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Incremental Focus of Attention for Robust Vision-Based Tracking
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Incremental Focus of Attention for Robust Vision-Based Tracking Kentaro Toyama1 and Gregory D. Hager2  | (1) | Microsoft Research, One Microsoft Way, Redmond, WA, 98052-6399 |
| (2) | Department of Computer Science, The Johns Hopkins University, Baltimore, Maryland, 21218-2694 |
Abstract We present the Incremental Focus of Attention (IFA) architecture for robust, adaptive, real-time motion tracking. IFA systems combine several visual search and vision-based tracking algorithms into a layered hierarchy. The architecture controls the transitions between layers and executes algorithms appropriate to the visual environment at hand: When conditions are good, tracking is accurate and precise; as conditions deteriorate, more robust, yet less accurate algorithms take over; when tracking is lost altogether, layers cooperate to perform a rapid search for the target and continue tracking. Implemented IFA systems are extremely robust to most common types of temporary visual disturbances. They resist minor visual perturbances and recover quickly after full occlusions, illumination changes, major distractions, and target disappearances. Analysis of the algorithm's recovery times are supported by simulation results and experiments on real data. In particular, examples show that recovery times after lost tracking depend primarily on the number of objects visually similar to the target in the field of view. visual tracking - real-time tracking - robust tracking - face tracking
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