Intelligent Mouse-Based Object Group Selection

  • Authors:
  • Hoda Dehmeshki;Wolfgang Stuerzlinger

  • Affiliations:
  • Department of Computer Science and Engineering, York University, Toronto, Canada;Department of Computer Science and Engineering, York University, Toronto, Canada

  • Venue:
  • SG '08 Proceedings of the 9th international symposium on Smart Graphics
  • Year:
  • 2008

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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.