Abstract
Modern graphical user interfaces support direct manipulation of objects and object groups. Current object group selection techniques such as lasso and rectangle selection can be time-consuming and error-prone. This paper presents a new approach to group selection that exploits the way human perception naturally groups objects, also known as Gestalt grouping. Based on known results from perception research, we present a novel method to group objects via models of the Gestalt principles of proximity and (curvi-)linearity. Then, we introduce several new mouse-based selection techniques that exploit these Gestalt groups. The results of a user study show that our new technique outperforms lasso and rectangle selection for object groups with an implicit structure, such as (curvi-)linear arrangements or clusters.
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Dehmeshki, H., Stuerzlinger, W. (2008). Intelligent Mouse-Based Object Group Selection. In: Butz, A., Fisher, B., Krüger, A., Olivier, P., Christie, M. (eds) Smart Graphics. SG 2008. Lecture Notes in Computer Science, vol 5166. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85412-8_4
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DOI: https://doi.org/10.1007/978-3-540-85412-8_4
Publisher Name: Springer, Berlin, Heidelberg
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