Robust posture estimation of human face in some bad conditions

In recent years much research concerned with biometrics, using parts of the human body, have been reported. The human face is most widely used in daily life for personal identification. Information obtained from the human face shows the person´s authentication and intentions, and thus the human face is an important site. Especially the direction of a face is used to measure the interest of a candidate person, or the compensation process of personal authentication. Posture estimation mostly by the conventional technique had only used a 2-dimensional (2-D) picture, or only used 3-dimensional (3-D) data. However, there was a problem. The posture estimation at a fine angle was inaccurate for posture estimation when only using the 2-D picture and in posture estimation have to use a special movie camera only using the 3-D data. Moreover, the result may differ from the user intention because of inaccurate estimations when only using 2-D or 3-D data. The problems with only using 2-D pictures are that posture direction cannot be estimated because the lighting conditions are bad and the angles (facial directions), which can be estimated, are limited. And the problems with only using 3-D data is that it sometimes cannot adapt to rapidly changing image. This paper is a highly accurate, handy technique by estimating posture for 2-D picture using previously stored feature extraction 3-D reference picture. The rotation angle to be calculated can be decreased by using the forecast processing. Therefore, the posture estimation processing is accelerated. The feature of this technique is performing posture estimation with robust accuracy to an unfavorable condition. The bad condition of targeting by this technique is adaptable for spectacles, the dirt on lens, out of focus lens, and lighting changes