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Articles Tagged: Displays and imagers

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Need for perceptual display hierarchies in visualization

The advent of computers with high processing power has led to the generation of large, multidimensional collections of data. Visualization lends itself well to the challenge of exploring and analyzing these information spaces by harnessing the strengths of the human visual system. Most visualization techniques are based on the assumption that the display device has sufficient resolution, and that our visual acuity is adequate for completing the analysis tasks. However, this may not be true, particularly for specialized display devices (e.g., PDAs or large-format projection walls).

In this article, we propose to: (1) determine the amount of information a particular display environment can encode; (2) design visualizations that maximize the information they represent relative to this upper-limit; and (3) dynamically update a visualization when the display environment changes to continue to maintain high levels of information content. To our knowledge, there are no visualization systems that do this type of information addition/removal based on perceptual guidelines. However, there are systems that attempt to increase or decrease the amount of information based on some level-of-detail or zooming rules. For example, semantic zooming tags objects with "details" and adds or removes them as the user zooms in and out. Furnas's original fisheye lens system [9] used semantic details to determine how much zoom was necessary to include certain details. Thus, while zooming for detail, you see not only a more detailed graphic representation, but also more text details (e.g., more street names on the zoomed-in portion of a map). Level-of-detail hierarchies have also been used in computer graphics to reduce geometric complexity where full resolution models are unnecessary and can be replaced with low-detail models where the resulting error cannot be easily recognized. Our approach is motivated by all these ideas, but our key contribution is that we use human perception constraints to define when to add or remove information.

By Amit Prakash Sawant, Christopher G. Healey, March 2007

PDF | HTML | In the Digital Library