Proceedings ArticleDOI
Weighted PCA space and its application in face recognition
Hui-Yuan Wang,Xiao-Juan Wu +1 more
- Vol. 7, pp 4522-4527
TLDR
The simulation results indicate that the proposed approach is superior to conventional PCA approach in recognition accuracy under the same computation complexity.Abstract:
In this paper, we propose a new PCA based subspace approach for pattern recognition. The conventional PCA feature space is first converted to a WPCA feature space with unit variance by weighting the features and then face recognition is performed in the new space. Detailed theoretical derivation and analysis are presented and simulation results on AR and ORL face databases are given. The simulation results indicate that the proposed approach is superior to conventional PCA approach in recognition accuracy under the same computation complexity.read more
Citations
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Spike sorting with Gaussian mixture models
TL;DR: An approach to perform unsupervised clustering using GMMs, estimating cluster properties in a data-driven way is developed and found the proposed GMM-based framework outperforms previously established methods in simulated and real extracellular recordings.
Proceedings ArticleDOI
DWT/PCA Face Recognition using Automatic Coefficient Selection
P. Nicholl,Abbes Amira +1 more
TL;DR: This paper proposes a method to automatically determine the most discriminative coefficients in a DWT/PCA-based face recognition system, based on their inter-class and intra-class standard deviations of the training set eigenface weight vectors.
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Biometric dispersion matcher
TL;DR: This paper proposes a new classifier called a dispersion matcher that can classify an open world problem and do not need to train the model again if a new user is added, and finds a natural solution for feature selection.
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A fast ℓ1-solver and its applications to robust face recognition
TL;DR: A recently proposed Lagrange Dual Method is applied to design a new Sparse Representation-based Classification algorithm for robust face recognition problem that improves the efficiency of the SRC algorithm significantly and can maintain good recognition accuracy whilst reducing the computational time dramatically.
Posted ContentDOI
Spike sorting with Gaussian mixture models
TL;DR: This study developed an approach to perform unsupervised clustering using GMMs, which estimates cluster properties in a data-driven way and shows that the proposed GMM-based framework outperforms previously established methods when using realistic simulations of extracellular spikes and actual Extracellular recordings to evaluate sorting performance.
References
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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.
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PCA versus LDA
Aleix M. Martinez,Avinash C. Kak +1 more
TL;DR: In this article, the authors show that when the training data set is small, PCA can outperform LDA and, also, that PCA is less sensitive to different training data sets.
Journal ArticleDOI
Application of the Karhunen-Loeve procedure for the characterization of human faces
Michael Kirby,Lawrence Sirovich +1 more
TL;DR: The use of natural symmetries (mirror images) in a well-defined family of patterns (human faces) is discussed within the framework of the Karhunen-Loeve expansion, which results in an extension of the data and imposes even and odd symmetry on the eigenfunctions of the covariance matrix.
Journal ArticleDOI
Face recognition by independent component analysis
TL;DR: Independent component analysis (ICA), a generalization of PCA, was used, using a version of ICA derived from the principle of optimal information transfer through sigmoidal neurons, which was superior to representations based on PCA for recognizing faces across days and changes in expression.