본문 바로가기
  • Home

An Accurate Forward Head Posture Detection using Human Pose and Skeletal Data Learning

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2023, 28(8), pp.87-93
  • DOI : 10.9708/jksci.2023.28.08.087
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : July 4, 2023
  • Accepted : July 31, 2023
  • Published : August 31, 2023

Jong-Hyun Kim 1

1인하대학교

Accredited

ABSTRACT

In this paper, we propose a system that accurately and efficiently determines forward head posture based on network learning by analyzing the user's skeletal posture. Forward head posture syndrome is a condition in which the forward head posture is changed by keeping the neck in a bent forward position for a long time, causing pain in the back, shoulders, and lower back, and it is known that daily posture habits are more effective than surgery or drug treatment. Existing methods use convolutional neural networks using webcams, and these approaches are affected by the brightness, lighting, skin color, etc. of the image, so there is a problem that they are only performed for a specific person. To alleviate this problem, this paper extracts the skeleton from the image and learns the data corresponding to the side rather than the frontal view to find the forward head posture more efficiently and accurately than the previous method. The results show that the accuracy is improved in various experimental scenes compared to the previous method.

Citation status

* References for papers published after 2022 are currently being built.