A Novel Approach of Eye Detection Based on Haar-Like Feature and SVM
Recognizing the importance of eye detection technology in face detection and recognition, facial expression recognition, driver fatigue detection, and so on, the current paper presents a novel approach to eye detection in images based on AdaBoost and the Support Vector Machine (SVM). The proposed method can accurately detect eyes with different postures, facial expressions, skin colors, and glasses in a simple background image. First, a Haar-like feature AdaBoost classifier based on the developed training samples is used to detect eyes in images. An SVM post classifier trained by coordinates of the true and pseudo eye rectangles is then used to optimize the results. Experimental results show that the proposed method is fast, robust, and has high generalization capability.
Dongye Sun, Wen-Pei Sung and Ran Chen
Y. H. Guo and J. Liu, "A Novel Approach of Eye Detection Based on Haar-Like Feature and SVM", Applied Mechanics and Materials, Vols. 121-126, pp. 1863-1867, 2012