Journal ArticleDOI
Face recognition
Keun-Chang Kwak,Witold Pedrycz +1 more
TLDR
This work designs classifiers based on the well-known fisherface method and demonstrates that the proposed method comes with better performance when compared with other template-based techniques and shows substantial insensitivity to large variation in light direction and facial expression.About:
This article is published in Pattern Recognition Letters.The article was published on 2005-05-01. It has received 679 citations till now. The article focuses on the topics: Facial recognition system & Fuzzy logic.read more
Citations
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Journal ArticleDOI
Dislocation, Not Dissociation: The Neuroanatomical Argument Against Visual Experience Driving Motor Action
TL;DR: It is argued that even if such content exists, it cannot be guiding motor action, since a review of current visual neuroscience indicates that the visual brain areas producing conscious representations are distinct from those driving motor action.
Book ChapterDOI
An Overview on Privacy Preserving Biometrics
TL;DR: The well-known ID/password is far the most used authentication method, it is widely spread despite its obvious lack of security, mainly due to its implementation ease and to its ergonomic feature: the users are used to this system, which enhances its acceptance and deployment.
Journal ArticleDOI
Factored principal components analysis, with applications to face recognition
TL;DR: A factored covariance model is proposed for matrix data, and a method for classification using a likelihood ratio criterion is developed, which has previously been used for evaluating the strength of forensic evidence.
Journal ArticleDOI
The own-age bias in face memory is unrelated to differences in attention- Evidence from event-related potentials
Markus F. Neumann,Albert End,Stefanie Luttmann,Stefan R. Schweinberger,Stefan R. Schweinberger,Holger Wiese +5 more
TL;DR: It is proposed that the OAB in memory is largely unrelated to early attentional processes, and contrast with the predictions from socio-cognitive accounts on own-group biases in recognition memory, and are more easily reconciled with expertise-based models.
Journal ArticleDOI
Prediction of eigenvalues and regularization of eigenfeatures for human face verification
TL;DR: Experimental results on popular face databases show that the proposed prediction and regularization strategy for alleviating the conventional problems of LDA and its variants consistently outperforms others.
References
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Journal ArticleDOI
Eigenfaces vs. Fisherfaces: recognition using class specific linear projection
TL;DR: A face recognition algorithm which is insensitive to large variation in lighting direction and facial expression is developed, based on Fisher's linear discriminant and produces well separated classes in a low-dimensional subspace, even under severe variations in lighting and facial expressions.
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
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.
Journal ArticleDOI
The FERET database and evaluation procedure for face-recognition algorithms
TL;DR: The FERET evaluation procedure is an independently administered test of face-recognition algorithms to allow a direct comparison between different algorithms and to assess the state of the art in face recognition.
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.