Abstract
This paper presents a novel technique for clustering and visualizing spatio-temporal data to analyze the navigational behavior of moving entities, such as users, virtual characters or vehicles. For testing our proposal, we developed CAST (Clustering And visualization tool for Spatio-Temporal data), a tool designed for interactively studying moving entities navigating through real as well as virtual environments. Such analysis allows one to derive information at a level of abstraction suitable to support (i) the evaluation of user spaces and (ii) the identification of the predominant navigation behavior of users. We demonstrate the effectiveness of our solution by testing the tool on data acquired by recording the movements of users while navigating through a virtual environment.
Keywords
- Virtual Environment
- Visualization Tool
- Virtual Character
- Trajectory Cluster
- Future Generation Computer System
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2009 Indian Institute of Information Technology, India
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Munaga, H., Ieronutti, L., Chittaro, L. (2009). CAST: A Novel Trajectory Clustering and Visualization Tool for Spatio-Temporal Data. In: Tiwary, U.S., Siddiqui, T.J., Radhakrishna, M., Tiwari, M.D. (eds) Proceedings of the First International Conference on Intelligent Human Computer Interaction. Springer, New Delhi. https://doi.org/10.1007/978-81-8489-203-1_15
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DOI: https://doi.org/10.1007/978-81-8489-203-1_15
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-8489-404-2
Online ISBN: 978-81-8489-203-1
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