Citation

Xu Y, Xu D, Lin S, Han TX, Cao X, Li X. IEEE Trans. Syst. Man. Cybern. B Cybern. 2011; 42(3): 729-739.

Copyright

(Copyright © 2011, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/TSMCB.2011.2175726

PMID

22147306

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.

Language: en