Motion primitives for designing flexible gesture set in human-robot interface

Suwon Shon, Jounghoon Beh, Cheoljong Yang, David K. Han, Hanseok Ko

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

    6 Citations (Scopus)

    Abstract

    This paper proposes motion primitives for designing a gesture set in a gesture recognition system as Human-Robot Interface (HRI). Based on statistical analyses of angular tendency of hand movements in sign languages and hand motions in practical gestures, we construct four motion primitives as building blocks for basic hand motions. By combining these motion primitives, we design a discernable 'fundamental hand motion set' toward improving machine based hand signal recognition. Novelty of combining the proposed motion primitives is demonstrated by a 'fundamental hand motion set' recognizer based on Hidden Markov Model (HMM). The recognition system shows 99.40% recognition rate on the proposed language set. For connected recognition of the 'fundamental motion set', the recognition system shows 97.95% recognition rate. The results validate that using the proposed motion primitives ensures flexibility and discernability of a gesture set. It is thus promising candidate for standardization when designing gesture sets for human-robot interface.

    Original languageEnglish
    Title of host publicationICCAS 2011 - 2011 11th International Conference on Control, Automation and Systems
    Pages1501-1504
    Number of pages4
    Publication statusPublished - 2011
    Event2011 11th International Conference on Control, Automation and Systems, ICCAS 2011 - Gyeonggi-do, Korea, Republic of
    Duration: 2011 Oct 262011 Oct 29

    Publication series

    NameInternational Conference on Control, Automation and Systems
    ISSN (Print)1598-7833

    Other

    Other2011 11th International Conference on Control, Automation and Systems, ICCAS 2011
    Country/TerritoryKorea, Republic of
    CityGyeonggi-do
    Period11/10/2611/10/29

    Keywords

    • HMM
    • HRI
    • gesture recognition

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Science Applications
    • Control and Systems Engineering
    • Electrical and Electronic Engineering

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