Robust Face Recognition via Sparse Representation

Keywords

Sparse approximation, Robustness (evolution), Artificial intelligence, Pattern recognition (psychology), Facial recognition system

References

• Pattern ClassificationShigeo Abe — 2012
• Feature Selection in Face Recognition: A Sparse Representation PerspectiveAllen Y. Yang, John Wright, Yi Ma — 2007
• The Johnson-Lindenstrauss Lemma Meets Compressed SensingRichard G. Baraniuk, Mark A. Davenport, Ronald DeVore — 2006
• Learning a dictionary of shape-components in visual cortex: comparison with neurons, humans and machinesTomaso Poggio, T. Serre — 2006
• The AR face databaseAleix M. Martı́nez — 1998
• Autonomous Military Robotics: Risk, Ethics, and DesignPatrick Lin, George A. Bekey, Keith Abney — 2008
• Occluded face recognition using parts-based representation methodsIulian B. Ciocoiu — 2005
• Identification of Familiar and Unfamiliar Faces from Internal and External Features: Some Implications for Theories of Face RecognitionHadyn D. Ellis, John W. Shepherd, Graham Davies — 1979
• Model Selection and the Principle of Minimum Description LengthMark Hansen, Bin Yu — 2001
• Random Projections of Smooth ManifoldsRichard G. Baraniuk, Michael B. Wakin — 2009
• Atomic Decomposition by Basis PursuitScott Shaobing Chen, David L. Donoho, Michael A. Saunders — 1998
• Face recognition: A literature surveyWenyi Zhao, Rama Chellappa, P. Jonathon Phillips — 2003
• The Role of Eyebrows in Face RecognitionJavid Sadr, Izzat Jarudi, Pawan Sinha — 2003
• Robust Recognition Using EigenimagesAleš Leonardis, Horst Bischof — 2000
• For most large underdetermined systems of linear equations the minimal 𝓁1‐norm solution is also the sparsest solutionDavid L. Donoho — 2006
• Database-friendly random projectionsDimitris Achlioptas — 2001
• Modeling By Shortest Data Description*J. Rissanen — 1978
• Model Selection using the Minimum Description Length PrinciplePeter G. Bryant, Olga I. Cordero-Braña — 2000
• On the Approximability of Minimizing Nonzero Variables or Unsatisfied Relations in Linear SystemsE. Amaldi, Viggo Kann — 1998
• Face Recognition by Humans: Nineteen Results All Computer Vision Researchers Should Know AboutPawan Sinha, Benjamin Balas, Yuri Ostrovsky — 2006

Cited by

• Robust face recognition based on three dimensional dataDi Huang — 2011
• Sparse representation of dataThomas Villmann, Frank-Michael Schleif, Barbara Hammer — 2010
• Collaborative Discriminant Locality Preserving Projections With its Application to Face RecognitionSheng Huang, Dan Yang, Yang, Dong — 2013
• Face recognition under partial occlusion and small dense noiseRohit Kumar — 2014
• Towards a robust face recognition system using compressive sensingAllen Y. Yang, Zihan Zhou, Yi Ma — 2010
• A Sparse Coding Based Similarity MeasureSebastian Klenk, Gunther Heidemann — 2009
• Subspace Learning from Image Gradient OrientationsEnrico Reggiani — 2012
• Joint-Structured-Sparsity-Based Classification for Multiple-Measurement Transient Acoustic SignalsHamana Masatomo, 浜名 政和, Noda Hiroshi — 2012
• Blur and Illumination Robust Face Recognition via Set-Theoretic Characterization泰司 磯部 — 2013
• General Subspace Learning With Corrupted Training Data Via Graph EmbeddingJorge Fernández García — 2013
• Sparse Representation for Infrared Dim Target Detection via a Discriminative Over-Complete Dictionary Learned OnlineSamuel Vial Muñoz — 2014
• Maximal Likelihood Correspondence Estimation for Face Recognition Across Pose順一 長谷川, 宏美 伊藤, 克友 植松 — 2014
• Multilinear Sparse Principal Component AnalysisJosé Navarro Botella — 2014
• Vector Sparse Representation of Color Image Using Quaternion Matrix AnalysisDamien Kingsbury, Michael Leach — 2015
• SLED: Semantic Label Embedding Dictionary Representation for Multilabel Image AnnotationXiaochun Cao, Hua Zhang, Xiaojie Guo — 2015
• Integration of Sparse Multi-modality Representation and Geometrical Constraint for Isointense Infant Brain SegmentationLi Wang, Feng Shi, Gang Li — 2013
• Coupled Learning for Facial Deblur充 桜井, 禎隆 齋藤 — 2016
• Robust Object Tracking via Key Patch Sparse RepresentationClaudio Messori — 2017
• Robust surface normal estimation via greedy sparse regressionMingjing Zhang, Mark S. Drew — 2015
• Tree-Structured Nuclear Norm Approximation With Applications to Robust Face RecognitionRocío de Diego‐Cordero — 2016

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