A Virtual Mouse interface based on Two-layered Bayesian Network

Myung Cheol Roh; Sung Ju Huh; Seong Whan Lee

doi:10.1109/WACV.2009.5403082

A Virtual Mouse interface based on Two-layered Bayesian Network

Myung Cheol Roh, Sung Ju Huh, Seong Whan Lee

Department of Brain and Cognitive Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	2009 Workshop on Applications of Computer Vision, WACV 2009
DOIs	https://doi.org/10.1109/WACV.2009.5403082
Publication status	Published - 2009
Event	2009 Workshop on Applications of Computer Vision, WACV 2009 - Snowbird, UT, United States Duration: 2009 Dec 7 → 2009 Dec 8

Publication series

Name	2009 Workshop on Applications of Computer Vision, WACV 2009

Other

Other	2009 Workshop on Applications of Computer Vision, WACV 2009
Country	United States
City	Snowbird, UT
Period	09/12/7 → 09/12/8

ASJC Scopus subject areas

Computer Science Applications
Computer Vision and Pattern Recognition

Access to Document

10.1109/WACV.2009.5403082

Fingerprint Dive into the research topics of 'A Virtual Mouse interface based on Two-layered Bayesian Network'. Together they form a unique fingerprint.

Cite this

Roh, MC, Huh, SJ & Lee, SW 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, 2009 Workshop on Applications of Computer Vision, WACV 2009, Snowbird, UT, United States, 09/12/7. https://doi.org/10.1109/WACV.2009.5403082

@inproceedings{c28f6879019d4276b7619415cb39e746,

title = "A Virtual Mouse interface based on Two-layered Bayesian Network",

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.",

author = "Roh, {Myung Cheol} and Huh, {Sung Ju} and Lee, {Seong Whan}",

year = "2009",

doi = "10.1109/WACV.2009.5403082",

language = "English",

isbn = "9781424454976",

series = "2009 Workshop on Applications of Computer Vision, WACV 2009",

booktitle = "2009 Workshop on Applications of Computer Vision, WACV 2009",

note = "2009 Workshop on Applications of Computer Vision, WACV 2009 ; Conference date: 07-12-2009 Through 08-12-2009",

}

TY - GEN

T1 - A Virtual Mouse interface based on Two-layered Bayesian Network

AU - Roh, Myung Cheol

AU - Huh, Sung Ju

AU - Lee, Seong Whan

PY - 2009

Y1 - 2009

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

AN - SCOPUS:77951190773

SN - 9781424454976

T3 - 2009 Workshop on Applications of Computer Vision, WACV 2009

BT - 2009 Workshop on Applications of Computer Vision, WACV 2009

T2 - 2009 Workshop on Applications of Computer Vision, WACV 2009

Y2 - 7 December 2009 through 8 December 2009

ER -