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Human Activity Recognition from Basic Actions Using Finite State Machine

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Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 285))

Abstract

High-level human activity recognition is an important method for the automatic event detection and recognition application, such as, surveillance system and patient monitoring system. In this paper, we propose a human activity recognition method based on FSM model. The basic actions with their properties for each person in the interested area are extracted and calculated. The action stream with related features (movement, referenced location) is recognized using the predefined FSM recognizer modeling based on rational activity. Our experimental result shows a good recognition accuracy (86.96 % in average).

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Faculty of Engineering, Prince of Songkla University, Hatyai, Songkhla, 90112, Thailand

    Nattapon Noorit & Nikom Suvonvorn

Authors
  1. Nattapon Noorit
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  2. Nikom Suvonvorn
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Corresponding author

Correspondence to Nattapon Noorit .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia

    Tutut Herawan

  2. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Mustafa Mat Deris

  3. School of Information Technology, Deakin University, Burwood, Victoria, Australia

    Jemal Abawajy

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© 2014 Springer Science+Business Media Singapore

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Noorit, N., Suvonvorn, N. (2014). Human Activity Recognition from Basic Actions Using Finite State Machine. In: Herawan, T., Deris, M., Abawajy, J. (eds) Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013). Lecture Notes in Electrical Engineering, vol 285. Springer, Singapore. https://doi.org/10.1007/978-981-4585-18-7_43

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  • DOI: https://doi.org/10.1007/978-981-4585-18-7_43

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-4585-17-0

  • Online ISBN: 978-981-4585-18-7

  • eBook Packages: EngineeringEngineering (R0)

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