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

    4 Citations (Scopus)

    Abstract

    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
    Volume76
    Issue number2
    DOIs
    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.

    Keywords

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

    ASJC Scopus subject areas

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

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