Results 1 to 10 of about 10,913 (220)

Markerless motion capture: What clinician-scientists need to know right now

JSAMS Plus, 2022
Markerless motion capture (mocap) could be the future of motion analysis. The purpose of this report was to describe our team of clinicians and scientists’ exploration of markerless mocap (Theia 3D) and share data for others to explore (link: https://osf.
Naoaki Itô, Haraldur B Sigurðsson, Kayla D Seymore   +2 more
exaly   +4 more sources

Evaluation of 3D Markerless Motion Capture Accuracy Using OpenPose With Multiple Video Cameras

Frontiers in Sports and Active Living, 2020
There is a need within human movement sciences for a markerless motion capture system, which is easy to use and sufficiently accurate to evaluate motor performance.
Kazuhiro Ueda, Arata Kimura, Yoichi Iino   +2 more
exaly   +3 more sources

Markerless vs. Marker-Based Gait Analysis: A Proof of Concept Study

Sensors, 2022
The analysis of human gait is an important tool in medicine and rehabilitation to evaluate the effects and the progression of neurological diseases resulting in neuromotor disorders.
Matteo Moro, Giorgia Marchesi, Francesca Odone   +2 more
exaly   +3 more sources

Validation of a Markerless Multi-Camera Pipeline for Bouldering Fall Kinematics [PDF]

Sensors
Indoor bouldering is a popular and rapidly growing sport in which climbers fall repeatedly from walls up to 4–5 m high, making lower-limb injuries common.
Nathan Carretier, Erwan Beurienne, Marie-Hélène Beauséjour, Lucas Gros, Claire Bruna-Rosso, Marine Dorsemaine, Michel Behr, Nicolas Bailly, Julien Clément   +8 more
doaj   +2 more sources

Evaluation of drop vertical jump kinematics and kinetics using 3D markerless motion capture in a large cohort

Frontiers in Bioengineering and Biotechnology
Introduction3D Markerless motion capture technologies have advanced significantly over the last few decades to overcome limitations of marker-based systems, which require significant cost, time, and specialization.
Daniel P Nicolella, Myer Gregory D, Nicolella Daniel P   +2 more
exaly   +3 more sources

Markerless Mouse Tracking for Social Experiments [PDF]

eneuro, 2021
Automated behavior quantification in socially interacting animals requires accurate tracking. While many methods have been very successful and highly generalizable to different settings, issues of mistaken identities and lost information on key anatomical features are common, although they can be alleviated by increased human effort in training or post-
Van Anh Le, Toni-Lee Sterley, Ning Cheng, Jaideep S. Bains, Kartikeya Murari   +4 more
openaire   +2 more sources

Applications and limitations of current markerless motion capture methods for clinical gait biomechanics [PDF]

PeerJ, 2022
Background Markerless motion capture has the potential to perform movement analysis with reduced data collection and processing time compared to marker-based methods.
Logan Wade, Laurie Needham, Polly McGuigan, James Bilzon   +3 more
doaj   +2 more sources

Inter-Device Reliability of a Three-Dimensional Markerless Motion Capture System Quantifying Elementary Movement Patterns in Humans

Journal of Functional Morphology and Kinesiology, 2023
With advancements in technology able to quantify wide-ranging features of human movement, the aim of the present study was to investigate the inter-device technological reliability of a three-dimensional markerless motion capture system (3D-MCS ...
Nicolas M. Philipp, Dimitrije Cabarkapa, Damjana V. Cabarkapa, Drake A. Eserhaut, Andrew C. Fry   +4 more
doaj   +1 more source

Examination of 2D frontal and sagittal markerless motion capture: Implications for markerless applications

PLOS ONE, 2023
This study examined if occluded joint locations, obtained from 2D markerless motion capture (single camera view), produced 2D joint angles with reduced agreement compared to visible joints, and if 2D frontal plane joint angles were usable for practical applications.
Logan Wade, Laurie Needham, Murray Evans, Polly McGuigan, Steffi Colyer, Darren Cosker, James Bilzon   +6 more
openaire   +5 more sources

Markerless human motion transfer [PDF]

ACM SIGGRAPH 2004 Sketches on - SIGGRAPH '04, 2004
In this paper we develop a computer vision-based system to transfer human motion from one subject to another. Our system uses a network of eight calibrated and synchronized cameras. We first build detailed kinematic models of the subjects based on our algorithms for extracting shape from silhouette across time [A 3D reconstruction algorithm combining ...
German K. M. Cheung, Simon Baker, Jessica K. Hodgins, Takeo Kanade   +3 more
openaire   +1 more source