Title
Automatic extraction of eye and mouth fields from a face image using eigenfeatures and multilayer perceptrons
Abstract
This paper presents a novel algorithm for the extraction of the eye and mouth (facial features) fields from 2-D gray-level face images. The fundamental philosophy is that eigenfeatures, derived from the eigenvalues and eigenvectors of the binary edge data set constructed from the eye and mouth fields, are very good features to locate these fields efficiently. The eigenfeatures extracted from the positive and negative training samples of the facial features are used to train a multilayer perceptron whose output indicates the degree to which a particular image window contains an eye or a mouth. It turns out that only a small number of frontal faces are sufficient to train the networks. Furthermore, they lend themselves to good generalization to non-frontal pose and even other people's faces. It has been experimentally verified that the proposed algorithm is robust against facial size and slight variations of pose.
Year
DOI
Venue
2001
10.1016/S0031-3203(00)00173-4
Pattern Recognition
Keywords
Field
DocType
Facial feature,Eye and mouth fields,Eigenfeature,Multilayer perceptron,Positive (Negative) sample
Computer vision,Pattern recognition,Computer science,Multilayer perceptron,Artificial intelligence,Perceptron,Eigenvalues and eigenvectors,Machine learning,Binary number
Journal
Volume
Issue
ISSN
34
12
0031-3203
Citations 
PageRank 
References 
15
1.01
7
Authors
2
Name
Order
Citations
PageRank
Yeon-Sik Ryu1463.01
Oh Se-young2275.16