Method for traffic sign detection

Image analysis – Applications – Target tracking or detecting

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C382S104000, C382S156000, C382S159000, C382S165000, C382S291000, C700S048000, C700S051000, C706S020000

Reexamination Certificate

active

07466841

ABSTRACT:
A method for detecting and recognizing at least one traffic sign is disclosed. A video sequence having a plurality of image frames is received. One or more filters are used to measure features in at least one image frame indicative of an object of interest. The measured features are combined and aggregated into a score indicating possible presence of an object. The scores are fused over multiple image frames for a robust detection. If a score indicates possible presence of an object in an area of the image frame, the area is aligned with a model. A determination is then made as to whether the area indicates a traffic sign. If the area indicates a traffic sign, the area is classified into a particular type of traffic sign. The present invention is also directed to training a system to detect and recognize traffic signs.

REFERENCES:
patent: 6266442 (2001-07-01), Laumeyer et al.
patent: 7072494 (2006-07-01), Georgescu et al.
patent: 7092548 (2006-08-01), Laumeyer et al.
patent: 7212651 (2007-05-01), Viola et al.
patent: 2001/0036293 (2001-11-01), Laumeyer et al.
patent: 2004/0186816 (2004-09-01), Lienhart et al.
patent: 2004/0234136 (2004-11-01), Zhu et al.
patent: 2006/0034484 (2006-02-01), Bahlmann et al.
patent: 2006/0165258 (2006-07-01), Avidan
patent: 2006/0177099 (2006-08-01), Zhu et al.
patent: 2007/0183651 (2007-08-01), Comaniciu et al.
patent: 2008/0069400 (2008-03-01), Zhu et al.
patent: WO 00/30024 (2000-05-01), None
Lindner F et al, “Robust Recognition of Traffic Signals”, Intelligent Vehicles Symposium, 2004 IEEE Parma, Italy, Jun. 14-16, 2004, pp. 49-53.
Wender S et al, “A Cascade Detector Approach Applied to Vehicle Occupant Monitoring with an Omni-directional Camera”, Intelligent Vehicles Symposium, 2004 IEEE, Jun. 14, 2004, pp. 345-350.
Jouny I et al, “M-ary Sequential Hypothesis Tests for Automatic Target Recognition”, Apr. 1992, IEEE Transactions on Aerospace and Electronic Systems, IEEE Inc., New York, US, pp. 473-483.
International Search Report including Notification of Transmittal of the International Search Report, International Search Report, and Written Opinion of the International Searching Authority.
Barnes et al., “Real-time radial symmetry for speed sign detection”, IEEE Intelligent Vehicles Symposium (IV), pp. 566-571, Parma, Italy, 2004.
de la Escalera et al., “Traffic sign recognition and analysis for intelligent vehicles”, Image and Vision Computing, 21, pp. 247-258, 2003.
de la Escalera, “Road traffic sign detection and classification”, IEEE Trans. Indust. Electronics, 44, pp. 848-859, 1997.
Fang et al., “Road-sign detection and tracking”, IEEE Trans. Vehicular Technology, 52(5), pp. 1329-1341, Sep. 2003.
Miura et al., “An active vision system for real-time traffic sign recognition”, Proc. IEEE Conf. on Intelligent Transportation Systems (ITS), pp. 52-57, Dearborn, MI, 2000.
Paclik et al., “Road sign classification using Laplace kemel classifier”, Pattern Recognition Lett., 21(13-14), pp. 1165-1173, 2000.
Piccioli et al., “A robust method for road sign detection and recognition”, Computer Vision—ECCV, pp. 495-500, Springer Verlag, 1994.
Schapire, “A brief introduction to boosting”, Proc. Of the 16thInt. Joint Conf. on Artificial Intelligence, 1999.
Torresen et al., “Efficient recognition of speed limit signs”, Proc. IEEE Conf. on Intelligent Transportation Systems (ITS), Washington, DC, 2004.
Viola et al., “Robust real-time object detection”, Technical Report CRL 2001/01, Cambridge Research Laboratory, 2001.
Xie et al., “Component fusion for face detection in the presence of heteroscedastic noise”, 25thPattern Recognition Symposium of the Germany Association for Pattern Recognition (DAGM), Magdeburg, Germany, 2003, Springer Verlag.
Zadeh et al., “Localization and recognition of traffic signs for automated vehicle control systems”, Proc. SPIE vol. 3207, Intelligent Transportation Systems, pp. 272-282, 1998.
Schapire et al., “Improved boosting algorithms using confidence-rated predictions”, Machine Learning, 37(3), pp. 297-336, 1999.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Method for traffic sign detection does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Method for traffic sign detection, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method for traffic sign detection will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-4033690

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.