Sensors and Materials
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Sensors and Materials, Volume 29, Number 6(1) (2017)
Copyright(C) MYU K.K. All Rights Reserved.
pp. 713-726
S&M1362
http://dx.doi.org/10.18494/SAM.2017.1487
Published: June 7, 2017

Fast Estimation of Pedestrian Movement

Ying-Che Kuo, Cheng-Tao Tsai, and Chih-Hao Chang

(Received October 17, 2016; Accepted December 26, 2016)

Keywords: pedestrian detection, Fisher classifier, Lucas–Kanade optical flow

In this study, a single camera has been used to capture images of the road in front of a moving vehicle. Image processing algorithms identify the location of pedestrians in the images, calculate the direction and rate of movement of each one, and issue safety warnings. The pedestrian motion vector detection and warning system presented here has three components: The first serves to identify, locate, and mark the positions of pedestrians in images using the Fisher classifier. The follow-up image processing is confined to the labeled images, and this significantly reduces the image postprocessing load. The second component involves the calculation of pedestrian motion vectors using the Lucas–Kanade optical flow method. Finally, the vehicle’s future zone of movement is established, and judgment is made as to whether any pedestrians will be in this zone or not. This is determined from the pedestrian movement vectors and a warning can be triggered to alert the driver in time for any necessary avoidance action to be taken. This can improve road safety and reduce the number of accidents involving pedestrians, which result from driver fatigue, negligence or careless driving, and the number of such accidents can be reduced.

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