An automated method to extract three-dimensional position data using an infrared time-of-flight camera

DUNN, Marcus, PAVAN, Davide, RAMIREZ, Paul, RAVA, Silvia and ATIQAH, Sharin (2018). An automated method to extract three-dimensional position data using an infrared time-of-flight camera. Proceedings, 2 (6), 502-207.

Dunn-AutomatedMethodToExtract3DPositionData(VoR).pdf - Published Version
Creative Commons Attribution.

Download (2MB) | Preview
Official URL:
Link to published version::


Traditional motion capture systems can be prohibitive in healthcare settings from time, cost, space and user-expertise perspectives. Ideally, movement analysis technologies for healthcare should be low-cost, quick, simple and usable in small spaces. This study demonstrates a simple, low-cost and close-range time-of-flight depth-camera system, for automatic gait analysis. A method to automatically track three-dimensional position and orientation of retro-reflective marker-triads in real-time was developed. A marker-triad was applied to a participant (self-selected walking pace): thigh angle (wrt. global-vertical) was calculated. Trials were concurrently recorded using a motion capture system. Root-mean-square error was 2.5°, 1.3° and 2.2° for depth-camera distances of 0.8 m, 1.1 m and 1.4 m respectively. Results indicate that walking distances of 1.1 m are optimal for the current system. Further development and investigation into potential healthcare applications (e.g., low-cost, close-range gait analysis) is warranted.

Item Type: Article
Additional Information: Presented at the 12th Conference of the International Sports Engineering Association, Brisbane, Queensland, Australia, 26–28 March 2018.
Research Institute, Centre or Group - Does NOT include content added after October 2018: Centre for Sports Engineering Research
Identification Number:
Page Range: 502-207
Depositing User: Marcus Dunn
Date Deposited: 12 Feb 2018 12:14
Last Modified: 18 Mar 2021 01:21

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics