Sensors 2010, 10(9), 8028-8053; doi:10.3390/s100908028
Article

Identifying and Tracking Pedestrians Based on Sensor Fusion and Motion Stability Predictions

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Received: 1 July 2010; in revised form: 9 August 2010 / Accepted: 26 August 2010 / Published: 27 August 2010
(This article belongs to the Special Issue Intelligent Sensors - 2010)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: The lack of trustworthy sensors makes development of Advanced Driver Assistance System (ADAS) applications a tough task. It is necessary to develop intelligent systems by combining reliable sensors and real-time algorithms to send the proper, accurate messages to the drivers. In this article, an application to detect and predict the movement of pedestrians in order to prevent an imminent collision has been developed and tested under real conditions. The proposed application, first, accurately measures the position of obstacles using a two-sensor hybrid fusion approach: a stereo camera vision system and a laser scanner. Second, it correctly identifies pedestrians using intelligent algorithms based on polylines and pattern recognition related to leg positions (laser subsystem) and dense disparity maps and u-v disparity (vision subsystem). Third, it uses statistical validation gates and confidence regions to track the pedestrian within the detection zones of the sensors and predict their position in the upcoming frames. The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle.
Keywords: pedestrian detection; advanced driver assistance systems; stereo vision; laser technology; confidence intervals; sensor fusion
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MDPI and ACS Style

Musleh, B.; García, F.; Otamendi, J.; Armingol, J.M.; De la Escalera, A. Identifying and Tracking Pedestrians Based on Sensor Fusion and Motion Stability Predictions. Sensors 2010, 10, 8028-8053.

AMA Style

Musleh B, García F, Otamendi J, Armingol JM, De la Escalera A. Identifying and Tracking Pedestrians Based on Sensor Fusion and Motion Stability Predictions. Sensors. 2010; 10(9):8028-8053.

Chicago/Turabian Style

Musleh, Basam; García, Fernando; Otamendi, Javier; Armingol, José Mª; De la Escalera, Arturo. 2010. "Identifying and Tracking Pedestrians Based on Sensor Fusion and Motion Stability Predictions." Sensors 10, no. 9: 8028-8053.

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