Distant targets identification as an on-line dynamic vehicle routing problem using an active-zooming camera
This paper considers the problem of modeling an active observer to plan a sequence of decisions regarding what target to look at, through a foveal-sensing action. The gathered images by the active observer provides meaningful identification imagery of distant targets which are not recognizable in a wide angle view. We propose a framework in which a pan/tilt/zoom (PTZ) camera schedules saccades in order to acquire high resolution images of as many moving targets as possible before they leave the scene. We cast the whole problem as a particular kind of dynamic discrete optimization, specially as a novel on-line dynamic vehicle routing problem (DVRP) with deadlines. We show that using an optimal choice for the sensing order of targets the total time spent in visiting the targets by the active camera can be significantly reduced. To show the effectiveness of our approach we apply congestion analysis to a dual camera system in a master-slave configuration. We report that our framework gives good results in monitoring wide areas with little extra costs with respect to approaches using a large number of cameras.