LIDAR and vision-based pedestrian detection system

Authors:
Cristiano Premebida;Oswaldo Ludwig;Urbano Nunes
Affiliations:
Institute for Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, Coimbra 3030-290, Portugal;Institute for Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, Coimbra 3030-290, Portugal;Institute for Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, Coimbra 3030-290, Portugal
Venue:
Journal of Field Robotics
Year:
2009

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Abstract

A perception system for pedestrian detection in urban scenarios using information from a LIDAR and a single camera is presented. Two sensor fusion architectures are described, a centralized and a decentralized one. In the former, the fusion process occurs at the feature level, i.e., features from LIDAR and vision spaces are combined in a single vector for posterior classification using a single classifier. In the latter, two classifiers are employed, one per sensor-feature space, which were offline selected based on information theory and fused by a trainable fusion method applied over the likelihoods provided by the component classifiers. The proposed schemes for sensor combination, and more specifically the trainable fusion method, lead to enhanced detection performance and, in addition, maintenance of false-alarms under tolerable values in comparison with single-based classifiers. Experimental results highlight the performance and effectiveness of the proposed pedestrian detection system and the related sensor data combination strategies. © 2009 Wiley Periodicals, Inc.