Improvement of the Classifier Performance of a Pedestrian Detection System by Pixel-Based Data Fusion

Authors:
Holger Lietz;Jan Thomanek;Basel Fardi;Gerd Wanielik
Affiliations:
Chemnitz University of Technology, Chemnitz, Germany 09126;Chemnitz University of Technology, Chemnitz, Germany 09126;Chemnitz University of Technology, Chemnitz, Germany 09126;Chemnitz University of Technology, Chemnitz, Germany 09126
Venue:
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
Year:
2009

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Abstract

This contribution presents an approach how to improve the classifier performance of an existing pedestrian detection system by using pixel-based data fusion of FIR and NIR sensors. The advantage of the proposed method is that the fused images are more suitable for the subsequent feature extraction. Both, the algorithm of the pedestrian detection system and the used pixel-based fusion techniques, are presented. Experimental results show that the detection performance based on a fused image sequence outperforms a detector that is based on just a single sensor.