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Privacy-Preserving Face Recognition with Outsourced Computation
applications Outsourced Computation
2016/1/5
Face recognition is one of the most important biometrics pattern recognitions, which has been widely applied in a variety of enterprise, civilian and law enforcement. The privacy of biometrics data ra...
Maori facial tattoo (Ta Moko): implications for face recognition processes.
Face recognition
2015/7/28
Ta Moko is the art of the Maori tattoo. It was an integral aspect of Maori society and is currently seeing resurgence in popularity. In particular it is linked with ancestry and a sense of “Maori” pri...
Face recognition plays an important role in biometrics base personal identification. The need for reliable recognition and identification
of interacting users is obvious. The biometrics recognition ...
An ever-increasing number of personal photos is stored online. This trend can be problematic, because face recognition software can undermine user privacy in unexpected ways. Face de-identification ai...
Face Recognition from Incomplete Measurements via l1-Optimization
Sparse Representation l1Minimization Face Recognition Sparse Recovery Interior Point Methods Sparse Regularization
2013/1/30
In this work, we consider a homotopic principle for solving large-scale and dense l1underdetermined problems and its applications in image processing and classification. We solve the face recognition ...
Efficient Point-to-Subspace Query in $\ell^1$ with Application to Robust Face Recognition
point-to-subspace distance nearest subspace search Cauchy projection ace recog-nition subspace modeling
2012/9/18
Motivated by vision tasks such as robust face and object recognition, we consider the follow-ing general problem: given a collection of low-dimensional linear subspaces in a high-dimensional ambient (...
Weighted Scatter-Difference-Based Two DimensionalDiscriminant Analysis for Face Recognition
Feature Extraction Face Recognition LDA PCA 2DPCA 2DLDA WSD2DDA
2013/1/28
Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension. It has been used widely in many applications involving high-dimensional data, such as face recognition, ...
Face Recognition Based on Non-Corresponding Region Matching
Recognition Non-Corresponding Region Matching
2013/7/24
In previous works of face recognition, similarity betweenfaces is measured by comparing corresponding face regions. That is to say, matching eyes with eyes and mouths withmouths etc.. In this paper, w...
Sparsely Encoded Local Descriptor for Face Recognition
Random-projection tree Sparse coding face verification face identification
2013/7/24
In this paper, a novel Sparsely Encoded Local Descriptor (SELD) is proposed for face recognition. Compared with K-means or Random-projection tree based previous methods, sparsity constraint is introdu...
Margin Emphasized Metric Learning and Its Application to Gabor Feature Based Face Recognition
face verification metric learning margin Gabor Labeled Faces in Wild
2013/7/24
In addressing side information based face recognition scenario, a new Margin Emphasized Metric Learning (MEML) method is proposed. As an improvement of previous metric learning, MEML defines a new obj...
Adaptive Discriminant Analysis for face recognition from Single Sample per Person
Adaptive Discriminant Single Sample
2013/7/24
Discriminant analysis, especially Fisherface and its numerous variants, have achieved great success in face recognition. However, these methods fail to work for face recognition from Single Sample per...
Attention Driven Face Recognition: A Combination of Spatial Variant Fixations and Glance
Face Recognition Human Visual System
2013/7/24
This paper proposes a novel face recognitionalgorithm inspired by the selective attention of Human VisualSystem (HVS). We record four observers’ eye movements whenthey are viewing 100 FRGC [1] frontal...
Co-occurrence matrix and its statistical features as a new approach for face recognition
Face recognition gray-level co-occurrence matrix Haralick features
2011/3/22
In this paper, a new face recognition technique is introduced based on the gray-level co-occurrence matrix (GLCM). GLCM represents the distributions of the intensities and the information about relati...
Adaptive Generic Learning for Face Recognition from a Single Sample per Person
Adaptive Generic Face Recognition Single Sample per Person
2010/12/21
Real-world face recognition systems often have to face the single sample per person (SSPP) problem, that is, only a single training sample for each person is enrolled in the
database. In this case, m...