Real-time infrared pedestrian detection based on multi-block LBP

This paper presents a real-time infrared pedestrian detection algorithm based on multi-block LBP features. Local pattern feature has been successfully used in many computer vision applications. However, to our best knowledge, it has not been utilized for pedestrian detection in infrared imagery. We exploit the discriminative power and computational simplicity of local pattern features for real-time infrared pedestrian detection. The proposed approach has been implemented on an experimental vehicle equipped with a forward-looking infrared (FLIR) camera. Experimental results under different urban street scenarios prove that our method is robust and efficient.