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Proceedings Paper

Real-time implementation of logo detection on open source BeagleBoard
Author(s): M. George; N. Kehtarnavaz; L. Estevez
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Paper Abstract

This paper presents the real-time implementation of our previously developed logo detection and tracking algorithm on the open source BeagleBoard mobile platform. This platform has an OMAP processor that incorporates an ARM Cortex processor. The algorithm combines Scale Invariant Feature Transform (SIFT) with k-means clustering, online color calibration and moment invariants to robustly detect and track logos in video. Various optimization steps that are carried out to allow the real-time execution of the algorithm on BeagleBoard are discussed. The results obtained are compared to the PC real-time implementation results.

Paper Details

Date Published: 2 February 2011
PDF: 10 pages
Proc. SPIE 7871, Real-Time Image and Video Processing 2011, 787107 (2 February 2011); doi: 10.1117/12.871952
Show Author Affiliations
M. George, The Univ. of Texas at Dallas (United States)
N. Kehtarnavaz, The Univ. of Texas at Dallas (United States)
L. Estevez, Texas Instruments Inc. (United States)

Published in SPIE Proceedings Vol. 7871:
Real-Time Image and Video Processing 2011
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)

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