We are currently experiencing intermittent issues impacting performance. We apologize for the inconvenience.
By Topic

Automatic face classifications by self-organization for face recognition

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Sato, Y. ; Graduate Sch. of Syst. & Inf. Eng., Tsukuba Univ., Japan ; Yoda, I. ; Sakaue, K.

We propose a method of face recognition that can consistently identify every face angle, assuming it is used in open spaces such as a normal room. We obtain the learning images not from an ideal world but from the real world, where users can move around freely with no constraints. We then automatically classify the face images that vary according to the user's position and posture by self-organization (unsupervised learning), and create a discrimination circuit using only the best face images for the recognition task. We show that the recognition rate for images with various facial angles in the real world can be improved by automatic classification through self-organization.

Published in:

Analysis and Modeling of Faces and Gestures, 2003. AMFG 2003. IEEE International Workshop on

Date of Conference:

17 Oct. 2003