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

Sensors

Basam Musleh¹  Fernando Garc໚¹  Javier Otamendi²  José Mª Armingol¹ 

[1] Intelligent Systems Laboratory, Universidad Carlos III de Madrid/ Avda de la Universidad 30, 28911, Leganés, Madrid, Spain; E-Mails:;Universidad Rey Juan Carlos/ Paseo Artilleros s/n. 28032, Vicálvaro, Madrid, Spain, E-Mail:

关键词: pedestrian detection;    advanced driver assistance systems;    stereo vision;    laser technology;    confidence intervals;    sensor fusion;   

DOI  :  10.3390/s100908028

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2010 by the authors; licensee MDPI, Basel, Switzerland.