Results 151 to 160 of about 8,152 (183)

Using markerless motion capture and musculoskeletal models: An evaluation of joint kinematics. [PDF]

Technol Health Care
Auer S, Süß F, Dendorfer S.
europepmc   +1 more source

Comparison of gait deviation index (GDI) and gait variability index (GVI) measured by marker-based and markerless motion capture systems in children with cerebral palsy (CP). [PDF]

Gait Posture
Poomulna J, Knarr BA, Dutt V, Kingston DC.   +3 more
europepmc   +1 more source

Feasibility of using low-cost markerless motion capture for assessing functional outcomes after lower extremity musculoskeletal cancer surgery. [PDF]

PLoS One
Furtado S, Galna B, Godfrey A, Rochester L, Gerrand C.   +4 more
europepmc   +1 more source

Evaluation of the Margin of Stability during Gait Initiation in Young Healthy Adults, Elderly Healthy Adults and Patients with Parkinson's Disease: A Comparison of Force Plate and Markerless Motion Capture Systems. [PDF]

Sensors (Basel)
Simonet A, Fourcade P, Loete F, Delafontaine A, Yiou E.   +4 more
europepmc   +1 more source

3D Motion Capture of Markerless Hands

3D Motion Capture of Markerless Hands
openaire  

MacAction: Realistic 3D macaque body animation based on multi-camera markerless motion capture

Martini LM, Bognár A, Vogels R, Giese MA.   +3 more
europepmc   +1 more source

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Validation of pitchAI ^TM markerless motion capture using marker-based 3D motion capture

Sports Biomechanics, 2022
This study sought to compare and validate baseball pitching mechanics, including joint angles and spatiotemporal parameters, from a single camera markerless motion capture solution with a 3D optical marker-based system. Ten healthy pitchers threw 2-3 maximum effort fastballs while concurrently using marker-based optical capture and pitchAITM ...
Tyler J. Dobos, Ryan W. G. Bench, Colin D. McKinnon, Anthony Brady, Kyle J. Boddy, Michael W. R. Holmes, Michael W. L. Sonne   +6 more
openaire   +2 more sources

Markerless Motion Capture with unsynchronized moving cameras

2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009
In this work we present an approach for markerless motion capture (MoCap) of articulated objects, which are recorded with multiple unsynchronized moving cameras. Instead of using fixed (and expensive) hardware synchronized cameras, this approach allows us to track people with off-the-shelf handheld video cameras.
Hasler, N., Rosenhahn, B., Thormählen, T., Wand, M., Gall, J., Seidel, H. ; https://orcid.org/0000-0002-1343-8613   +5 more
openaire   +2 more sources

Markerless Motion Capture using Multiple Cameras

Computer Vision for Interactive and Intelligent Environment (CVIIE'05), 2006
Motion capture has important applications in different areas such as biomechanics, computer animation, and human-computer interaction. Current motion capture methods use passive markers that are attached to different body parts of the subject and are therefore intrusive in nature.
A. Sundaresan, R. Chellappa
openaire   +1 more source