Matching pursuit filters applied to face identification

An algorithm has been developed for the automatic identification of human faces. Because the algorithm uses facial features restricted to the nose and eye regions of the face, it is robust to variations in facial expression, hair style and the surrounding environment. The algorithm uses coarse to fine processing to estimate the location of a small set of key facial features. Based on the hypothesized locations of the facial features, the identification module searches the database for the identity of the unknown face. The identification is made by matching pursuit filters. Matching pursuit filters have the advantage that they can be designed to find the differences between facial features needed to identify unknown individuals. The algorithm is demonstrated on a database of 172 individuals.