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.
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Lietz, H., Thomanek, J., Fardi, B., Wanielik, G. (2009). Improvement of the Classifier Performance of a Pedestrian Detection System by Pixel-Based Data Fusion. In: Serra, R., Cucchiara, R. (eds) AI*IA 2009: Emergent Perspectives in Artificial Intelligence. AI*IA 2009. Lecture Notes in Computer Science(), vol 5883. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10291-2_13
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DOI: https://doi.org/10.1007/978-3-642-10291-2_13
Publisher Name: Springer, Berlin, Heidelberg
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