Serial Skeletal Detection using a Kalman Filter in Combination with OpenPose

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Abstract

The use of OpenPose for gait analysis is highly anticipated as a cost-effective and easy-to-implement method. However, it can sometimes fail to accurately detect skeletal structures, limiting its ability to perform high-precision analysis. Therefore, in this paper, we propose a real-time correction method by combining OpenPose with the Kalman filter for sequential processing. We demonstrate the effectiveness of this approach by comparing the corrected knee joint angles with those obtained from 3D motion capture data.

Original languageEnglish
Title of host publication2024 International Conference on Electronics, Information, and Communication, ICEIC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350371888
DOIs
Publication statusPublished - 2024
Event2024 International Conference on Electronics, Information, and Communication, ICEIC 2024 - Taipei, Taiwan, Province of China
Duration: 28 Jan 202431 Jan 2024

Publication series

Name2024 International Conference on Electronics, Information, and Communication, ICEIC 2024

Conference

Conference2024 International Conference on Electronics, Information, and Communication, ICEIC 2024
Country/TerritoryTaiwan, Province of China
CityTaipei
Period28/01/2431/01/24

Keywords

  • Gait Analysis
  • Kalman Filter
  • OpenPose
  • Skeleton Detection
  • Video Processing

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