Synchronised Video, Motion Capture and Force Plate Dataset for Validating Markerless Human Movement Analysis
The BioCV dataset is a unique combination of synchronised multi-camera video, marker based optical motion capture, and force plate data, observing 15 healthy participants (7 males, 8 females) performing controlled and repeated motions (walking, running, jumping and hopping), as well as photogrammetry scan data for each participant. The dataset was created for the purposes of developing and validating the performance of computer vision based markerless motion capture systems with respect to marker based systems.
Authors
- Polly McGuigan (ORCID: https://orcid.org/0000-0002-3497-5151)
- Logan Wade (ORCID: https://orcid.org/0000-0002-9973-9934)
- James Bilzon (ORCID: https://orcid.org/0000-0002-6701-7603)
- Laurie Needham (ORCID: https://orcid.org/0000-0002-8675-4684)
- Murray Evans (ORCID: https://orcid.org/0009-0001-4680-8342)
- Steffi Colyer (ORCID: https://orcid.org/0000-0002-4973-6591)
- Martin Parsons (ORCID: https://orcid.org/0000-0002-4197-6857)
- Darren Cosker (ORCID: https://orcid.org/0000-0001-5177-4741)
Institutions
- Microsoft (United Kingdom) (GB)
- Berkshire Health Systems (US)
- University of Bath (GB)
- Bath Spa University (GB)
Publication Details
- Journal
- Scientific Data
- Published
- 2024-11-28
- DOI
- https://doi.org/10.1038/s41597-024-04077-3
- Citations
- 5
- Primary Topic
- Diabetic Foot Ulcer Assessment and Management
- Type
- article
- Field-Weighted Citation Impact
- 1.79
Funders
- Research Councils UK
- Engineering and Physical Sciences Research Council