Incremental focus of attention for robust vision-based tracking

We present the Incremental Focus of Attention (IFA) architecture for robust , adaptive, real-time motion tracking. IFA systems combine several visual s earch and vision-based tracking algorithms into a layered hierarchy. The ar chitecture controls the transitions between layers and executes algorithms appropriate to the visual environment at hand: When conditions are good, tr acking is accurate and precise; as conditions deteriorate, more robust, yet less accurate algorithms take over; when tracking is lost altogether, laye rs cooperate to perform a rapid search for the target and continue tracking . Implemented IFA systems are extremely robust to most common types of tempor ary visual disturbances. They resist minor visual perturbances and recover quickly after full occlusions, illumination changes, major distractions, an d target disappearances. Analysis of the algorithm's recovery times are sup ported by simulation results and experiments on real data. In particular, e xamples show that recovery times after lost tracking depend primarily on th e number of objects visually similar to the target in the field of view.