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The tracking of humans in a video stream has become one of the most desirable computer vision tasks over the past few years. It remains however a difficult problem and the reliability of systems is often dependent on getting good lighting and clear video images. This paper reports on the development of our PHACT tracker: parallel HOG and correlation tracking. This system uses a cascade of tracking algorithms that enhances the reliability and robustness of the system as a whole when used in difficult conditions.

Human tracking with multiple parallel metrics