Real-time Cooperative Multi-target Tracking
by Dense Communication among Active Vision Agents
We have proposed a real-time multi-target tracking system by cooperative behaviors of Active Vision Agents (AVAs), where an AVA is a logical model of a network-connected computer with an active camera. All AVAs change their roles adaptively by negotiating with each other. The previous system, however, was unable to simultaneously track target objects that are greater in number than the AVAs. In this paper, we realize the increase in number of simultaneously trackable objects by improving cooperative tracking protocols so that AVAs exchange a large amount of information with each other without increasing network traffic. This system enables the increase of trackable objects by (1) an AVA that provides information of observed objects for several agencies (i.e., a group of AVAs that track the same target) and (2) a vacant-agency that receives information of its target from AVAs tracking other objects. Experimental results demonstrate that our system can track multiple targets (greater in number than the cameras) simultaneously and robustly in real time.