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Variations on a fuzzy logic gesture recognition algorithm

Published: 02 September 2004 Publication History

Abstract

Web-cam based gesture recognition systems for home use are becoming more viable. A modification to an algorithm developed by Bimber yields low failure rates for wand motions tested against three sets of gestures. Additionally, the speed at which a gesture is performed does not affect its recognition rate, though the gesture's orientation does.

References

[1]
Bimber, O. Continuous 6D Gesture Recognition: A Fuzzy-Logic Approach. Proceedings of 7-th International Conference in Central Europe on Computer Graphics, Visualization and Interactive Digital Media (WSCG'99), 1, (1999), 24--30.
[2]
Cao, X., Balakrishnan, Ravin. Vision Wand: Interaction Techniques for Large Displays using a Passive Wand Tracked in 3D. Proceedings of the 16th annual ACM symposium on User interface software and technology, (2003), 173--18

Cited By

View all
  • (2009)gRmobileProceedings of the 2009 VIII Brazilian Symposium on Games and Digital Entertainment10.1109/SBGAMES.2009.24(141-150)Online publication date: 8-Oct-2009
  • (2006)Interval Fuzzy Rule-Based Hand Gesture RecognitionProceedings of the 12th GAMM - IMACS International Symposium on Scientific Computing, Computer Arithmetic and Validated Numerics10.1109/SCAN.2006.25Online publication date: 26-Sep-2006

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Mark L Wambach

Tracking human gestures in three dimensions (3D), and using that information to meaningfully interact with computers, has become an enticing exercise. Bimber [1] provided these authors with the inspiration to improve on his algorithms and means of tracking wand movement. Such wand movement could be used to interact with certain computer games. Bimber's method included a six-degree of freedom (6DOF) means to concisely record data about change in location in 3D, as well as the change of orientation of the object being tracked. Sequential samples of these changes could be saved to represent particular meaningful motions. Sets of this type of data are designated to represent various gestures. Fuzzy logic is then applied, comparing the representative data to data collected from someone whose motions are being tracked. A close enough match is determined to be a meaningful gesture. The alterations proposed by the authors included simplifying the type of data being collected (orientation only), changing Bimber's weighting formula, and applying both of these changes at once. The number of experiments was somewhat limited, and the ability to gather sample data was sometimes affected by restrictions of the devices sensing visual motion. The most interesting result of this study is that standard data that was collected by one device (modeling a particular meaningful gesture) could be used successfully in identifying gestures tracked by a different device. The tests cited in this paper are minimal, and conclusions are intended to spur more research. Portions of the paper will make sense to the average reader. Interpretation of the authors' methodology, understanding the reasons behind the modification of data collection and its interpretation, and interpretation of the figure-based data are only feasible for those familiar with Bimber's approach to recognizing gestures. This paper is probably only of interest to those planning a larger, related study. Online Computing Reviews Service

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cover image ACM Other conferences
ACE '04: Proceedings of the 2004 ACM SIGCHI International Conference on Advances in computer entertainment technology
September 2004
368 pages
ISBN:1581138822
DOI:10.1145/1067343
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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 September 2004

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Author Tags

  1. control
  2. fuzzy logic
  3. games
  4. gesture recognition
  5. wand

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ACE04

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Cited By

View all
  • (2009)gRmobileProceedings of the 2009 VIII Brazilian Symposium on Games and Digital Entertainment10.1109/SBGAMES.2009.24(141-150)Online publication date: 8-Oct-2009
  • (2006)Interval Fuzzy Rule-Based Hand Gesture RecognitionProceedings of the 12th GAMM - IMACS International Symposium on Scientific Computing, Computer Arithmetic and Validated Numerics10.1109/SCAN.2006.25Online publication date: 26-Sep-2006

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