TRAFFIC SIGN RECOGNITION WITH CONSTELLATIONS OF VISUAL WORDS

Toon Goedemé

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

  1. Arya, S., Mount, D., Netanyahu, N., Silverman, R., , and Wu, A. (1998). An optimal algorithm for approximate nearest neighbor searching. In J. of the ACM, vol. 45, pp. 891-923.
  2. Ballerini, R., Cinque, L., Lombardi, L., and Marmo, R. (2005). Rectangular Traffic Sign Recognition. Springer Berlin / Heidelberg.
  3. Baumberg, A. (2000). Reliable feature matching across widely separated views. In Computer Vision and Pattern Recognition, Hilton Head, South Carolina, pp. 774-781.
  4. Bay, H., Tuytelaars, T., and Gool, L. V. (2006). Speeded up robust features. In ECCV.
  5. Fasel, B. and Gool, L. V. (2007). Interactive museum guide: Accurate retrieval of object descriptions. In Adaptive Multimedia Retrieval: User, Context, and Feedback, Lecture Notes in Computer Science, Springer, volume 4398.
  6. Garcia-Garrido, M., Sotelo, M., and Martin-Gorostiza, E. (2006). Fast traffic sign detection and recognition under changing lighting conditions. In Intelligent Transportation Systems Conference 2006, pp. 811 - 816.
  7. Goedemé, T., Tuytelaars, T., Nuttin, M., and Gool, L. V. (2006). Omnidirectional vision based topological navigation. In International Journal of Computer Vision and International Journal of Robotics Research, Special Issue: Joint Issue of IJCV and IJRR on Vision and Robotics.
  8. Zhu, S. and Liu, L. (2006). Traffic sign recognition based on color standardization. In IEEE International Conference on Information Acquisition 2006, pp. 951-955, Veihai, China.
Download


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