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The goal of the sponsored research was to develop face recognition algorithms. The FERET database was collected to support the sponsored research and the FERET evaluations. The FERET evaluations were performed to measure progress in algorithm development and identify future research directions.


Department of Defense (DoD) Counterdrug Technology Development Program Office sponsored the Face Recognition Technology (FERET) program. The goal of the FERET program was to develop automatic face recognition capabilities that could be employed to assist security, intelligence, and law enforcement personnel in the performance of their duties. The program consisted of three major elements:

  • Sponsoring research
  • Collecting the FERET database
  • Performing the FERET evaluations

The goal of the sponsored research was to develop face recognition algorithms. The FERET database was collected to support the sponsored research and the FERET evaluations. The FERET evaluations were performed to measure progress in algorithm development and identify future research directions.

The FERET program started in September of 1993, with Dr. P. Jonathon Phillips, Army Research Laboratory, Adelphi, Maryland, serving as technical agent. Initially, the FERET program consisted of three phases, each one year in length. The goals of the first phase were to establish the viability of automatic face recognition algorithms and to establish a performance baseline against which to measure future progress. The goals of phases 2 and 3 were to further develop face recognition technology. After the successful conclusion of phase 2, the DoD Counterdrug Technology Development Program Office initiated the FERET demonstration effort. The goals of this effort were to port FERET evaluated algorithms to real-time experimental/demonstration systems.

FERET-Sponsored Algorithm Development Research

The FERET program was initiated with a broad agency announcement (BAA). Twenty-four proposals were received and evaluated jointly by DoD and law enforcement personnel. The winning proposals were chosen based on their advanced ideas and differing approaches. Five algorithm development contracts were awarded. The organizations and principle investigators selected were:

  • Massachusetts Institute of Technology (MIT), Alex Pentland
  • Rutgers University, Joseph Wilder
  • The Analytic Science Company (TASC), Gale Gordon
  • University of Illinois at Chicago (UIC) and University of Illinois at Urbana-Champagne, Lewis Sadler and Thomas Huang
  • University of Southern California (USC), Christoph von der Malsburg

For phase 2, MIT, TASC, and USC were selected to continue development of their algorithms. The MIT and USC teams continued work on developing face recognition algorithms from still images. The TASC effort extended their approach to developing an algorithm for recognizing faces from video. The emphasis of the TASC effort was to estimate the three-dimensional shape of a face from motion and then recognize a face based on its shape. Rutgers' Phase 2 effort compared and assessed the relative merits of long-wave infrared (thermal) and visible imagery for face recognition and detection. The results of this study were presented in the paper "Comparison of visible and infrared imagery for face recognition" by J. Wilder, P. J. Phillips, C. Jiang, and S. Wiener in Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, pages 182-187, 1996.

The FERET Database

 standard database of face imagery was essential to the success of the FERET program, both to supply standard imagery to the algorithm developers and to supply a sufficient number of images to allow testing of these algorithms. Before the start of the FERET program, there was no way to accurately evaluate or compare facial recognition algorithms. Various researchers collected their own databases for the problems they were investigating. Most of the databases were small and consisted of images of less than 50 individuals. Notable exceptions were databases collected by three primary researchers:

  • Alex Pentland of the Massachusetts Institute of Technology (MIT) assembled a database of ~7500 images that had been collected in a highly controlled environment with controlled illumination; all images had the eyes in a registered location, and all images were full frontal face views.
  • Joseph Wilder of Rutgers University assembled a database of ~250 individuals collected under similarly controlled conditions.
  • Christoph von der Malsburg of the University of Southern California (USC) and colleagues used a database of ~100 images that were of controlled size and illumination but did include some head rotation.

The FERET program set out to establish a large database of facial images that was gathered independently from the algorithm developers. Dr. Harry Wechsler at George Mason University was selected to direct the collection of this database. The database collection was a collaborative effort between Dr. Wechsler and Dr. Phillips. The images were collected in a semi-controlled environment. To maintain a degree of consistency throughout the database, the same physical setup was used in each photography session. Because the equipment had to be reassembled for each session, there was some minor variation in images collected on different dates.

The FERET database was collected in 15 sessions between August 1993 and July 1996. The database contains 1564 sets of images for a total of 14,126 images that includes 1199 individuals and 365 duplicate sets of images. A duplicate set is a second set of images of a person already in the database and was usually taken on a different day.

For some individuals, over two years had elapsed between their first and last sittings, with some subjects being photographed multiple times. This time lapse was important because it enabled researchers to study, for the first time, changes in a subject's appearance that occur over a year.

to read the rest of the article please visit  https://www.nist.gov .