Area-correlation tracker with improved reliability

Computer Science – Performance

Scientific paper

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Scientific paper

Area correlation tracking is an effective method of tracking targets or a scene of interest that do not have prominent features or high contrast with respect to the background. The essential step in area correlation tracking is to find the 'best fit' of a target/area reference image in a real- time search image acquired by the imaging sensor. The solutions for these are broadly classified as template and feature level matching algorithms. Various algorithms reported in the open literature have different degrees of performance under different field conditions. For certain autonomous tracking applications where there is relative motion between the sensor and the scene/target, it is essential to continuously register a part of previous scene in the next frame. When the reference is thus updated for each frame, there is a possibility that the system may become divergent, if mis-registration is not detected. A correct registration omitted as a wrong registration is tolerable, but a mis-registration committed as a correct registration is a catastrophe. In view of this, it is essential to improve the reliability of registration, and take a confidence measure whenever it is in doubt. This paper addresses that issue and proposes a scheme to improve the performance of area correlation trackers.

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