Real-time pedestrian detection is a key technology for video surveillance. A widespread approach for detecting pedestrians is the use of color information. In recent times, the use of thermal infrared cameras has revealed to be an excellent alternative that offers good results in people segmentation. Nonetheless, thermal infrared cameras are very sensitive to the overall heat detected at each image. Moreover, a great amount of infrared images has low spatial resolution and lower sensitivity than visible spectrum images due to the technological limitations of infrared cameras. This chapter introduces a comparison of three different algorithms for real-time and robust pedestrian detection in the infrared spectrum. The aim of the paper is to look for the best algorithms prepared to resolve the conflicts that arise in the detection process in image sequences. We propose to use simple rules as conflict resolution mechanism when the outputs of the three algorithms do not coincide.
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