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

Conference paper
First Online:
Part of the Advances in Intelligent Systems and Computing book series (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.

Keywords

Hand motion recognition HCI HMM 1-D HMM 2-D HMM 
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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of ECEKarunya UniversityCoimbatoreIndia

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