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Visual Object Tracking using Adaptive Correlation Filters

Visual Object Tracking using Adaptive Correlation FiltersDavid S. Bolme J. Ross Beveridge Bruce A. Draper Yui Man LuiComputer Science DepartmentColorado State UniversityFort Collins, CO 80521, not commonly used, Correlation Filters can trackcomplex objects through rotations, occlusions and otherdistractions at over 20 times the rate of current state-of-the-art techniques. The oldest and simplest correlationfilters use simple templates and generally fail when ap-plied to Tracking . More modern approaches such as ASEFand UMACE perform better, but their training needs arepoorly suited to Tracking . Visual Tracking requires robustfilters to be trained from a single frame and dynamicallyadapted as the appearance of the target Object paper presents a new type of Correlation filter, aMinimum Output Sum of Squared Error (MOSSE) filter,which produces stable Correlation Filters when initializedusing a single frame.

tracking. 3 CorrelationFilterBasedTracking Filter based trackers model the appearance of objects us-ing filters trained on example images. The target is ini-tially selected based on a small tracking window cen-tered on the object in the first frame. From this point on, tracking and filter training work together. The target is

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  Tracking, Object, Object tracking

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