We show how feature selection mechanisms can be successfully employed for ranking the features used by a tracking system, maintaining high frame rates. In particular, feature selection mounted on the Adaptive Color Tracking (ACT) system operates at over 110 FPS. This work demonstrates the importance of feature selection in online and realtime applications, resulted in what is clearly a very impressive performance, our solutions improve by 3% up to 7% the baseline ACT while providing superior results compared to 29 state-of-the-art tracking methods.
Giorgio (2020). Online Feature Selection for Visual Tracking (https://www.mathworks.com/matlabcentral/fileexchange/66876-online-feature-selection-for-visual-tracking), MATLAB Central File Exchange. Retrieved .
Inspired by: Feature Selection Library
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