Download:
|
by Chengjun Liu, Harry Wechsler
http://www.cs.gmu.edu/~cliu/papers/ijcnn99.ps.gz
Add To MetaCart
Abstract:
This paper introduces a new face coding scheme which employs an Enhanced Fisher Classifier (EFC) operating on integrated shape and intensity features. The dimensionalities of the shape and the intensity image spaces are first reduced using Principal Component Analysis (PCA), constrained by the EFC for enhanced generalization. The reduced shape and the intensity features are then integrated through a normalization procedure to form integrated features. Experiments using 600 face images from the FERET database of varying illumination and corresponding to 200 subjects, whose facial expression can vary, show the feasibility of the new face coding scheme. In particular, the EFC achieves 98.5 % recognition rate using only 25 features. Our experiments also show that the integrated shape and intensity features carry the most discriminating information followed in order by textures, shape vectors, masked images, and shape images. 1
Citations
|
1744
|
Eigenfaces for Recognition
– Turk, Pentland
- 1991
|
|
1663
|
Introduction to Statistical Pattern Recognition
– Fukunaga
- 1990
|
|
739
|
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection,” Proc
– Belhumeur, Hespanha, et al.
- 1997
|
|
402
|
Human and Machine Recognition of faces: A survey
– Chellappa, Sirohey
- 1995
|
|
263
|
Using discriminant eigenfeatures for image retrieval
– Swets, Weng
- 1996
|
|
203
|
The FERET database and evaluation procedure for facerecognition algorithms
– Phillips, Wechsler, et al.
- 1998
|
|
182
|
Automatic Recognition and Analysis of Human Faces and Facial Expressions: A
– Samal
- 1992
|
|
144
|
Linear object classes and image synthesis from a single example
– Vetter, Poggio
- 1997
|
|
133
|
T.: Automatic interpretation and coding of face images using flexible models
– Lanitis, Taylor, et al.
- 1997
|
|
52
|
Face recognition using active appearance models
– Edwards, Cootes, et al.
- 1998
|
|
36
|
Face recognition by computer
– Craw, Cameron
- 1992
|
|
28
|
Vectorizing Face Images by Interleaving Shape and Texture Computations
– Beymer
- 1995
|
|
26
|
How should we represent faces for automatic recognition
– Craw, Costen, et al.
- 1999
|
|
21
|
Enhanced Fisher linear discriminant models for face recognition
– Liu, Wechsler
|
|
21
|
Probabilistic reasoning models for face recognition
– Liu, Wechsler
|
