OMGH: Online Manifold-Guided Hashing for Flexible Cross-modal Retrieval

Xin Liu*, Jinhan Yi, Yiu Ming Cheung, Xing Xu, Zhen Cui

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

15 Citations (Scopus)

Abstract

Cross-modal hashing hasrecently gained an increasing attention for its efficiency and fast retrieval speed in indexing the multimedia data across different modalities. Nevertheless, the multimedia data points often emerge in a streaming manner, and existing online methods often lack of learning capacity to handle both labeled and unlabeled data.To alleviate these concerns, this paper proposes an Online Manifold-Guided Hashing (OMGH) framework, which can incrementally learn the compact hash code of streaming data while adaptively optimizing the hash function in a streaming manner. To be specific, OMGH first exploits a matrix tri-factorization framework to learn the discriminative hash codes for streaming multi-modal data. Then, an online anchor-based manifold structure is designed to sparsely represent the old data and adaptively guide the hash code learning process, which can wellreduce the complexity in preserving the semantic correlation between the old data and streaming data. Meanwhile, such anchor-based manifold embedding is adaptive to the unsupervised and supervised learning strategies in a flexible way. Besides, an online discrete optimization method is efficiently addressed to incrementally update the hash functions and optimize the hash codes on streaming data points. As a result, the derived hash codes are more semantically meaningful for various online cross-modal retrieval tasks. Extensive experiments verify the advantages of the proposed OMGH model, by achieving and improving the state-of-the-art cross-modal retrieval performances on three benchmark datasets.

Original languageEnglish
Pages (from-to)3811-3824
Number of pages14
JournalIEEE Transactions on Multimedia
Volume25
Early online date12 Apr 2022
DOIs
Publication statusPublished - Sept 2023

Scopus Subject Areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Media Technology
  • Computer Science Applications

User-Defined Keywords

  • Cross-modal hashing
  • Anchor-based manifold structure
  • online discrete optimization
  • streaming data

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