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

K Martin Sagayam,D Jude Hemanth

doi:10.1007/978-981-10-3373-5_22

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

K Martin Sagayam, D Jude Hemanth

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

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Publication Date: Jul 13, 2017

Citations: 5

Affiliation: Karunya University

#Hidden Markov Model #Hand Motion Recognition + Show 8 more

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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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