Multi-Agent Real-Time 3d Tracking In Robot Vision

In this paper, we present a real-time 3D FeatureBased Tracker (3DFBT): a robot vision system for tracking and segmenting the 3D motion of objects using image input from a calibrated stereo pair of video cameras. After an initialization step (in which the cameras are calibrated and interest-point features are extracted), the system runs in a multi-level cycle of prediction and verification or correction. The currently modelled 3D positions and velocities of the feature points are extrapolated a short time into the future to yield predictions of 3D position. These 3D predictions are projected into the two stereo views, and are used to guide a fast and highly focused visual search for the feature points. The image positions at which the features are re-acquired are backprojected in 3D space in order to update the 3D positions and velocities. At a higher level, features are dynamically grouped into clusters with common 3D motion. Predictions from the cluster level can be fed to the lower l..