Combining camera systems for human shape detection

The detection of pedestrians is an important field of research for commercial, governmental, and military organizations. In particular, the US Army is actively developing obstacle detection for multifunction utility/logistics equipment (MULE) vehicle operations, path following, and intent-based anti-tamper surveillance systems. This article introduces a new optical system for the detection of human shapes from unmanned MULE vehicles on the move. Locating people against background noise can be a challenging task. For example, pedestrians can assume different poses, wear different clothes, and carry objects that obscure the distinctive human silhouette. These problems are further compounded by camera movements and different lighting conditions in uncontrolled outdoor environments. To tackle this task, a number of monocular and stereo optical systems have been developed that use visible light (daylight cameras) or far infrared (FIR) wavelengths (7–14μm). In many scenarios, FIR cameras (often called ‘thermal’ cameras) are well suited to initial detection. In other situations, such as sunny and hot environments, targets are harder to pick out from the background, and daylight cameras are a better choice. In addition, daylight cameras provide more detailed images and offer more reliable target verification. The simultaneous use of two stereo camera systems, one based on visible light (daylight) and the other on FIR wavelengths, have therefore been investigated to exploit the benefits of both technologies.