The objective of the CyberScout project is to develop an autonomous surveillance and reconnaissance system using a network of all-terrain vehicles. In this paper, we focus on two facets of this system: 1) vision for surveillance and 2) autonomous navigation and dynamic path planning. In the area of vision-based surveillance, we have developed robust, efficient algorithms to detect, classify, and track moving objects of interest (person, people, or vehicle) with a static camera. Adaptation through feedback from the classifier and tracker allow the detector to use grayscale imagery, but perform as well as prior color-based detectors. We have extended the detector using scene mosaicing to detect and index moving objects when the camera is panning or tilting. The classification algorithm performs well (less than 8% error rate for all classes) with coarse inputs (20x20-pixel binary image chips), has unparalleled rejection capabilities (rejects 72% of spurious detections), and can flag novel...
Mahesh Saptharishi, C. Spence Oliver, Christopher