LIDAR and vision-based pedestrian detection system
Article first published online: 1 SEP 2009
Copyright © 2009 Wiley Periodicals, Inc.
Journal of Field Robotics
Volume 26, Issue 9, pages 696–711, September 2009
How to Cite
Premebida, C., Ludwig, O. and Nunes, U. (2009), LIDAR and vision-based pedestrian detection system. J. Field Robotics, 26: 696–711. doi: 10.1002/rob.20312
- Issue published online: 1 SEP 2009
- Article first published online: 1 SEP 2009
- Manuscript Accepted: 30 JUL 2009
- Manuscript Received: 11 SEP 2008
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.