Reconstructed error and linear representation coefficients restricted by \(\ell_1\)-minimization for face recognition under different illumination and occlusion

DOI10.1155/2017/1458412zbMath1426.94032OpenAlexW2617008165WikidataQ59147255 ScholiaQ59147255MaRDI QIDQ1992344

Xiaoping Zeng, Xuegang Wu, Bin Fang, Changyuan Xing, Yuan Yan Tang

Publication date: 5 November 2018

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2017/1458412

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Uses Software

• AR face

Cites Work

• Unnamed Item
• Deep extreme learning machine and its application in EEG classification
• Subspace learning via local probability distribution for hyperspectral image classification
• A weighted block dictionary learning algorithm for classification
• Face recognition using FLDA with single training image per person
• Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
• Connected Component Model for Multi-Object Tracking
• Face Recognition Under Varying Illumination Using Gradientfaces
• Normalization of Face Illumination Based on Large-and Small-Scale Features
• For most large underdetermined systems of linear equations the minimal 𝓁₁‐norm solution is also the sparsest solution
• Stable signal recovery from incomplete and inaccurate measurements

This page was built for publication: Reconstructed error and linear representation coefficients restricted by \(\ell_1\)-minimization for face recognition under different illumination and occlusion