Research On The Technology Of Human Head, Face, Eyes, Mouth Detection Based On Boosting Algorithm

In this thesis, we study the human head, face, eyes and mouth detection based on Boosting algorithm. Nowadays, in the field of the image interface between human and machine, research consists of face recognition, pose estimation and etc. The detection of human head, face, eyes and mouth is a hot topic and deserve the attention of researchers.We study the methods of human head, face, eyes and mouth detection at state of arts, classify all the methods for the first time, and analyze the merits and deficiency of all these methods. We introduce the approaches of head, face, eyes and mouth detection based on the AdaBoost algorithm. There exists numbers of researchers who have performed face detection based on AdaBoost, we extend the approach to head, face, eyes and mouth detection. We perform experiments on real images and analyze the results. We design the flow chart of the experiments, train the Boosting classifiers of the head, face, eyes and mouth detection. Experimental results demonstrate the good performance of our methods. The experimental results show the robustness of the AdaBoost method, and it maintains the real-time requirement.