Abstract
This paper proposes a sensor fusion based obstacle detection/classification system for active pedestrian protection system. At the front-end of vehicle, one laser scanner and one camera is installed. Clustering and tracking of range data from laser scanner generate obstacle candidates. Vision system classifies the candidates into three categories: pedestrian, vehicle, and other. Gabor filter bank extracts the feature vector of candidate image. The obstacle classification is implemented by combining two classifiers with the same architecture: support vector machine for pedestrian and vehicle. Obstacle detection system recognizing the class can actively protect pedestrian while reducing false positive rate.
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Jung, H.G., Lee, Y.H., Yoon, P.J., Hwang, I.Y., Kim, J. (2006). Sensor Fusion Based Obstacle Detection/Classification for Active Pedestrian Protection System. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2006. Lecture Notes in Computer Science, vol 4292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11919629_31
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DOI: https://doi.org/10.1007/11919629_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-48626-8
Online ISBN: 978-3-540-48627-5
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