Human Motion System Model Based on Real-Time Image Acquisition and Data Simulation

Authors

  • Xi Yongping Zhangjiakou University, Zhangjiakou, Hebei 075000, China
  • Yang Shengdong Zhangjiakou University, Zhangjiakou, Hebei 075000, China
  • Wang Penglong Zhangjiakou University, Zhangjiakou, Hebei 075000, China
  • Feng Yuhong Zhangjiakou University, Zhangjiakou, Hebei 075000, China

Abstract

The rapid development of video technology has gone hand-in-hand with communication technology, the development of which is a major force
driving video technology advancement and expanding its range of applications. Simultaneously, issues such as security (among others) have been
addressed and continue to attract research attention. However, the development of video technology has encountered many obstacles, one of which
concerns the capturing of motion. Hence, the purpose of this study is to conduct an in-depth investigation of motion capture technology and to discuss
how video technology and motion capture can be combined with the human body motion posture for a more accurate video recording of human
movements. Related motion nodes can further capture the human motion process, and record and analyze the human motion data. This research can
be used not only for the human motion research model, but can also be applied to various domains such as medicine, sports, and animation. The
research focus of this study is on the analysis of human body posture and images of the human body that can be collected during movement. This
is the key to the development of video technology. When collecting data on images of human movement, this article is based on the data It further
simulates the motion posture of the human body, and after many experiments, the authenticity of the data is improved.

Keywords: image acquisition; data simulation; human movement; system model

Cite As

X. Yongping, Y. Shengdong, W. Penglong, F. Yuhong, "Human Motion System Model Based on Real-Time Image
Acquisition and Data Simulation", Engineering Intelligent Systems, vol 29 no 3, pp. 175-181, 2021.


Published

2021-06-01