Camera Setup and OpenPose Software without GPU for Calibration and Recording in Telerehabilitation Use

Yoram Segal, Yuval Yona, Omer Danan, Raz Birman, Ofer Hadar, Patrik Kutilek, Jan Hejda, Michaela Hourova, Pavel Kral, Lenka Lhotska, Jaromir Dolezal, Jindrich Adolf

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Home exercises are significant in the rehabilitation process of physiotherapy patients, which lack immediate feedback as to the proper movement and therefore might humper patient treatment. In this paper we are proposing an algorithm for fast tracking of human body movements performed during physiotherapeutic exercises using a simple webcam home setup and common domestically available CPU computing resources. We use OpenPose for detecting body vertices in key frames and a novel vertex tracking algorithm between video frames, which leverages encoded video Motion Vectors (MVs). We show excellent tracking accuracy between frames and x15 reduction in time, as compared to native OpenPose, which would require a Graphical Processing Unit (GPU) to perform in real time. We further provide a design and implementation of a precision camera system consisting of two cameras in the frontal and lateral direction, which were precisely positioned using a laser cross. This system will be also used to verify whether the webcam is able to record with sufficient quality to further image processing analysis. As part of this work, a camera system including supporting calibration and recording scripts was designed and implemented. The cameras triggers were synchronized by wire interconnection and set up by proposed script. In this work we synchronize two cameras and align their frames such that the OpenPose can be applied independently to each of the two channels to measure movements from two different body projections (3D).

Original languageEnglish
Title of host publication2021 9th E-Health and Bioengineering Conference, EHB 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665440004
DOIs
StatePublished - 2021
Externally publishedYes
Event9th IEEE International Conference on E-Health and Bioengineering Conference, EHB 2021 - Iasi, Romania
Duration: 18 Nov 202119 Nov 2021

Publication series

Name2021 9th E-Health and Bioengineering Conference, EHB 2021

Conference

Conference9th IEEE International Conference on E-Health and Bioengineering Conference, EHB 2021
Country/TerritoryRomania
CityIasi
Period18/11/2119/11/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Funding

ACKNOWLEDGMENT This research was supported by a grant from the Ministry of Science & Technology, Israel & The Ministry of Education, Youth and Sports of the Czech Republic. The described research was supported by the project No. LTAIZ19008 Enhancing Robotic Physiotherapeutic Treatments using Machine Learning awarded in frame of the Czech-Israeli cooperative scientific research program (Inter-Excellence MEYS CR and MOST Israel).

FundersFunder number
Czech–Israeli cooperative scientific research program
Ministry of Science & Technology, Israel & The Ministry of Education, Youth and SportsLTAIZ19008
Ministry of Science, Technology and Space

    Keywords

    • FLIR
    • Motion Vectors
    • OpenPose
    • camera calibration

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