Toward a sensor-based threat warning system for patrols in MOUT scenarios

Military Operations in Urban Terrain (MOUT) require the capability to perceive and to analyse the situation around a patrol in order to recognize potential threats. Human operators can only observe a limited field of regard. Sensors can enhance the field of regard up to 360°, but then the amount of data cannot be fully exploited by a human operator any more. For this reason an intelligent assistance system is required that monitors the circumference of a moving platform and warns the driver of a threatening situation. One first processing step of such a system is the recognition of humans. There are numerous approaches to the detection of humans, mainly from stationary cameras. Moving cameras play a role in the field of pedestrian protection from a moving road vehicle. There are two principal differences to this latter application domain. Firstly, the threat in a MOUT scenario potentially arises from humans in the scene. Secondly, not only the trajectories of individual humans are relevant, but also the motion and the behavior of groups of humans. As a first step towards an assistance system that automatically warns drivers in a MOUT scenario, we implemented an approach to the detection of humans in video images and applied them to a relevant set of image sequences taken in a MOUT scenario. In the paper we assess the obtained results and outline further research activities.