Face detection based on eye location and AdaBoost Gabor filter
Yang Ding-l · Jisuanji yingyong yanjiu · 2014
Face detection rate is always affected by illumination. However the Gabor wavelet has good biological visual characteristic,and it is insensitive to illumination. In addition,if the position of the face was relatively fixed in images,the ability of the classifiers would be enhanced when classifiers were trained with Adaboost method. In order to increase the face detection rate when face image was affected by illumination,this paper proposed the new face detection method based on the human eye location and AdaBoost Gabor filter. Firstly,it determined eye region with AdaBoost method,Hough transform and direct least squares method. Secondly,it located the pupil and eyelid of the eye. Then,it obtained face region according to the knowledge of the face that its width was five eyes and its high was three court. Finally,it determined face with the cascade strong classifiers which were trained by AdaBoost Gabor filter algorithm. Experiments are executed in Yale,CMU Frontal Face database,and so on. Experiments show that not only false alarm rate with this method is lower,but also face detection rate is higher than other methods.