Abstract
In this paper, we present an automated face recognition (AFR) system that contains two components: eye detection and face recognition. Based on invariant radial basis function (IRBF) networks and knowledge rules of facial topology, a hybrid neural method is proposed to localize human eyes and segment the face region from a scene. A dual eigenspaces method (DEM) is then developed to extract algebraic features of the face and perform the recognition task with a two-layer minimum distance classifier. Experimental results illustrate that the proposed system is effective and robust.
| Original language | English |
|---|---|
| Pages (from-to) | 787-793 |
| Number of pages | 7 |
| Journal | IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans |
| Volume | 32 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 1 Nov 2002 |
Keywords
- Dual eigenspaces method
- Eyes detection
- Face recognition
- Hybrid neural method
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Human-Computer Interaction
- Computer Science Applications
- Electrical and Electronic Engineering
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