loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Shibo Gao 1 ; Yizhou Yu 2 and Yongmei Cheng 1

Affiliations: 1 College of Automation and Northwestern Polytechnical University, China ; 2 The University of Hong Kong, Hong Kong

Keyword(s): Face Recognition, Linear Subspace Learning, Discriminative Dictionary Learning.

Abstract: Learning linear subspaces for high-dimensional data is an important task in pattern recognition. A modern approach for linear subspace learning decomposes every training image into a more discriminative part (MDP) and a less discriminative part (LDP) via sparse coding before learning the projection matrix. In this paper, we present a new linear subspace learning algorithm through discriminative dictionary learning. Our main contribution is a new objective function and its associated algorithm for learning an overcomplete discriminative dictionary from a set of labeled training examples. We use a Fisher ratio defined over sparse coding coefficients as the objective function. Atoms from the optimized dictionary are used for subsequent image decomposition. We obtain local MDPs and LDPs by dividing images into rectangular blocks, followed by blockwise feature grouping and image decomposition. We learn a global linear projection with higher classification accuracy through the local MDPs a nd LDPs. Experimental results on benchmark face image databases demonstrate the effectiveness of our method. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.221.174.248

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Gao, S.; Yu, Y. and Cheng, Y. (2013). Linear Subspace Learning based on a Learned Discriminative Dictionary for Sparse Coding. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2013) - Volume 1: VISAPP; ISBN 978-989-8565-47-1; ISSN 2184-4321, SciTePress, pages 530-538. DOI: 10.5220/0004207905300538

@conference{visapp13,
author={Shibo Gao. and Yizhou Yu. and Yongmei Cheng.},
title={Linear Subspace Learning based on a Learned Discriminative Dictionary for Sparse Coding},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2013) - Volume 1: VISAPP},
year={2013},
pages={530-538},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004207905300538},
isbn={978-989-8565-47-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2013) - Volume 1: VISAPP
TI - Linear Subspace Learning based on a Learned Discriminative Dictionary for Sparse Coding
SN - 978-989-8565-47-1
IS - 2184-4321
AU - Gao, S.
AU - Yu, Y.
AU - Cheng, Y.
PY - 2013
SP - 530
EP - 538
DO - 10.5220/0004207905300538
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic