Locality-preserving K-SVD based joint dictionary and classifier learning for object recognition

Yuan Shan Lee, Chien Yao Wang, Seksan Mathulaprangsan, Jia Hao Zhao, Jia Ching Wang

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

9 Scopus citations


This paper concerns the development of locality-preserving methods for object recognition. The major purpose is consideration of both descriptor-level locality and image-level locality throughout the recognition process. Two dual-layer locality-preserving methods are developed, in which locality-constrained linear coding (LLC) is used to represent an image. In the learning phase, the discriminative locality-preserving K-SVD (DLP-KSVD) in which the label information is incorporated into the locality-preserving term is proposed. In addition to using class labels to learn a linear classifier, the label-consistent LP-KSVD (LCLP-KSVD) is proposed to enhance the discriminability of the learned dictionary. In LCLP-KSVD, the objective function includes a label-consistent term that penalizes sparse codes from different classes. For testing, additional information about the locality of query samples is obtained by treating the locality-preserving matrix as a feature. The recognition results that were obtained in experiments with the Caltech101 database indicate that the proposed method outperforms existing sparse coding based approaches.

Original languageEnglish
Title of host publicationMM 2016 - Proceedings of the 2016 ACM Multimedia Conference
PublisherAssociation for Computing Machinery, Inc
Number of pages5
ISBN (Electronic)9781450336031
StatePublished - 1 Oct 2016
Event24th ACM Multimedia Conference, MM 2016 - Amsterdam, United Kingdom
Duration: 15 Oct 201619 Oct 2016

Publication series

NameMM 2016 - Proceedings of the 2016 ACM Multimedia Conference


Conference24th ACM Multimedia Conference, MM 2016
Country/TerritoryUnited Kingdom


  • D-KSVD
  • Joint dictionary learning
  • K-SVD
  • Locality-preserving
  • Object recognition


Dive into the research topics of 'Locality-preserving K-SVD based joint dictionary and classifier learning for object recognition'. Together they form a unique fingerprint.

Cite this