Journal
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
Volume 42, Issue 3, Pages 729-739Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMCB.2011.2175726
Keywords
Coarse to fine; pedestrian detection; performance evaluation; spatiotemporal refinement; sudden pedestrian crossing
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Funding
- National Basic Research Program of China (973 Program) [2012CB316400]
- Singapore A*STAR SERC [082 101 0018]
- National Natural Science Foundation of China [61125106, 60972103, 61072093]
- Open Project Foundation of State Key Laboratory of Industrial Control Technology, Zhejiang University [ICT1105]
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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.
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