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Virginia Tech

Calibrating Video Capture Systems To Aid Automated Analysis And Expert Rating Of Human Movement Performance

Abstract

dc:description.abstract

We propose a methodology for calibrating the activity space and the cameras involved in video capture systems for upper extremity stroke rehabilitation. We discuss an in-home stroke rehabilitation system called Semi-Automated Rehabilitation At Home System (SARAH) and a clinic-based system called Action Research Arm Test (ARAT) developed by the Interactive Neuro-Rehabilitation Lab (INR) at Virginia Tech. We propose a calibration workflow for achieving invariant video capture across multiple therapy sessions. This ensures that the captured data is less noisy. In addition, there is prior knowledge of the captured activity space and patient location in the video frames provided to the Computer Vision algorithms analyzing the captured data. Such a standardized calibration approach improved machine learning analysis of patient movements and a higher rate of agreement across multiple therapists regarding the captured patient performance. We further propose a Multi-Camera Calibration approach to perform stereo camera calibration in SARAH and ARAT capture systems to help perform a 3D reconstruction of the activity space from 2D videos. The importance of the proposed activity space and camera calibration workflows, including new research paths opened as a result of our approach, are discussed in this thesis.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Computer Science and Applications
Department dc:contributor.department
Computer Science
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Yeshala, Sai krishna
Chair dc:contributor.committeechair
  • Kelliher, Aisling
Committee members dc:contributor.committeemember
  • Gracanin, Denis
  • Ellis, Margaret O.'Neil
  • Rikakis, Thanassis

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • In Copyright
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:35226
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/110949

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Yeshala, Sai krishna. Calibrating Video Capture Systems To Aid Automated Analysis And Expert Rating Of Human Movement Performance. masters thesis, Virginia Tech, 2022. http://hdl.handle.net/10919/110949