Face Recognition without Features

We have developed a near-real-time computer system which can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals. Our approach treats the face recognition problem as an intrinsically twodimensional recognition problem, taking advantage of the fact that faces are are normally upright and thus may be described by a small set of 2-D characteristic views. The system functions by projecting face images onto a feature space that spans the significant variations among known face images. The significant features are known as "eigenfaces", because they are the eigenvectors (principal componmt,s) of the set of faces; they do not necessarily correspontl to features such as eyes, ears, and noses.

• Type: Conference
• Year: 1990
• Where: MVA
• Authors: Matthew Turk, Alex Pentland
• Keywords: Face Images, Face Recognition Problem, MVA 1990, MVA 2007, Recognition Problem