Results 21 to 30 of about 3,662,643 (303)
Neural MoCon: Neural Motion Control for Physically Plausible Human Motion Capture [PDF]
Computer Vision and Pattern Recognition, 2022 Due to the visual ambiguity, purely kinematic formulations on monocular human motion capture are often physically incorrect, biomechanically implausible, and can not reconstruct accurate interactions.
Buzhen Huang +4 more
semanticscholar +1 more source
Scandinavian Journal of Medicine & Science in Sports, 2023 Markerless motion capture based on low‐cost 2‐D video analysis in combination with computer vision techniques has the potential to provide accurate analysis of running technique in both a research and clinical setting. However, the accuracy of markerless
Bas van Hooren +3 more
semanticscholar +1 more source
Journal of Biomechanics, 2023 Motion analysis is essential for assessing in-vivo human biomechanics. Marker-based motion capture is the standard to analyze human motion, but the inherent inaccuracy and practical challenges limit its utility in large-scale and real-world applications.
Ke-zhi Song +4 more
semanticscholar +1 more source
Education Sciences, 2023 Motion capture is gaining significance in educational research. Different motion capture systems (MCSs) are used in educational research for different purposes and in different ways, which creates a diversity that is difficult to monitor. The aim of this
Anna Sophia Reuter, Maike Schindler
doaj +1 more source
Motion Capture Technologies for Ergonomics: A Systematic Literature Review
Diagnostics, 2023 Muscular skeletal disorder is a difficult challenge faced by the working population. Motion capture (MoCap) is used for recording the movement of people for clinical, ergonomic and rehabilitation solutions.
S. Salisu +5 more
semanticscholar +1 more source
Bioengineering, 2023 Marker-based Optical Motion Capture (OMC) systems and associated musculoskeletal (MSK) modelling predictions offer non-invasively obtainable insights into muscle and joint loading at an in vivo level, aiding clinical decision-making.
Abhishek Dasgupta +3 more
doaj +1 more source
Healthcare applications of single camera markerless motion capture: a scoping review
PeerJ, 2022 Background Single camera markerless motion capture has the potential to facilitate at home movement assessment due to the ease of setup, portability, and affordable cost of the technology. However, it is not clear what the current healthcare applications
Bradley Scott +4 more
semanticscholar +1 more source
Inter-session repeatability of markerless motion capture gait kinematics.
Journal of Biomechanics, 2021 The clinical uptake and influence of gait analysis has been hindered by inherent limitations of marker-based motion capture systems, which have long been the standard method for the collection of gait data including kinematics.
Robert M. Kanko +3 more
semanticscholar +1 more source
The Development and Evaluation of a Fully Automated Markerless Motion Capture Workflow
bioRxiv, 2022 This study presented a fully automated deep learning based markerless motion capture workflow and evaluated its performance against marker-based motion capture during overground running, walking and counter movement jumping. Multi-view high speed (200 Hz)
L. Needham +6 more
semanticscholar +1 more source
MOTION CAPTURE WITH MEMS SENSORS
Сучасні інформаційні системи, 2023 The object of this article is the registration and analysis of human movements based on sensors. This paper presents a comparison of the basic methods of data processing from inertial micromechanical sensors to collect data a device was implemented that
Dmytro Dashkov, Oleksii Liashenko
doaj +1 more source