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Face Detection Using an SVM Trained in Eigenfaces Space
[chapter]
2003
Lecture Notes in Computer Science
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1 The central problem in the case of face detectors is to build a face class model. We present a method for face class modeling in the eigenfaces space using a large-margin classifier like SVM. ...
We will present different strategies for choosing the dimensionality of the PCA space and discuss their effectiveness in the case of face-class modeling. ...
More detailed results will be presented in the final version of the paper.
Conclusions In this paper we presented a method for face class modeling in eigenfaces space. ...
doi:10.1007/3-540-44887-x_23
fatcat:r5v67zls5zaong3qdixch4njye
Eigen Faces and Principle Component Analysis for Face Recognition Systems: A Comparative Study
2015
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY
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Eigenfaces and principle component analysis (PCA) can be considered as most important face recognition approaches in the literature. ...
At the same time, there is a lack of literature studies which are related to face recognition systems based on EigenFaces and PCA. ...
These Eigenfaces contribute in reconstruction of a new face image projected onto face space with a weight. ...
doi:10.24297/ijct.v14i4.1967
fatcat:mj5konnzkbendj3tuzzjiooahu
Intelligent Sensor for Image Control Point of Eigenfaces for Face Recognition
2010
Journal of Computer Science
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Approach: In fact, the aim of such a research consisted first, identification of the face recognition and the possibility of improving eigenface recognition. ...
Problem statement: The sensor for image control point in Face Recognition (FR) is one of the most active research areas in computer vision and pattern recognition. ...
The images of known individual fall near some face class in the face space. ...
doi:10.3844/jcssp.2010.484.491
fatcat:kenq2cluz5bi3fwfkbbv3auita
Intelligent sensor for image control point of eigenface for face recognition
2010
2010 2nd International Conference on Signal Processing Systems
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Approach: In fact, the aim of such a research consisted first, identification of the face recognition and the possibility of improving eigenface recognition. ...
Problem statement: The sensor for image control point in Face Recognition (FR) is one of the most active research areas in computer vision and pattern recognition. ...
The images of known individual fall near some face class in the face space. ...
doi:10.1109/icsps.2010.5555793
fatcat:naiw3zo4bzdpdhf3jjvztg7cim
Face Recognition Applied to Computer Forensics
2006
The International Journal of Forensic Computer Science
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A model of automated face recognition, based on algorithm designated eigenfaces is considered and presented in details. ...
In this paper, a historical briefing of face recognition is presented. Some psychological aspects of the subject and models considered for face perception are also presented. ...
All the representative images of the classes are projected in eigenfaces space and represented by a linear combination of eigenfaces, having a new variable that corresponds to a more condensed dimensional ...
doi:10.5769/j200601002
fatcat:rssu7e472rcbjhlkwhmtv5spky
Array of Multilayer Perceptrons with No-class Resampling Training for Face Recognition
2010
Inteligencia Artificial
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Once a face is located in an image, it has to be represented through a feature extraction process, for later performing a proper face classification task. ...
In the classification phase, an input face is projected to the obtained eigenspace and classified by an appropriate classifier. ...
In this way, if we deal with aproximately similar images of faces, they will be located in a small region of the space. ...
doi:10.4114/ia.v13i44.1041
fatcat:42c7s5d7mjblnl527np6n5sbda
Face Recognition using Fisherfaces
2019
International Journal for Research in Applied Science and Engineering Technology
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Distinctive procedure, for example, eigenface, fisher faces, flexible pack chart coordinating and so forth can be utilize full for the location. ...
In any case, the fisherface technique can exploit ewithin-classí data, limiting variety inside each class, yet as yet boosting class detachment. ...
For instance, one's face may be made out of the normal face in addition to 10% from eigenface 1, 55% from eigenface 2, and even −3% from eigenface 3. ...
doi:10.22214/ijraset.2019.10039
fatcat:uc5d4ywjgredxf6smixbxcihaq
A Statistical Nonparametric Approach of Face Recognition: Combination of Eigenface & Modified k-Means Clustering
[article]
2011
arXiv
pre-print
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This methodology is developed combining Eigenface method for feature extraction and modified k-Means clustering for identification of the human face. ...
Automatic recognition of human face based on facial expression can be an important component of natural human-machine interface. It may also be used in behavioural science. ...
