3D Target Tracking Using Multiple Calibrated Cameras

We present the architecture of a system for tracking multiple targets, using multiple cameras with possibly overlapping fields of views, to determine the 3D location and orientation of the targets. A separate tracker is assigned to each new target. That tracker uses the information provided by 2D pattern matchers about the location of the target in the cameras´ video streams to update its estimate of the target´s 3D state. An extended Kalman filter (EKF) is used to maintain each target´s 3D state. New targets are detected by employing an adaptive background subtraction algorithm. We present examples of results of our tracker for outdoor scenes.