Technology Of Face And Facial Pose Detection In Digital Image

Research efforts in face processing include face detection, face tracking, face recognition as well as derivative analysis of pose and expression. Face detection is a key technology of the filed of face information processing. In the beginning, research efforts in face processing chiefly fastened its attention on face recognition, and early face recognition algorithms are based on having a frontal face or faces'getting easily. But with faces'application spreading and practical systems'demand improving, this kind of research on this condition can't satisfy requirements any more. Face detection develops as an alone research.This paper mainly researches in the dynamic face detection and the face pose detection. To achieve the purpose that in dynamic context detect the position of face, and from all poses of faces find the most positive face to use in the face identification. That can improve the veracity in face identification.In this dissertation, we first sum up and analyze current typical algorithms on face detection, and then present a multistage detection and conformed method from coarse to fine in order to find faces in the complicated background. This method is discussed on details as follows. First, the algorithm analyzes and compares complexion's clustering in the different color space, and then establishes a skin model based on the color space of YCbCr. Using this model, the complexion is segmented and two-value processed. On account of noise's immanence, we can get backup face area using the filter based on mathematical morphology. In the selective and conformed stage,we utilize faces'geometrical characters to roughly choose between these backup areas. Finally we use Euler number and fair model to repeatedly choose and verify these regions,and to get the end results.The determinacy of face pose is based on the eyes and the mouth areas which are detected by the method based on the color space of YCbCr . Then ,delete the false area,find the middle of eyes and mouth area. The three points joint into a triangle. When the triangle meets some rules which makes face pose positive, save that picture as the result.In the last part of the dissertation ,we implement the algorithm using Visual C++. In the case of that the lab is steady ,the parameter of the system is proper, the camera is still and in the perfect place, experimental results show that the method is effective in many conditions including many faces'different scales and complex background. But due to face's complexity by itself ,there are some missing faces and false faces. The system is practical to a certain extent.