An Intelligent Real-Time Multiple Moving Object Tracker

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Abstract
An intelligent real-time multiple moving object tracker is introduced. It consists of five main functional units: a multi-mode object detector, a detection confidence measure, a multi-state intelligent tracking controller, a clutter filter, and an intelligent predictor. The object detector exploits correlation, motion, and contrast detection modes cooperatively, and operates at multiple image resolutions. The detection confidence measure is used to combine dynamically the measured and predicted attributes of current tracked objects. To control and maintain good tracking, each tracking step is assigned one of eight possible tracking states, with associated strategies for intelligent detection, matching and prediction. The clutter filter uses a stored database of interesting objects to reject clutter selectively during stable tracking, based on both feature and motion history. The intelligent predictor predicts the tracking state, tracked object attributes and background properties expected in the next tracking step. This tracking scheme incorporates knowledge and control not exploited by conventional Kalman filter based trackers. We demonstrate its performance in detecting and accurately tracking dynamic targets from FLIR image sequences.

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