[6] deals with "face recognition using the mixtureof-eigenfaces method" uses more than one set of eigenfaces from the expectation maximization learning in the PCA mixture model for representation of ...
arXiv:1104.1237v1
fatcat:wy2tq5spnbgofbcm4squnjnewa
Mixture of SVMs for Face Class Modeling
[chapter]
2005
Lecture Notes in Computer Science
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We 1 present a method for face detection which uses a new SVM structure trained in an expert manner in the eigenface space. ...
class modeling. ...
In [6] , Popovici and Thiran proposed to model the face class using a SVM trained in eigenfaces space. ...
doi:10.1007/978-3-540-30568-2_15
fatcat:6oz7x7ln4beivltlqdvyk5ba7a
Face Class Modeling Using Mixture of SVMs
[chapter]
2004
Lecture Notes in Computer Science
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We 1 present a method for face detection which uses a new SVM structure trained in an expert manner in the eigenface space. ...
class modeling. ...
In [6] , Popovici and Thiran proposed to model the face class using a SVM trained in eigenfaces space. ...
doi:10.1007/978-3-540-30126-4_86
fatcat:my7wakhosbcf3ffhto4cpfleje
Face recognition using Eigenfaces-Fisher Linear Discriminant and Dynamic Fuzzy Neural Network
2010
2010 3rd International Conference on Computer Science and Information Technology
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In order to solve the problem of face recognition in natural illumination, a new face recognition algorithm using Eigenface-Fisher Linear Discriminant (EFLD) and Dynamic Fuzzy Neural Network (DFNN) is ...
In this paper, we use EFLD model to extract the face feature, which will be considered as the input of the DFNN. And the DFNN is implemented as a classifier to solve the problem of classification. ...
And it will be the future work. i th set of eigenface. c is the number of the class and n i represents the number of i th class. ...
doi:10.1109/iccsit.2010.5563558
fatcat:akzhhn664rbxpiqbdpeeoudqpa
An Evaluation of Audio-Visual Person Recognition on the XM2VTS Corpus using the Lausanne Protocols
2007
2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07
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This architecture exploits the complementary and redundant nature of the face and speech modalities. ...
This multimodal architecture includes the fusion of a face recognition system with the MIT/LL GMM/UBM speaker recognition architecture. ...
The columns of Φ F form a basis for the Eigenfaces face space whose origin is the mean face Ψ. ...
doi:10.1109/icassp.2007.366893
dblp:conf/icassp/BradyBQD07
fatcat:5vqlw4kosjhl5g3qjpw4is4ypa
Face recognition using the nearest feature line method
1999
IEEE Transactions on Neural Networks
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In this paper, we propose a novel classification method, called the nearest feature line (NFL), for face recognition. ...
With a combined face database, the NFL error rate is about 43.7-65.4% of that of the standard eigenface method. ...
In a feature space, which is an eigenface space in this study, the NFL method uses a linear model to interpolate and extrapolate each pair of prototype feature points belonging to the same class. ...
doi:10.1109/72.750575
pmid:18252542
fatcat:li2l4mgdfzazda6ufenkq2xw4a
Comparison of Different Face Recognition Method Based On PCA
2014
INTERNATIONAL JOURNAL OF MANAGEMENT & INFORMATION TECHNOLOGY
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This paper is about human face recognition in image files. Face recognition involves matching a given image with the database of images and identifying the image that it resembles the most. ...
Here, face recognition is done using: (a) Eigen faces and (b) applying Principal Component Analysis (PCA) on image. ...
face class. ...
doi:10.24297/ijmit.v10i4.626
fatcat:7wshau3h4zalrflsmzpbpcype4
Eigenfaces vs. Fisherfaces: recognition using class specific linear projection
1997
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Rather than explicitly modeling this deviation, we linearly project the image into a subspace in a manner which discounts those regions of the face with large deviation. ...
We take advantage of the observation that the images of a particular face, under varying illumination but fixed pose, lie in a 3D linear subspace of the high dimensional image space-if the face is a Lambertian ...
First, due to selfshadowing, specularities, and facial expressions, some regions in images of the face have variability that does not agree with the linear subspace model. ...
doi:10.1109/34.598228
fatcat:vxenjxbi2fg5nnjs4i3plfgueu
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