Face Recognition based on Discriminative Group Structured Dictionary

DOI

10.2991/tlicsc-18.2018.56How to use a DOI?

Keywords

Face recognition, discriminative group structured dictionary, group sparsity, linear discriminant analysis, low rank matrix recovery.

Abstract

Given a group structured dictionary, sparse representation vector is more likely to take on a particular structure. Intuitively, better results can be achieved if the structural characteristics are reasonably utilized. Inspired by this, we propose to construct a new discriminative group structured dictionary and impose a group sparse structure on the desired sparse representation vector. Thus, each testing sample can be decomposed as the product of the discriminative group structured dictionary and a group sparse representation vector. The identity of testing sample can be found by evaluating which class could induce the minimum reconstruction residual. Numerous experimental results on benchmark face databases demonstrate the effectiveness of the proposed method.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yuhua Li
PY  - 2018/12
DA  - 2018/12
TI  - Face Recognition based on Discriminative Group Structured Dictionary
BT  - Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)
PB  - Atlantis Press
SP  - 351
EP  - 358
SN  - 1951-6851
UR  - https://doi.org/10.2991/tlicsc-18.2018.56
DO  - 10.2991/tlicsc-18.2018.56
ID  - Li2018/12
ER  -