Rotation invariant fast features for large-scale recognition

Gabriel Takacs; Vijay Chandrasekhar; Sam Tsai; David Chen; Radek Grzeszczuk; Bernd Girod

doi:10.1117/12.945968

15 October 2012 Rotation invariant fast features for large-scale recognition

Gabriel Takacs, Vijay Chandrasekhar, Sam Tsai, David Chen, Radek Grzeszczuk, Bernd Girod

Proceedings Volume 8499, Applications of Digital Image Processing XXXV; 84991D (2012) https://doi.org/10.1117/12.945968
Event: SPIE Optical Engineering + Applications, 2012, San Diego, California, United States

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.²Such high-speed features benefit a range of applications from Mobile Augmented Reality (MAR) to web-scale image retrieval and analysis.

Citation Download Citation

Gabriel Takacs, Vijay Chandrasekhar, Sam Tsai, David Chen, Radek Grzeszczuk, and Bernd Girod "Rotation invariant fast features for large-scale recognition", Proc. SPIE 8499, Applications of Digital Image Processing XXXV, 84991D (15 October 2012); https://doi.org/10.1117/12.945968

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