Discriminative Structured Dictionary Learning for Face Recognition

  • Ying ZhuEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 517)


For a few years, plenty of face recognition algorithms, such as deep learning, have been in hot pursuit with the trend of the technology, while dictionary learning algorithm is still out of the woods for the sake of its higher robustness to occlusion and light. In this paper, we propose to learn a discriminative structured dictionary with constraint named as multi-label to suppress representations for different classes, as well as Laplacian Eigenmaps to encourage the representations for the same class to be close to each other. Demonstrated by the results of the experiments, our proposed dictionary learning methods intend to achieve better classification performance and higher computational efficiency compared to the existing algorithms.


Dictionary learning Supervised learning Face recognition Laplacian Eigenmaps 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.College of Telecommunication and InformationNanjing University of Posts and TelecommunicationsNanjingChina

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