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The Perceptual Eye View: A User-Defined Method for Information Visualization

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 4551))

Abstract

With the growing volumes of data, exploring the relationships within the huge amounts of data is difficult. Information visualization uses the human perception system to assist users in analyzing complex relationships and graphical hierarchy trees used commonly to present the relationship among the data. Conventional information visualization approaches fail to consider human factors, they only provide fixed degree of detail to different users. However, different users have different perceptions. A well-known information visualization called ’Magic Eye View’ uses a three-dimensional interaction to allow the user to control the degree of detail he would like. However, it fails to consider some important focus + context features such as the smooth transition of the focus region and the global context. In this paper, we propose a novel information visualization method, called the ’Perceptual Eye View,’ by which users may control the focus points three-dimensionally enabling different users to view their user-defined degree of detail of information space and to perceive based on their own knowledge and perception. The results demonstrate that our proposed method improve the ’Magic Eye View’ by providing smooth transition of the focus region and the global context, which are important focus+context features that the ’Magic Eye View’ fails to consider.

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Julie A. Jacko

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© 2007 Springer-Verlag Berlin Heidelberg

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Wu, LH., Hsu, PY. (2007). The Perceptual Eye View: A User-Defined Method for Information Visualization. In: Jacko, J.A. (eds) Human-Computer Interaction. Interaction Platforms and Techniques. HCI 2007. Lecture Notes in Computer Science, vol 4551. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73107-8_20

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  • DOI: https://doi.org/10.1007/978-3-540-73107-8_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73106-1

  • Online ISBN: 978-3-540-73107-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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