Share Email Print

Proceedings Paper

Face recognition using the neural tree network
Author(s): Joseph Wilder; S. Juth; Augustine Tsai; X. Y. Zhang
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

A face recognition system has been developed and demonstrated at the Rutgers University Center for Computer Aids for Industrial Productivity. The system uses a preliminary data reduction step. gray scale projections, and a fast transform technique to greatly reduce the computational complexity of the problem and, consequently, the cost of high-speed implementation. The decision function is a few, extremely cost-effective neural network, the Mammone/Sankar Neural Tree Network. This network can be trained and re-trained rapidly on face image data and the system has built-in facilities for acquiring and editing a large data base of face images. Recognition rates higher than 90% were achieved on data sets containing up to 269 subjects. More importantly, it performed well on subjects with and without their glasses, under a wide range of changes in facial expressions, and under a variety of small tilts, translations and rotations.

Paper Details

Date Published: 1 February 1994
PDF: 8 pages
Proc. SPIE 2093, Substance Identification Analytics, (1 February 1994);
Show Author Affiliations
Joseph Wilder, Rutgers Univ. (United States)
S. Juth, Rutgers Univ. (United States)
Augustine Tsai, Rutgers Univ. (United States)
X. Y. Zhang, Rutgers Univ. (United States)

Published in SPIE Proceedings Vol. 2093:
Substance Identification Analytics
James L. Flanagan; Richard J. Mammone; Albert E. Brandenstein; Edward Roy Pike M.D.; Stelios C. A. Thomopoulos; Marie-Paule Boyer; H. K. Huang; Osman M. Ratib, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?