Discriminative neighborhood preserving dictionary learning for image classification

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a discriminative neighborhood preserving dictionary learning method is proposed. The geometrical structure of the feature space is used to preserve the similarity information of the features, and the features’ class information is employed to enhance the discriminative power of the learned dictionary. The Laplacian matrix which expresses the similarity information and the class information of the features is constructed and used in the objective function. Experimental results on four public datasets demonstrate the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationImage and Graphics - 8th International Conference, ICIG 2015, Proceedings
EditorsYu-Jin Zhang
PublisherSpringer Verlag
Pages185-196
Number of pages12
ISBN (Print)9783319219622
DOIs
Publication statusPublished - 2015
Event8th International Conference on Image and Graphics, ICIG 2015 - Tianjin, China
Duration: 13 Aug 201516 Aug 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9218
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Image and Graphics, ICIG 2015
Country/TerritoryChina
CityTianjin
Period13/08/1516/08/15

Keywords

  • Dictionary learning
  • Discriminative
  • Image classification
  • Similarity

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