Transcription of Visual Object Tracking using Adaptive Correlation Filters
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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.
speed and simplicity of the underlying correlation based approach. Despite the simplicity of the approach, tracking based on modified ASEF, UMACE, or MOSSE filters performs well under changes in rotation, scale, lighting, and par-tial occlusion (See Figure 1). The Peak-to-Sidelobe Ratio (PSR), which measures the strength of a correlation peak,
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