Proceedings ArticleDOI
Face identification by means of a neural net classifier
Virginia Espinosa-Duro,Marcos Faundez-Zanuy +1 more
- pp 182-186
TLDR
A novel face identification method that combines the eigenfaces theory with the Neural Nets, and a neural net classifier that performs the identification process is presented.Abstract:
This paper describes a novel face identification method that combines the eigenfaces theory with the Neural Nets. We use the eigenfaces methodology in order to reduce the dimensionality of the input image, and a neural net classifier that performs the identification process. The method presented recognizes faces in the presence of variations in facial expression, facial details and lighting conditions. A recognition rate of more than 87% has been achieved, while the classical method of Turk and Pentland achieves a 75.5%.read more
Citations
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Proceedings ArticleDOI
Facial Expression Recognition Using Neural Networks and Log-Gabor Filters
TL;DR: This study proposes a classification-based facial expression recognition method using a bank of multilayer perceptron neural networks, using logarithmic Gabor filters to extract features and testing on static images from the Cohn-Kanade database found that the average correct classification rate was increased from 52% for the full set of the log-Gabor features, to 70%" for the optimised sub-set of log- Gabor features.
Proceedings ArticleDOI
Facial expression recognition from image sequences using optimized feature selection
TL;DR: A novel method for facial expression recognition from sequences of image frames is described and tested and can automatically recognize six expressions: anger, disgust, fear, happiness, sadness and surprise.
Facial expression recognition using log-Gabor filters and local binary pattern operators
TL;DR: Two different methods of feature extraction for person-independent facial expression recognition from images are investigated, with comparable performance between Log-Gabor filters and LBP operator, with a classification accuracy of around 82.3% and 81.7% respectively.
Face Recognition using Radial Basis Function Network based on LDA.
TL;DR: In this paper, a method to improve the robustness of a face recognition system based on the combination of two compensating classifiers is described, where face images are preprocessed by the appearance-based statistical approaches such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA).
Proceedings ArticleDOI
Biometric identification system using a radial basis network
TL;DR: An efficient face identification method using a probabilistic neural net based on the Karhunen-Loeve transform for feature extraction and a feedforward multilayer perceptron neural net, implemented as a classifier device, that performed the identification process.
References
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Journal ArticleDOI
Eigenfaces for recognition
Matthew Turk,Alex Pentland +1 more
TL;DR: A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture.
Proceedings ArticleDOI
Face recognition using eigenfaces
Matthew Turk,Alex Pentland +1 more
TL;DR: An approach to the detection and identification of human faces is presented, and a working, near-real-time face recognition system which tracks a subject's head and then recognizes the person by comparing characteristics of the face to those of known individuals is described.
Journal ArticleDOI
Human and machine recognition of faces: a survey
TL;DR: A critical survey of existing literature on human and machine recognition of faces is presented, followed by a brief overview of the literature on face recognition in the psychophysics community and a detailed overview of move than 20 years of research done in the engineering community.
Proceedings ArticleDOI
View-based and modular eigenspaces for face recognition
Pentland,Moghaddam,Starner +2 more
TL;DR: In this paper, a view-based multiple-observer eigenspace technique is proposed for use in face recognition under variable pose, which incorporates salient features such as the eyes, nose and mouth, in an eigen feature layer.
Journal ArticleDOI
Automatic recognition and analysis of human faces and facial expressions: a survey
Ashok Samal,Prasana A. Iyengar +1 more
TL;DR: The capability of the human visual system with respect to face identification, analysis of facial expressions, and classification based on physical features of the face are discussed.