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Visual Browsing of Large Image Databases

  • Conference paper
Advanced Machine Learning Technologies and Applications (AMLTA 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 488))

Abstract

The amount of user-generated and -contributed data, online and offline, is growing at a rapid rate. This is particularly true for visual information in form of images. On the other hand, efficient and effective tools for managing these growing repositories are relatively scarce. In this paper, we present approaches that, rather than being directly retrieval-based, allow visual interactive exploration of large image collections. We introduce the underlying methods that are being employed to effectively visualise image databases as well as the browsing operations that enable interaction. We then present the Hue Sphere Image Browser, an efficient and intuitive hierarchical image browser, including its recent ports to large multi-touch screens and to mobile devices.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Loughborough University, Loughborough, U.K.

    Gerald Schaefer

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  1. Gerald Schaefer
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Editor information

Editors and Affiliations

  1. Cairo University, Egypt

    Aboul Ella Hassanien

  2. Ain Shams University, Cairo, Egypt

    Mohamed F. Tolba

  3. Benha University, Benha, Egypt

    Ahmad Taher Azar

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Schaefer, G. (2014). Visual Browsing of Large Image Databases. In: Hassanien, A.E., Tolba, M.F., Taher Azar, A. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2014. Communications in Computer and Information Science, vol 488. Springer, Cham. https://doi.org/10.1007/978-3-319-13461-1_49

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  • DOI: https://doi.org/10.1007/978-3-319-13461-1_49

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13460-4

  • Online ISBN: 978-3-319-13461-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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