Optimal projection guided transfer hashing for image retrieval

Lei Zhang, Ji Liu, Yang Yang, Fuxiang Huang, Feiping Nie, David Zhang

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

Recently, learning to hash has been widely studied for image retrieval thanks to the computation and storage efficiency of binary codes. Most existing learning to hash methods have yielded significant performance. However, for most existing learning to hash methods, sufficient training images are required and used to learn precise hashing codes. In some real-world applications, there are not always sufficient training images in the domain of interest. In addition, some existing supervised approaches need a amount of labeled data, which is an expensive process in terms of time, labor and human expertise. To handle such problems, inspired by transfer learning, we propose a simple yet effective unsupervised hashing method named Optimal Projection Guided Transfer Hashing (GTH) where we borrow the images of other different but related domain i.e., source domain to help learn precise hashing codes for the domain of interest i.e., target domain. In GTH, we aim to learn domain-invariant hashing functions. To achieve that, we propose to minimize the error matrix between two hashing projections of target and source domains. We seek for the maximum likelihood estimation (MLE) solution of the error matrix between the two hashing projections due to the domain gap. Furthermore, an alternating optimization method is adopted to obtain the two projections of target and source domains. By doing so, two projections can be progressively aligned. Extensive experiments on various benchmark databases for cross-domain visual recognition verify that our method outperforms many state-of-the-art learning to hash methods. The source code is available at https://github.com/liuji93/GTH.

Original languageEnglish
Article number8850110
Pages (from-to)3788-3802
Number of pages15
JournalIEEE Transactions on Circuits and Systems for Video Technology
Volume30
Issue number10
DOIs
StatePublished - Oct 2020

Keywords

  • image retrieval
  • learning to hash
  • maximum likelihood estimation
  • Projection alignment
  • transfer learning

Fingerprint

Dive into the research topics of 'Optimal projection guided transfer hashing for image retrieval'. Together they form a unique fingerprint.

Cite this