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Taxonomy and experimental evaluation of two-handed selection techniques for volumetric data

Posted on:2009-02-09Degree:Ph.DType:Dissertation
University:The University of North Carolina at CharlotteCandidate:Ulinski, Amy CatherineFull Text:PDF
GTID:1448390005951618Subject:Information Science
Abstract/Summary:
Good three-dimensional (3D) user interface design is critical for the success of 3D visualization applications. There has been little research done in designing and evaluating interaction techniques for visualizations of volumetric data. Also, interaction techniques designed and developed for polygonal data are often not suitable for volumetric data. Another issue is that most interaction techniques that have been developed are dependent on the application for which they were developed. There has been little research done in attempting to generalize these interaction techniques.;Since selection interaction is a primary component of most volumetric visualization applications, this research focuses on designing, categorizing and quantifying bimanual selection techniques for 3D volumetric data. In particular, we will do a complete analysis of the issues around Hand Cooperation (i.e., how and when the hands work together). In particular, this dissertation will: (1) Determine what factors play a role in selection of 3D volumetric data and develop a taxonomy that illustrates the relationships among these factors. (2) Design and evaluate bimanual interaction techniques for 3D volumetric data based on our classifications. (3) Develop design guidelines based on the results of the evaluations.
Keywords/Search Tags:Volumetric data, Techniques, Selection
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