Robust classifier based two-layer Adaboost for precise eye location
双层结构Adaboost健壮分类器用于人眼精确定位

A two-layer eye classifier for eye detection was proposed. Two layers, double-eye layer and single-eye layer, had been trained and cascaded into a strong one for eye detection. Two-layer classifier was more robust in illumination invariance eye detection compared with YCbCr space eye map algorithm. Also, it kept the same detection rate as the commonly trained Adaboost eye classifier with a much lower error detection rate. Relationship among stages, training sample number and error detection rate had been analyzed to facilitate the training procedure.