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Perceiving the environment is crucial in any application related to mobile robotics research. In this paper, a new approach to real-time human detection through processing video captured by a thermal infrared camera mounted on the autonomous mobile platform mSecurit^T^M is introduced. The approach starts with a phase of static analysis for the detection of human candidates through some classical image processing techniques such as image normalization and thresholding. Then, the proposal starts a dynamic image analysis phase based in optical flow or image difference. Optical flow is used when the robot is moving, whilst image difference is the preferred method when the mobile platform is still. The results of both phases are compared to enhance the human segmentation by infrared camera. Indeed, optical flow or image difference will emphasize the foreground hot spot areas obtained at the initial human candidates' detection.