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 language | English |
|---|---|
| Title of host publication | 2009 Workshop on Applications of Computer Vision, WACV 2009 |
| DOIs | |
| Publication status | Published - 2009 Dec 1 |
| Event | 2009 Workshop on Applications of Computer Vision, WACV 2009 - Snowbird, UT, United States Duration: 2009 Dec 7 → 2009 Dec 8 |
Other
| Other | 2009 Workshop on Applications of Computer Vision, WACV 2009 |
|---|---|
| Country | United States |
| City | Snowbird, UT |
| Period | 09/12/7 → 09/12/8 |
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ASJC Scopus subject areas
- Computer Science Applications
- Computer Vision and Pattern Recognition
Cite this
A Virtual Mouse interface based on Two-layered Bayesian Network. / Roh, Myung Cheol; Huh, Sung J.; Lee, Seong Whan.
2009 Workshop on Applications of Computer Vision, WACV 2009. 2009. 5403082.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A Virtual Mouse interface based on Two-layered Bayesian Network
AU - Roh, Myung Cheol
AU - Huh, Sung J.
AU - Lee, Seong Whan
PY - 2009/12/1
Y1 - 2009/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=77951190773&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77951190773&partnerID=8YFLogxK
U2 - 10.1109/WACV.2009.5403082
DO - 10.1109/WACV.2009.5403082
M3 - Conference contribution
SN - 9781424454976
BT - 2009 Workshop on Applications of Computer Vision, WACV 2009
ER -