Pedestrian recognition for intelligent transportation systems
نویسندگان
چکیده
This paper describes a binocular vision-based pedestrian recognition System. The basic components of pedestrians are first located in the image and then combined with a SVM-based classifier. This poses the problem of pedestrian detection and recognition in real, cluttered road images. Candidate pedestrians are located using a subtractive clustering attention mechanism. A distributed learning approach is proposed in order to better deal with pedestrians variability, illumination conditions, partial occlusions and rotations. The performance of the pedestrian recognition system is enhanced by a multiframe validation process. By doing so, the detection rate is largely increased. A database containing hundreds of pedestrian examples extracted from real traffic images has been created for learning purposes. We present and discuss the results achieved up to date.
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