Abstract
This paper presents a new method for extracting pedestrian contours from images using 2D and 3D information obtained from a stereo-vision acquisition system. Two pedestrian contour types are extracted. First is obtained from static pedestrian confidence images using fixed background scenes and second from general traffic scenes having variable background. A robust approach for building contour hierarchies of these contours is then presented. First hierarchy is built of ”perfect” contours extracted from fixed background scenes and the second one is built of ”imperfect” contours extracted from images with variable background. The objective is to evaluate the two hierarchies in order to identify the best one for real time pedestrian detection.
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Giosan, I., Nedevschi, S. (2009). Building Pedestrian Contour Hierarchies for Improving Detection in Traffic Scenes. In: Bolc, L., Kulikowski, J.L., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2008. Lecture Notes in Computer Science, vol 5337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02345-3_16
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DOI: https://doi.org/10.1007/978-3-642-02345-3_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02344-6
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