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Pedestrian detection and tracking with night vision

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3 Author(s)
Fengliang Xu ; Geodetic Sci. Dept., Ohio State Univ., Columbus, OH, USA ; Xia Liu ; Fujimura, K.

This paper presents a method for pedestrian detection and tracking using a single night-vision video camera installed on the vehicle. To deal with the nonrigid nature of human appearance on the road, a two-step detection/tracking method is proposed. The detection phase is performed by a support vector machine (SVM) with size-normalized pedestrian candidates and the tracking phase is a combination of Kalman filter prediction and mean shift tracking. The detection phase is further strengthened by information obtained by a road-detection module that provides key information for pedestrian validation. Experimental comparisons (e.g., grayscale SVM recognition versus binary SVM recognition and entire-body detection versus upper-body detection) have been carried out to illustrate the feasibility of our approach.

Published in:

Intelligent Transportation Systems, IEEE Transactions on  (Volume:6 ,  Issue: 1 )

Date of Publication:

March 2005

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