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Far infrared pedestrian detection and tracking for night driving

Published online by Cambridge University Press:  29 July 2010

Daniel Olmeda ,
Arturo de la Escalera  and
José María Armingol
Daniel Olmeda*
Affiliation:
Intelligent Systems Laboratory, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, C./ Butarque 15, 28911 Leganes, Spain
Arturo de la Escalera
Affiliation:
Intelligent Systems Laboratory, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, C./ Butarque 15, 28911 Leganes, Spain
José María Armingol
Affiliation:
Intelligent Systems Laboratory, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, C./ Butarque 15, 28911 Leganes, Spain
*
*Corresponding author. E-mail: dolmeda@ing.uc3m.es
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Summary

This paper presents a module for pedestrian detection from a moving vehicle in low-light conditions. The algorithm make use of a single far infrared camera based on a microbolometer. Images of the area ahead of the vehicle are analyzed to determine if any pedestrian might be in its trajectory. Detection is achieved by searching for distributions of temperatures in the scene similar to that of the human body. Those areas with an appropriate temperature, size, and position in the image are classified, by means of a correlation between them and some probabilistic models, which represents the average temperature of the different parts of the human body. Finally, those pedestrians found are tracked in a subsequent step, using an unscented Kalman filter. This final stage of the algorithm enables the algorithm to predict the trajectory of the pedestrian, in a way that does not depend on the movement of the camera. The aim of this system is to warn the vehicle's driver and reduce the reaction time in case an emergency break is necessary.

Keywords

Computer visionIR pedestrian detectionDriver Assistance SystemUnscented Kalman filterIntelligent Transportation Systems
Type
Articles
Information
Robotica , Volume 29 , Issue 4 , July 2011 , pp. 495 - 505
Copyright
Copyright © Cambridge University Press 2010

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