Automatic generation of optimum classification cascades
Ezzat El‐Sherif, Sherif Abdelazeem, M.F. Abu El-Yazeed · 2008
In this paper, we present a novel technique to automatically generate optimum classification cascades. Given a powerful classifier SFwith satisfactory accuracy and a set of N classifiers, our algorithm builds the fastest cascade that achieves an accuracy not less than that of SF. The algorithm is fully automatic and has a complexity of O(N2) which means it is fast and scalable to large values of N.