 15× faster than SURF1 while producing large-scale retrieval results that are comparable to SIFT.2 Such high-speed features benefit a range of applications from Mobile Augmented Reality (MAR) to web-scale image retrieval and analysis.

Paper Details

Date Published: 15 October 2012
PDF: 10 pages
Proc. SPIE 8499, Applications of Digital Image Processing XXXV, 84991D (15 October 2012); doi: 10.1117/12.945968
Show Author Affiliations
Gabriel Takacs, Nokia Research Ctr. (United States)
Vijay Chandrasekhar, Stanford Univ. (United States)
Sam Tsai, Stanford Univ. (United States)
David Chen, Stanford Univ. (United States)
Radek Grzeszczuk, Nokia Research Ctr. (United States)
Bernd Girod, Stanford Univ. (United States)

Published in SPIE Proceedings Vol. 8499:
Applications of Digital Image Processing XXXV
Andrew G. Tescher, Editor(s)

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