Journal ArticleDOI
Computer recognition of human face—A survey
TLDR
The article presents the latest trends in computer-based human face recognition by introducing methods of facial pattern representation intended to identify persons using frontal face images as well as recent studies in extending those methods by giving flexibility in terms of face orientation and view.Abstract:
The article presents the latest trends in computer-based human face recognition. First, methods of facial pattern representation intended to identify persons using frontal face images are introduced as well as recent studies in extending those methods by giving flexibility in terms of face orientation and view. The FERET face recognition project, which is one of the driving forces to promote robustness in face recognition technology, is considered. In addition, computer face recognition is treated as an element of media processing for content search and editing of visual databases, and studies in computer face recognition that model human cognition in the face recognition process are surveyed. Finally, the state of the art in extracting facial patterns from visual scenes is analyzed. © 1999 Scripta Technica, Syst Comp Jpn, 30(10): 76–89, 1999read more
Citations
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Patent
Method for verifying users and updating database, and face verification system using the same
TL;DR: In this paper, a method was proposed to reduce degradation of recognition performance due to eye detection errors during face verification and to overcome a problem in that sufficient data to design an optimum feature classifier cannot be obtained during face registration.
Journal ArticleDOI
Affective Information Processing and Recognizing Human Emotion
TL;DR: A new approach for recognizing human emotion based on Mental State Transition Network will be described and one emotion estimation method based on sentence pattern of emotion occurrence events will be discussed, and some new results of the project will be given.
Proceedings ArticleDOI
Scale invariant face detection method using higher-order local autocorrelation features extracted from log-polar image
TL;DR: A scale invariant face detection method which combines higher-order local autocorrelation (HLAC) features extracted from a log-polar transformed image with linear discriminant analysis for "face" and "not face" classification is proposed.
Book ChapterDOI
Vision-based face understanding technologies and applications
TL;DR: Vision-based face understanding technologies, such as face detection, facial feature point detection, face recognition, face tracking, encoding and transmission of facial motion, face situation estimation, gender and age estimation, etc, are introduced.
Proceedings ArticleDOI
Detecting head pose from stereo image sequence for active face recognition
Ming Xu,T. Akatsuka +1 more
TL;DR: An approach to detect human head pose by reconstructing 3D positions of facial points from stereo images is proposed for the implementation of an active face recognition system where fast, correct and automatic head pose detection is of critical importance.
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.
Journal ArticleDOI
Neural network-based face detection
TL;DR: A neural network-based upright frontal face detection system that arbitrates between multiple networks to improve performance over a single network, and a straightforward procedure for aligning positive face examples for training.
Journal ArticleDOI
Understanding face recognition
Vicki Bruce,Andrew W. Young +1 more
TL;DR: A functional model is proposed in which structural encoding processes provide descriptions suitable for the analysis of facial speech, for analysis of expression and for face recognition units, and it is proposed that the cognitive system plays an active role in deciding whether or not the initial match is sufficiently close to indicate true recognition.
Journal ArticleDOI
Networks for approximation and learning
Tomaso Poggio,Federico Girosi +1 more
TL;DR: Regularization networks are mathematically related to the radial basis functions, mainly used for strict interpolation tasks as mentioned in this paper, and two extensions of the regularization approach are presented, along with the approach's corrections to splines, regularization, Bayes formulation, and clustering.
Journal ArticleDOI
Face recognition: features versus templates
Roberto Brunelli,Tomaso Poggio +1 more
TL;DR: Two new algorithms for computer recognition of human faces, one based on the computation of a set of geometrical features, such as nose width and length, mouth position, and chin shape, and the second based on almost-gray-level template matching are presented.