Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications

The Study on Virtual Input Method Based on Machine Vision

Authors
Yi Xu
Corresponding Author
Yi Xu
Available Online May 2016.
DOI
10.2991/wartia-16.2016.32How to use a DOI?
Keywords
Virtual Reality, Machine Vision, Image Processing, Gesture Recognition, Template Matching
Abstract

Currently, virtual reality technology has been increasingly used in different industries. In the virtual and reality environment, the human-computer interaction device is challenged by expensive cost and restrained using environment. With the development of computer technology, using computer vision technology to solve the problem of human-computer interaction in virtual reality has become a thought used for the study the man-machine interface. This article uses the Gaussian model based on skin color in combination with improved optical flow field tracking algorithm, realizing the real-time rapid gesture tracking under complicated situations. The method can ensure high algorithm execution efficiency and detection accuracy while ensuring high robustness.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
Series
Advances in Engineering Research
Publication Date
May 2016
ISBN
978-94-6252-195-7
ISSN
2352-5401
DOI
10.2991/wartia-16.2016.32How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yi Xu
PY  - 2016/05
DA  - 2016/05
TI  - The Study on Virtual Input Method Based on Machine Vision
BT  - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
PB  - Atlantis Press
SP  - 178
EP  - 183
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-16.2016.32
DO  - 10.2991/wartia-16.2016.32
ID  - Xu2016/05
ER  -