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Discriminant Analysis on Riemannian Manifold of Gaussian Distributions for Face Recognition with Image Sets

Wen Wang, Ruiping Wang, Zhiwu Huang, Shiguang Shan, Xilin Chen
2017 IEEE Transactions on Image Processing  
This paper presents a method named Discriminant Analysis on Riemannian manifold of Gaussian distributions (DARG) to solve the problem of face recognition with image sets.  ...  In the light of information geometry, the Gaussians lie on a specific Riemannian manifold.  ...  Overview of our approach In this paper we propose a new method named Discriminant Analysis on Riemannian manifold of Gaussian distributions (DARG) for face recognition with image sets.  ... 
doi:10.1109/tip.2017.2746993 pmid:28866497 fatcat:h4nu5sufprg4xlii2kga3xdj4u

Discriminant analysis on Riemannian manifold of Gaussian distributions for face recognition with image sets

Wen Wang, Ruiping Wang, Zhiwu Huang, Shiguang Shan, Xilin Chen
2015 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
This paper presents a method named Discriminant Analysis on Riemannian manifold of Gaussian distributions (DARG) to solve the problem of face recognition with image sets.  ...  In the light of information geometry, the Gaussians lie on a specific Riemannian manifold.  ...  Overview of our approach In this paper we propose a new method named Discriminant Analysis on Riemannian manifold of Gaussian distributions (DARG) for face recognition with image sets.  ... 
doi:10.1109/cvpr.2015.7298816 dblp:conf/cvpr/WangWHSC15 fatcat:xw7anblsjra6hnw6vi4ks6vwje

Multiple Riemannian Manifold-valued Descriptors based Image Set Classification with Multi-Kernel Metric Learning [article]

Rui Wang, XiaoJun Wu, Josef Kittler
2019 arXiv   pre-print
In recent years, some proposed image set classification methods have made a considerable advance by modeling the original image set with covariance matrix, linear subspace, or Gaussian distribution.  ...  The importance of wild video based image set recognition is becoming monotonically increasing.  ...  (RSR) [24] and Discriminant Analysis on 1 The source code will be released on: https://github.com/GitWR Riemannian manifold of Gaussian distributions (DARG) [10] . • Riemannian manifold dimensionality  ... 
arXiv:1908.01950v1 fatcat:wnzp4zuls5b5vgdbj6selzuc3a

Face recognition on large-scale video in the wild with hybrid Euclidean-and-Riemannian metric learning

Zhiwu Huang, Ruiping Wang, Shiguang Shan, Xilin Chen
2015 Pattern Recognition  
By treating each video as one image set, set-based methods recently have made great success in the field of video-based face recognition.  ...  Specifically, we represent each image set simultaneously by mean, covariance matrix and Gaussian distribution, which generally complement each other in the aspect of set modeling.  ...  With this in mind, we represent each image set with multiple statistics-mean, covariance matrix and Gaussian distribution.  ... 
doi:10.1016/j.patcog.2015.03.011 fatcat:sqr2cvioajdczbfmno3mnfonha

Hybrid Euclidean-and-Riemannian Metric Learning for Image Set Classification [chapter]

Zhiwu Huang, Ruiping Wang, Shiguang Shan, Xilin Chen
2015 Lecture Notes in Computer Science  
Besides, according to information geometry, the space of Gaussian distribution can be embedded into another Riemannian manifold Sym + d+1 .  ...  The proposed method is evaluated on two tasks: set-based object categorization and video-based face recognition.  ...  The work is partially supported by Natural Science Foundation of China under contracts nos.61390511, 61379083, and 61222211.  ... 
doi:10.1007/978-3-319-16811-1_37 fatcat:ihjhwmxo5rbglfwknfvbovj2jq

LGLG-WPCA: An Effective Texture-based Method for Face Recognition [article]

Chaorong Li, Huang Wei, Huafu Chen
2019 arXiv   pre-print
Because the space of Gaussian is a Riemannian manifold and it is difficult to incorporate learning mechanism in the model.  ...  In this paper, we proposed an effective face feature extraction method by Learning Gabor Log-Euclidean Gaussian with Whitening Principal Component Analysis (WPCA), called LGLG-WPCA.  ...  Chen, “Discriminative covariance Proceedings of the IEEE conference on computer vision and pattern oriented representation learning for face recognition with image sets,”  ... 
arXiv:1811.08345v4 fatcat:qy75mwqojvhijpvh3wty3gfbiq

Some Information Geometric Aspects of Cyber Security by Face Recognition

C. T. J. Dodson, John Soldera, Jacob Scharcanski
2021 Entropy  
The important provision is of a natural geometric measure structure on families of probability distributions by representing them as Riemannian manifolds.  ...  Exploring this property, we propose a new face recognition method which scores dissimilarities between face images by multiplying geodesic distance approximations between 3-variate RGB Gaussians representative  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/e23070878 fatcat:3kjpclkzivc3jf4w3vcwcplria

Cross Euclidean-to-Riemannian Metric Learning with Application to Face Recognition from Video [article]

Zhiwu Huang, Ruiping Wang, Shiguang Shan, Luc Van Gool, Xilin Chen
2017 arXiv   pre-print
By learning information on heterogeneous data with the shared label, the discriminant metric in the common space improves face recognition from videos.  ...  Riemannian manifolds have been widely employed for video representations in visual classification tasks including video-based face recognition.  ...  of faces with a variation model (e.g., linear subspace, affine subspace and SPD matrices) and learn a discriminant Riemannian metric on the underlying Riemannian manifold for robust videobased face recognition  ... 
arXiv:1608.04200v2 fatcat:6j2x3shm2baopbcw2akrm6jk7m

Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels

Sadeep Jayasumana, Richard Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Harandi
2015 IEEE Transactions on Pattern Analysis and Machine Intelligence  
We show that many popular algorithms designed for Euclidean spaces, such as support vector machines, discriminant analysis and principal component analysis can be generalized to Riemannian manifolds with  ...  Since the Gaussian RBF defined with any given metric is not always positive definite, we present a unified framework for analyzing the positive definiteness of the Gaussian RBF on a generic metric space  ...  The authors would like thank Bob Williamson for useful discussions.  ... 
doi:10.1109/tpami.2015.2414422 pmid:26539851 fatcat:zyremymijjbghcozmcet7ev474

Beyond Gauss: Image-Set Matching on the Riemannian Manifold of PDFs

Mehrtash Harandi, Mathieu Salzmann, Mahsa Baktashmotlagh
2015 2015 IEEE International Conference on Computer Vision (ICCV)  
State-of-the-art image-set matching techniques typically implicitly model each image-set with a Gaussian distribution.  ...  Our experiments on diverse problems, such as video-based face recognition and dynamic texture classification, evidence the benefits of our approach over the state-of-the-art image-set matching methods.  ...  image-sets with Gaussian distributions.  ... 
doi:10.1109/iccv.2015.468 dblp:conf/iccv/HarandiSB15 fatcat:tsdpeq5lcva4dnlb7lfq5uyvmu

A Benchmark and Comparative Study of Video-Based Face Recognition on COX Face Database

Zhiwu Huang, Shiguang Shan, Ruiping Wang, Haihong Zhang, Shihong Lao, Alifu Kuerban, Xilin Chen
2015 IEEE Transactions on Image Processing  
Face recognition with still face images has been widely studied, while the research on video-based face recognition is inadequate relatively, especially in terms of benchmark datasets and comparisons.  ...  Second, for benchmarking the three scenarios designed on our database, we review and experimentally compare a number of existing set-based methods.  ...  Yan Li for giving us great helps in collecting and processing COX face database.  ... 
doi:10.1109/tip.2015.2493448 pmid:26513790 fatcat:73fbij3kc5aozamebnwpm5dssm

Hilbert–Schmidt Independence Criterion Subspace Learning on Hybrid Region Covariance Descriptor for Image Classification

Xi Liu, Peng Yang, Zengrong Zhan, Zhengming Ma, Muhammad Haroon Yousaf
2021 Mathematical Problems in Engineering  
To address the non-Euclidean properties of SPD manifolds, this study also proposes an algorithm called the Hilbert-Schmidt independence criterion subspace learning (HSIC-SL) for SPD manifolds.  ...  The proposed method is compared with existing methods and is proved to be highly accurate and valid by classification experiments on the HRCD and HSIC-SL using the COIL-20, ETH-80, QMUL, face data FERET  ...  on SPD manifolds, but it was inferior in the classification of datasets with subtle features, such as face recognition and texture recognition.  ... 
doi:10.1155/2021/6663710 fatcat:ove6gjdomfd2bcfelqw75uqd3m

Face Recognition System Using: LDA and GMM based Approach

Aditi Mandloi, Priyanka Gupta
2017 International Journal of Computer Applications  
In this work we presented a novel Face Recognition feature Extraction Mode based on the combination of Linear Discriminant Analysis (LDA) and Gaussian Mixture Model (GMM).  ...  The classifier performance and the length of the selected feature vector are considered for performance evaluation using MATLAB in ORL face dataset.  ...  Wen Wang et al. [8] Presents a method named Discrimin1ant Analysis on Riemannian manifold of Gaussian distributions (DARG) to solve the problem of face recognition with image sets.  ... 
doi:10.5120/ijca2017915888 fatcat:4o7zzg556na77jhixwnedu25ze

Multiple Manifolds Metric Learning with Application to Image Set Classification [article]

Rui Wang, Xiao-Jun Wu, Kai-Xuan Chen, Josef Kittler
2018 arXiv   pre-print
In image set classification, a considerable advance has been made by modeling the original image sets by second order statistics or linear subspace, which typically lie on the Riemannian manifold.  ...  Motivated by the inability of existing methods to extract discriminatory features for data on Riemannian manifolds, we propose a novel algorithm which combines multiple manifolds as the features of the  ...  The Hybrid Euclidean-and-Riemannian Metric Learning (HERML) [21] is a method that combines multiple heterogeneous statistics, such as mean, covariance, and Gaussian distribution for image set classification  ... 
arXiv:1805.11918v1 fatcat:yrfxbnvhunaczcsmbdhojol6zq

An Effective Modeling for Face Recognition System: LDA and GMM based Approach

Aditi Mandloi, Priyanka Gupta
2017 International Journal of Computer Applications  
In this work we presented a novel Face Recognition feature Extraction Mode based on the combination of Linear Discriminant Analysis (LDA) and Gaussian Mixture Model (GMM).  ...  The definite advantages of face based recognition over other biometrics are distinctiveness and response.  ...  Wen Wang et al. [8] Presents a method named Discriminant Analysis on Riemannian manifold of Gaussian distributions (DARG) to solve the problem of face recognition with image sets.  ... 
doi:10.5120/ijca2017915889 fatcat:irlohfxeevhdtle42p66msep6a
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