The primary goal of this study is to track a ground-moving target using a machine-vision system installed on an unmanned helicopter, and to estimate its position if the target becomes unobservable. The machine-vision system is accomplished using real-time color images obtained from a charge-coupled device (CCD) camera mounted on a computer-controlled gimbaled system that can pitch and yaw. To avoid real-time image-tracking failure resulting from a moving target becoming concealed, the Kalman filtering technique is applied to predict the target's follow-on position, so that the camera can continuously track the target. The entire system is initially tested on the ground and then mounted on a helicopter for in-flight testing. The following three cases are shown in the flight tests: (1) an uncovered static target; (2) a moving visible target; and (3) a target that moves in a straight line at a constant speed and becomes temporarily concealed. The vision-based tracking system with the developed algorithm is successfully applied in all three cases.