A Virtual Mouse interface based on Two-layered Bayesian Network

Myung Cheol Roh, Sung Ju Huh, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Recently, many studies on gestural control methods for substituting for keyboard and mouse devices have been conducted because of their conveniences and intuitiveness. This paper presents a Virtual Mouse interface which is a gesture-based mouse interface and Two-layered Bayesian Network (TBN) for robust hand gesture recognition in realtime. The TBN provides robust recognition of hand gestures, as it compensates for an incorrectly recognized hand posture and its location via the preceding and following information. Experiments demonstrate that the proposed model recognizes hand gestures with a recognition rate of 93.78% and 85.15% for a simple and cluttered background, respectively.

Original languageEnglish
Title of host publication2009 Workshop on Applications of Computer Vision, WACV 2009
DOIs
Publication statusPublished - 2009
Event2009 Workshop on Applications of Computer Vision, WACV 2009 - Snowbird, UT, United States
Duration: 2009 Dec 72009 Dec 8

Publication series

Name2009 Workshop on Applications of Computer Vision, WACV 2009

Other

Other2009 Workshop on Applications of Computer Vision, WACV 2009
CountryUnited States
CitySnowbird, UT
Period09/12/709/12/8

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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  • Cite this

    Roh, M. C., Huh, S. J., & Lee, S. W. (2009). A Virtual Mouse interface based on Two-layered Bayesian Network. In 2009 Workshop on Applications of Computer Vision, WACV 2009 [5403082] (2009 Workshop on Applications of Computer Vision, WACV 2009). https://doi.org/10.1109/WACV.2009.5403082