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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Proceedings ArticleDOI
Subspace State Estimator for Facial Biometric Verification
TL;DR: The experimental results demonstrate the superiority of the proposed method in comparison with its counterparts, and include a subspace method that overcomes the computational complexity associated with the sequential estimator.
Face authentication /recognition system for forensic application using sketch based on the sift features approach
TL;DR: The proposed algorithm is generic and is not tied up to specific features, and does not impose any restrictions on the location of features in the recognition process.
Dissertation
Face Detection and Recognition in Video-Streams
TL;DR: This work demonstrates how the Viola-Jones face detector can be combined with a person specific active appearance model and used for automated annotation of video streams and demonstrates the face detection and recognition scheme on a series of Danmarks Radio game shows featuring actor and talk show host Jarl Friis Mikkelsen.
Journal ArticleDOI
Selecting discriminant eigenfaces by using binary feature selection
TL;DR: A binary feature selection (BFS) method to choose the most suitable set of eigenfaces for classification when only a small number of training samples per subject are available and outperforms not only traditional PCA and LDA but also some state of the art methods.
Performance Evaluation of Principal Component Analysis And Independent Component Analysis Algorithms For Facial Recognition
M A Hambali,Jimoh R. G +1 more
TL;DR: Comparison study of two most popular appearance-based face recognition methods - Principal Component Analysis and Independent Component Analysis showed that Indepenedent Component Analysis (ICA) perform better in term of recognition rate and error rate, therefore it can be used for real time recognition system.
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.