ArticlePloS one2023
Examination of 2D frontal and sagittal markerless motion capture: Implications for markerless applications.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Accuracy and Validity of 3D Markerless Motion Capture Compared to Marker-Based Systems for Lower-Limb Biomechanical Assessment: A Systematic Review.Sensors (Basel, Switzerland) · 2026Pooled it
- Agreement between markerless and marker-based motion capture for knee kinematics and kinetics during functional activities in knee osteoarthritis.Osteoarthritis and cartilage open · 2026Article
- Phase Segmentation and Phase-Specific Kinematic Feature Extraction of Hurdle Clearance Based on Monocular Video and Markerless Pose Estimation.Sensors (Basel, Switzerland) · 2026Article
- Comparative Analysis of Markerless Motion-Capture Models for Assessing Football Kinematics During 30 m Long-Pass Tasks.Sensors (Basel, Switzerland) · 2026Article
- Verification of Markerless Gait Analysis: Multi-Camera and Single-Camera Approaches in Comparison to Marker-Based Gait Analysis.Medicina (Kaunas, Lithuania) · 2026Article
- Mechanical work derived using markerless motion capture provides a valid indication of acute neuromuscular fatigue in tennis.PloS one · 2026Article
- Gait assessment using a 2D video-based pose estimation app in comparison to a markerless motion capture system in subjects with osteoarthritis of the knee - a pilot study.Frontiers in bioengineering and biotechnology · 2026Article
- Generating synthetic images of human skeletal motion for pose and kinematics estimation tasks.Scientific data · 2025Article
- Multimodal Motion Capture Toolbox for Enhanced Analysis of Intersegmental Coordination in Children with Cerebral Palsy and Typically Developing.Journal of visualized experiments : JoVE · 2025Article
- Assessing single camera markerless motion capture with OpenSim inverse kinematics during upper limb activities of daily living.International biomechanics · 2025Article
- In Vivo Assessment of Ankle Stability During Dynamic Exercises: Scoping Review.Healthcare (Basel, Switzerland) · 2025Review
- Integrative Field-Based Health and Performance Research: A Narrative Review on Experimental Methods and Logistics to Conduct Competition and Training Camp Studies in Athletes.Sports medicine (Auckland, N.Z.) · 2025Review
- Influence of the Camera Viewing Angle on OpenPose Validity in Motion Analysis.Sensors (Basel, Switzerland) · 2025Article
- A Comprehensive Review of Vision-Based Sensor Systems for Human Gait Analysis.Sensors (Basel, Switzerland) · 2025Review
- Reliability assessment of markerless technologies in biomechanical motion analysis: a performance comparison.Frontiers in sports and active living · 2025Article
- Synchronised Video, Motion Capture and Force Plate Dataset for Validating Markerless Human Movement Analysis.Scientific data · 2024Article
- Gait data from 51 healthy participants with motion capture, inertial measurement units, and computer vision.Data in brief · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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. Fifteen healthy participants performed over-ground walking whilst recorded by fifteen marker-based cameras and two machine vision cameras (frontal and sagittal plane). Repeated measures Bland-Altman analysis illustrated that markerless standard deviation of bias and limits of agreement for the occluded-side hip and knee joint angles in the sagittal plane were double that of the camera-side (visible) hip and knee. Camera-side sagittal plane knee and hip angles were near or within marker-based error values previously observed. While frontal plane limits of agreement accounted for 35-46% of total range of motion at the hip and knee, Bland-Altman bias and limits of agreement (-4.6-1.6 ± 3.7-4.2˚) were actually similar to previously reported marker-based error values. This was not true for the ankle, where the limits of agreement (± 12˚) were still too high for practical applications. Our results add to previous literature, highlighting shortcomings of current pose estimation algorithms and labelled datasets. As such, this paper finishes by reviewing methods for creating anatomically accurate markerless training data using marker-based motion capture data.
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