Image search—from thousands to billions in 20 years

  • Authors:
  • Lei Zhang;Yong Rui

  • Affiliations:
  • Microsoft Research Asia, China;Microsoft Research Asia, China

  • Venue:
  • ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) - Special Sections on the 20th Anniversary of ACM International Conference on Multimedia, Best Papers of ACM Multimedia 2012
  • Year:
  • 2013

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Abstract

This article presents a comprehensive review and analysis on image search in the past 20 years, emphasizing the challenges and opportunities brought by the astonishing increase of dataset scales from thousands to billions in the same time period, which was witnessed first-hand by the authors as active participants in this research area. Starting with a retrospective review of three stages of image search in the history, the article highlights major breakthroughs around the year 2000 in image search features, indexing methods, and commercial systems, which marked the transition from stage two to stage three. Subsequent sections describe the image search research from four important aspects: system framework, feature extraction and image representation, indexing, and big data's potential. Based on the review, the concluding section discusses open research challenges and suggests future research directions in effective visual representation, image knowledge base construction, implicit user feedback and crowdsourcing, mobile image search, and creative multimedia interfaces.