Accurate videogrammetric data for human limb movement research
Paper
Paper/Presentation Title | Accurate videogrammetric data for human limb movement research |
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Presentation Type | Paper |
Authors | Chong, Albert K. (Author) and AL-Baghdadi, Jasim Ahmed Ali (Author) |
Journal or Proceedings Title | Signal and Image Processing Applications (ICSIPA) |
ERA Conference ID | 72389 |
Article Number | 67079 |
Number of Pages | 5 |
Year | 2014 |
Place of Publication | United States |
ISBN | 9781479902675 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/ICSIPA.2013.6707995 |
Web Address (URL) of Paper | https://ieeexplore.ieee.org/abstract/document/6707995 |
Conference/Event | International Conference on Signal and Image Processing Applications (ICSIPA) (2013) |
IEEE International Conference on Signal and Image Processing Applications (ICSIPA) | |
Event Details | International Conference on Signal and Image Processing Applications (ICSIPA) (2013) Event Date 08 to end of 10 Oct 2013 Event Location Melaka, Malaysia |
Event Details | IEEE International Conference on Signal and Image Processing Applications (ICSIPA) ICSIPA |
Abstract | Recently, off-the-shelf HD video cameras are recognized low-cost video capture for the study of human movements associating with sport training, sport performance evaluation, physical impairment evaluation and rehabilitation evaluation. The data required for these applications are usually dimensions, 3D distance, angular elements and speed of movement of the various body components such as the head, trunk and limbs. More complex data include isoline plots, profile and cross-section and 3D textured models of these body parts. This paper focuses on the developed techniques that are used for acquiring high accuracy data for these applications. In the paper, the results of three current case studies are provided to show the quality of the videogrammetric acquired data. The studies show that the techniques developed produce high accuracy data for various applications in movement research. |
Keywords | videogrammetric data, human limb, movement, biomechanical measurement |
ANZSRC Field of Research 2020 | 460702. Computer graphics |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Faculty of Engineering and Surveying |
Department of Surveying and Land Information | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q25x6/accurate-videogrammetric-data-for-human-limb-movement-research
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