Track Estimation of Multiple Targets from Bearing Sensor Data by Cooperative Processing

Track estimation of targets from sensor data is a crucial issue in active dynamic scene understanding. Multitarget motion analysis, where there are multiple moving targets and multiple xed sensors which only measure bearings of the targets, is to associate targets and sensor data, and estimate target tracks based on that association. This is an NPhard problem in general, and solved using stepwise relaxation. However, it is hard to obtain the optimal solution, as the method easily gets trapped in one of local optima. We applied the decentralized cooperative search technique to this problem, and proved our method e ective. The method uses more than one processors, each of which has its own partial search space, searching multiple possibilities in parallel. This approach leads to cooperative distributed vision. We are currently extending our method to address the case where targets move toward varying directions and in varying velocities. This report shows the current status of our research, and presents two prototypes of cooperative multiagent systems for \extended" multitarget motion analysis.