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Journal ArticleDOI

Face recognition

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.

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Citations
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Dissertation

Fusion of face and gait for human recognition

Rabia Jafri
TL;DR: The integrated system is found to outperform the individual face and gait classifiers that it is composed of, thus, demonstrating the potential of using the gait to supplement the face in scenarios where the face classifier alone does not perform well due to the non-availability of high resolution face data.
Dissertation

A Rough Set Approach to Face Recognition

Xuguang Chen
TL;DR: A Thesis Submitted to the Faculty of Graduate Studies & Research in Partial Fullfillment of the Requirements for the Degree of Doctor of Philosophy in Computer Science, University of Regina.

Ambient role playing games: towards a grammar of endlessness

Mark Eyles, +1 more
TL;DR: The development and deployment of an ambient role playing game prototype is described and future audiences and applications of this technology are suggested, with particular reference to possible requirements of ambient gaming women.
Journal ArticleDOI

A survey of genetic algorithm-based face recognition

TL;DR: The chromosomes generated by the genetic algorithm contain information (parameters) about the face, and genetic operators are used to detect and obtain the position of the face of interest in an image.

Fuzzy face model for face detection using eyes and mouth features

TL;DR: A novel approach for the detection of human face in a digital image based on the fuzzy spatial interrelationships of only the prominent facial features of the face, namely, eyes and mouth is proposed.
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

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

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

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.
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