Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/97129
Title: Detection of sudden pedestrian crossings for driving assistance systems
Authors: Han, Tony X.
Xu, Yanwu
Xu, Dong
Lin, Stephen
Cao, Xianbin
Li, Xuelong
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2011
Source: Xu, Y., Xu, D., Lin, S., Han, T. X., Cao, X., & Li, X. (2012). Detection of Sudden Pedestrian Crossings for Driving Assistance Systems. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 42(3), 729-739.
Series/Report no.: IEEE transactions on systems, man, and cybernetics, part b (cybernetics)
Abstract: In this paper, we study the problem of detecting sudden pedestrian crossings to assist drivers in avoiding accidents. This application has two major requirements: to detect crossing pedestrians as early as possible just as they enter the view of the car-mounted camera and to maintain a false alarm rate as low as possible for practical purposes. Although many current sliding-window-based approaches using various features and classification algorithms have been proposed for image-/video-based pedestrian detection, their performance in terms of accuracy and processing speed falls far short of practical application requirements. To address this problem, we propose a three-level coarse-to-fine video-based framework that detects partially visible pedestrians just as they enter the camera view, with low false alarm rate and high speed. The framework is tested on a new collection of high-resolution videos captured from a moving vehicle and yields a performance better than that of state-of-the-art pedestrian detection while running at a frame rate of 55 fps.
URI: https://hdl.handle.net/10356/97129
http://hdl.handle.net/10220/11446
ISSN: 1083-4419
DOI: 10.1109/TSMCB.2011.2175726
Rights: © 2011 IEEE.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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