A Computer Vision-Based Gesture Recognition Using Hidden Markov Model

  • Keshav SinhaEmail author
  • Rashmi Kumari
  • Annu Priya
  • Partha Paul
Conference paper


One of the unique features present in the human being is a gesture. Nowadays, the human gesture is used to interact with the computer which will reduce the workload. The gesture recognition consists of various types of human interfaces such as facial, finger, iris, hand. In this paper, we proposed a hand gesture recognition using hidden Markov model (HMM) and trajectory code word. There are various papers presented on this topic by using different methods, whereas our technique uses the four phases for recognition: (i) tracking of real-time gesture and segmentation, (ii) feature extraction using the Gaussian model, (iii) HMM likelihood for forward algorithm, and (iv) gesture recognition using Viterbi decoding. Because of using the inbuilt function of OpenCV and MATLAB, it would be very easy to develop the system. The experimental results show the accuracy of 99%, in recognition rate, whereas it is quite faster while using for real-time application.


HMM Viterbi decoding Hand recognition Gaussian model 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Keshav Sinha
    • 1
    Email author
  • Rashmi Kumari
    • 1
  • Annu Priya
    • 1
  • Partha Paul
    • 1
  1. 1.Department of Computer Science EngineeringBirla Institute of Technology, MesraRanchiIndia

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