Multimedia Tools and Applications

, Volume 69, Issue 2, pp 539–567 | Cite as

Retrieval of high-dimensional visual data: current state, trends and challenges ahead

  • Antonio Foncubierta-Rodríguez
  • Henning Müller
  • Adrien Depeursinge


Information retrieval algorithms have changed the way we manage and use various data sources, such as images, music or multimedia collections. First, free text information of documents from varying sources became accessible in addition to structured data in databases, initially for exact search and then for more probabilistic models. Novel approaches enable content-based visual search of images using computerized image analysis making visual image content searchable without requiring high quality manual annotations. Other multimedia data followed such as video and music retrieval, sometimes based on techniques such as extracting objects and classifying genre. 3D (surface) objects and solid textures have also been produced in quickly increasing quantities, for example in medical tomographic imaging. For these two types of 3D information sources, systems have become available to characterize the objects or textures and search for similar visual content in large databases. With 3D moving sequences (i.e., 4D), in particular medical imaging, even higher-dimensional data have become available for analysis and retrieval and currently present many multimedia retrieval challenges.

This article systematically reviews current techniques in various fields of 3D and 4D visual information retrieval and analyses the currently dominating application areas. The employed techniques are analysed and regrouped to highlight similarities and complementarities among them in order to guide the choice of optimal approaches for new 3D and 4D retrieval problems. Opportunities for future applications conclude the article. 3D or higher-dimensional visual information retrieval is expected to grow quickly in the coming years and in this respect this article can serve as a basis for designing new applications.


3-dimensional objects Visual information retrieval 3D retrieval 4D retrieval High-dimensional objects 



This work was partially supported by the Swiss National Science Foundation (FNS) in the MANY project (grant 205321–130046), the EU 7th Framework Program in the context of the Khresmoi project (FP7–257528), and the Center for Biomedical Imaging (CIBM).


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Antonio Foncubierta-Rodríguez
    • 1
  • Henning Müller
    • 1
  • Adrien Depeursinge
    • 1
  1. 1.University of Applied Sciences Western Switzerland (HES–SO)SierreSwitzerland

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