TRAFFIC SIGN RECOGNITION WITH CONSTELLATIONS OF VISUAL WORDS

Toon Goedemé

2008

Abstract

In this paper, we present a method for fast and robust object recognition. As an example, the method is applied to traffic sign recognition from a forward-looking camera in a car. To facilitate and optimise the implementation of this algorithm on an embedded platform containing parallel hardware, we developed a voting scheme for constellations of visual words, i.e. clustered local features (SURF in this case). On top of easy implementation and robust and fast performance, even with large databases, an extra advantage is that this method can handle multiple identical visual features in one model.

References

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Paper Citation


in Harvard Style

Goedemé T. (2008). TRAFFIC SIGN RECOGNITION WITH CONSTELLATIONS OF VISUAL WORDS . In Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-8111-31-9, pages 222-227. DOI: 10.5220/0001495302220227


in Bibtex Style

@conference{icinco08,
author={Toon Goedemé},
title={TRAFFIC SIGN RECOGNITION WITH CONSTELLATIONS OF VISUAL WORDS},
booktitle={Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2008},
pages={222-227},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001495302220227},
isbn={978-989-8111-31-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - TRAFFIC SIGN RECOGNITION WITH CONSTELLATIONS OF VISUAL WORDS
SN - 978-989-8111-31-9
AU - Goedemé T.
PY - 2008
SP - 222
EP - 227
DO - 10.5220/0001495302220227