| ECVision indexed and annotated bibliography of cognitive computer vision publications This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1 The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
Fabien Pelisson and Daniela Hall and Olivier Riff and James L Crowley
ABSTRACT
In this article, we describe a module for the identification of brand logos from video data. A model for the visual appearance of each logo is generated from a small number of sample images using multi-dimensional histograms of scale-normalised chromatic Gaussian receptive fields. We compare several state-of-the-art identification techniques, based multi-dimensional histograms. Each of the methods display high recognition rates and can be used for logo identification. Our method for calculating scale normalized Gaussian receptive fields has linear computational complexity, and is thus well adapted to a real time system. However, with the current generation of micro-processors we obtain at best only 2 images per second when processing a full PAL video stream. To accelerate the process, we propose an architecture that applies color based logo detection to initiate a robust tracking process. Tracked logos are then identified off line using receptive field histograms. The resulting real time system is evaluated using video streams from sports Formula-1 races and football. |
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