Pedestrian Detection in Infrared Image Sequences Using SVM and Histogram Classifiers

In dark environments and foggy or smoky conditions where it is not possible to use eyesight and usual binoculars to detect human from other objects, the best solution is to use infrared images. This paper presents a robust method to recognize pedestrians in infrared image sequences. For this purpose, combination of SVM and histogram classifiers has been used. A pre-processing phase extracts image patterns similar to human patterns and delivers them to histogram and SVM classifiers. For training and testing phases of the presented algorithm thermal data base of OSU pedestrian video sequences has been utilized. Results of the algorithm present its good accuracy and performance.