Glasses detection by boosting simple wavelet features
Bo Wu, Haizhou Ai, Ran Liu · 2004
In this paper we propose a novel method for glasses detection. The glasses detectors are learned by using a variation of boosting algorithm, called real Adaboost [1], to boost simple wavelet feature based Look-Up-Table type weak classifiers. Two types of wavelet features, Haar and Gabor, have been investigated. Experiments results are reported to show that our method has very high correctness and extremely fast running speed. Based on this method we have developed a glasses detection system which can detect the glasses in facial images automatically.