Human-face search and location in a scene by multi-pyramid architecture for personal identification

To realize fully automated face image recognition, there must be thorough processing from the detection of the face in a scene to recognition. It is very difficult, however, to apply the detection or recognition process based on the shape features as in the conventional method to the face which is a typical soft object. This paper aims at personal identification by the facial image. The face in a scene is sought by coarse-to-fine processing using only the gray-level data, and the result is applied to the recognition. First, the human head is detected from the scene using the multiresolution mosaic. Then the central part of the face is detected from the head region using the mosaic, and the precise position is determined based on the histogram for the eye and the nose region. The search algorithm is applied to 100 personal images derived from the motion image. The detection and location succeeded in 97 percent of the cases, except for the face with eyes shielded by hair, for example. When the result of successful detection is applied to the recognition, the recognition rate of 99 percent is obtained. In this method, a facial image of any size at any position in a scene can be detected. Other features are that the background can be uniform, and the color data are not required, which greatly relaxes the past requirement for the input image.