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Comparative Analysis of 1-D HMM and 2-D HMM for Hand Motion Recognition Applications

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Book cover Progress in Intelligent Computing Techniques: Theory, Practice, and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 518))

Abstract

Hand motion recognition is an interesting field in the development of virtual reality applications through the human–computer interface. The stochastic mathematical model hidden Markov model (HMM) is used in this work. There are numerous parametric efforts in HMM for temporal pattern recognition. To overcome the recursiveness in the forward and backward procedures, dimensionality and storage problem in Markov model, 2-D HMM has been used. The experimental results show the comparison of 2-D HMM with 1-D HMM in terms of performance measures.

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Authors and Affiliations

  1. Department of ECE, Karunya University, Coimbatore, Tamil Nadu, India

    K. Martin Sagayam & D. Jude Hemanth

Authors
  1. K. Martin Sagayam
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  2. D. Jude Hemanth
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Corresponding author

Correspondence to K. Martin Sagayam .

Editor information

Editors and Affiliations

  1. National Institute of Technology, Dept. of Computer Science & Engineering National Institute of Technology, Rourkela, Odisha, India

    Pankaj Kumar Sa

  2. National Institute of Technology, Dept. of Computer Science & Engineering National Institute of Technology, Rourkela, Odisha, India

    Manmath Narayan Sahoo

  3. Universiti Malaysia Perlis (UniMAP), School of Mecahtronics Engineering Universiti Malaysia Perlis (UniMAP), Arau, Perlis, Malaysia

    M. Murugappan

  4. The University of Exeter, Lecturer The University of Exeter, Exeter, Devon, United Kingdom

    Yulei Wu

  5. National Institute of Technology, Dept. of Computer Science & Engineering National Institute of Technology, Rourkela, Odisha, India

    Banshidhar Majhi

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© 2018 Springer Nature Singapore Pte Ltd.

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Sagayam, K.M., Hemanth, D.J. (2018). Comparative Analysis of 1-D HMM and 2-D HMM for Hand Motion Recognition Applications. In: Sa, P., Sahoo, M., Murugappan, M., Wu, Y., Majhi, B. (eds) Progress in Intelligent Computing Techniques: Theory, Practice, and Applications. Advances in Intelligent Systems and Computing, vol 518. Springer, Singapore. https://doi.org/10.1007/978-981-10-3373-5_22

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  • DOI: https://doi.org/10.1007/978-981-10-3373-5_22

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3372-8

  • Online ISBN: 978-981-10-3373-5

  • eBook Packages: EngineeringEngineering (R0)

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