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OctoPocus: a dynamic guide for learning gesture-based command sets

Published: 19 October 2008 Publication History

Abstract

We describe OctoPocus, an example of a dynamic guide that combines on-screen feedforward and feedback to help users learn, execute and remember gesture sets. OctoPocus can be applied to a wide range of single-stroke gestures and recognition algorithms and helps users progress smoothly from novice to expert performance. We provide an analysis of the design space and describe the results of two experi-ments that show that OctoPocus is significantly faster and improves learning of arbitrary gestures, compared to con-ventional Help menus. It can also be adapted to a mark-based gesture set, significantly improving input time compared to a two-level, four-item Hierarchical Marking menu.

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cover image ACM Conferences
UIST '08: Proceedings of the 21st annual ACM symposium on User interface software and technology
October 2008
308 pages
ISBN:9781595939753
DOI:10.1145/1449715
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 19 October 2008

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Author Tags

  1. dynamic guides
  2. feedback
  3. feedforward
  4. gesture recognition
  5. mouse input
  6. octopocus
  7. pen input

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Overall Acceptance Rate 561 of 2,567 submissions, 22%

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  • (2024)Interaction Techniques for Comparing VideoProceedings of the 50th Graphics Interface Conference10.1145/3670947.3670948(1-13)Online publication date: 3-Jun-2024
  • (2024)ViRgilites: Multilevel Feedforward for Multimodal Interaction in VRProceedings of the ACM on Human-Computer Interaction10.1145/36586458:EICS(1-24)Online publication date: 17-Jun-2024
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