This paper proposes a new method for automatic identification of human faces. This identification method uses a facial three‐dimensional (3‐D) shape that is extracted from an absolute range map. The important issue is to determine what to use as feature vector components for the identification of 3‐D objects. There have been several approaches to identify 3‐D objects, but in the identification of objects that have smooth and complex shape (such as a human face) such approaches did not use the whole feature included in an object, or a long time was required for the identification because of the large number of feature vector components needed. To solve these problems, an approximation of a facial surface with a B‐spline surface was made by least‐square fitting, and the vertices of the B‐spline surface were used as feature vector components for the identification. Since this process condenses the whole feature included in a surface into a small number of points (vertices), features can be used efficiently for the identification. By this method, identification accuracy of 98.8 percent is obtained for 33 persons (5 data/person).
ASJC Scopus subject areas
- Theoretical Computer Science
- Information Systems
- Hardware and Architecture
- Computational Theory and Mathematics