research-article

Head Posture Recognition Based on Newton-Raphson Method

Authors:

Sun Wenzhu,

Cao Jianping,

Fu Zhanping,

Deng HaifengAuthors Info & Claims

ICCPR '20: Proceedings of the 2020 9th International Conference on Computing and Pattern Recognition

Pages 1 - 5

https://doi.org/10.1145/3436369.3436370

Published: 11 January 2021 Publication History

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Abstract

In the research of flight simulator, the head posture recognition of pilot is very important. The accuracy of head posture recognition directly affects the quality of flight simulation. In this paper, a head posture recognition method is proposed for Flight Training Simulation. Firstly, the development process and working principle of Helmet Mounted Sight (HMS) are deeply studied, then the principle of Newton-Raphson method is introduced, after that the head posture recognition method based on Newton-Raphson method is proposed. Finally, the hardware design and software workflow of head posture recognition system are given. The simulation result shows that the method has high efficiency and accuracy and is suitable for head pose recognition.

References

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Daniel Lelis Baggio, Shervin Emami, David Millan Escrive, Roy Shikrot. 2012. Mastering OpenCV with Practical Computer Vision Projects, Pack Publishing Lad, Birmingham.

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Breitenstein. 2008. Real-Time face pose estimation from Single Range Images, Harvard University

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Koichi Takahashi. Yasue Mitsukura. 2013. Head Pose Tracking Based on Optimizing Normalized Cross-Correlation, In Proceedings of the SICE Annual Conference (Sep 14-17 2013)

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Li Lingge, Caicao. 2014. Face Recognition Based on LBP and Manifold Learning, COMPUTER & DIGITAL ENGINEERING

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Index Terms

Head Posture Recognition Based on Newton-Raphson Method
1. Security and privacy
  1. Intrusion/anomaly detection and malware mitigation
    1. Intrusion detection systems
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Algorithmic game theory and mechanism design
      1. Algorithmic mechanism design

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Information

Published In

ICCPR '20: Proceedings of the 2020 9th International Conference on Computing and Pattern Recognition

October 2020

552 pages

ISBN:9781450387835

DOI:10.1145/3436369

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Beijing University of Technology

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 January 2021

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ICCPR 2020

ICCPR 2020: 2020 9th International Conference on Computing and Pattern Recognition

October 30 - November 1, 2020

Xiamen, China

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A Real-Time Hand Posture Recognition System Using Deep Neural Networks

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Gesture Recognition Method Using Sensing Blocks