A virtual mouse interface with a two-layered Bayesian network

Myung Cheol Roh, Dongoh Kang, Sungju Huh, Seong Whan Lee

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


During the last decade, many natural interaction methods between human and computer have been introduced. They were developed for substitutions of keyboard and mouse devices so that they provide convenient interfaces. Recently, many studies on vision based gestural control methods for Human-Computer Interaction (HCI) have been attracted attention because of their convenience and simpleness. Two of the key issues in these kinds of interfaces are robustness and real-time processing. This paper presents a hand gesture based virtual mouse interface and Two-layer Bayesian Network (TBN) for robust hand gesture recognition in real-time. The TBN provides an efficient framework to infer hand postures and gestures not only from information at the current time frame, but also from the preceding and following information, so that it compensates for erroneous postures and its locations under cluttered background environment. Experiments demonstrated that the proposed model recognized hand gestures with a recognition rate of 93.76 % and 85.15 % on simple and cluttered background video data, respectively, and outperformed previous methods: Hidden Markov Model (HMM), Finite State Machine (FSM).

Original languageEnglish
Pages (from-to)1615-1638
Number of pages24
JournalMultimedia Tools and Applications
Issue number2
Publication statusPublished - 2017 Jan 1

Bibliographical note

Funding Information:
This work was partly supported by the ICT R&D program of MSIP/IITP [B0101-15-0552 , Development of Predictive Visual Intelligence Technology] and also supported by the Implementation of Technologies for Identification, Behavior, and Location of Human based on Sensor Network Fusion Program through the Ministry of Trade, Industry and Energy (Grant No. 10041629).

Publisher Copyright:
© 2015, Springer Science+Business Media New York.


  • Hand gesture recognition
  • Two-layer Bayesian network
  • Virtual mouse interface

ASJC Scopus subject areas

  • Software
  • Media Technology
  • Hardware and Architecture
  • Computer Networks and Communications


Dive into the research topics of 'A virtual mouse interface with a two-layered Bayesian network'. Together they form a unique fingerprint.

Cite this