ArticleSensors (Basel, Switzerland)2024
Accuracy Evaluation of 3D Pose Reconstruction Algorithms Through Stereo Camera Information Fusion for Physical Exercises with MediaPipe Pose.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Perception, assessment, and coaching: a systematic review and taxonomy of computer vision-based physical rehabilitation techniques.Frontiers in rehabilitation sciences · 2026Pooled it
- Smartphone-based real-time feedback to suppress trunk compensation for unsupervised upper limb rehabilitation in patients with brain disorders.Journal of neuroengineering and rehabilitation · 2026Trial
- Markerless On-Device Detection of Compensatory Movement Patterns in Upper-Limb Rehabilitation Exercises from Monocular RGB Video: A Validation Study in Healthy Adults.Sensors (Basel, Switzerland) · 2026Article
- Optimizing camera placement in multi-view markerless motion capture: a validation study against gold-standard kinematics for static and dynamic tasks.BMC research notes · 2026Article
- Accurate estimation of hip range of motion using MediaPipe and inertial sensors with machine learning models.BMC musculoskeletal disorders · 2026Article
- Utilizing an Augmented Reality Headset to Accurately Quantify Lower Extremity Function in Parkinson's Disease.Sensors (Basel, Switzerland) · 2026Article
- Tactile Sensor-Based Body Center of Pressure Estimation System Using Supervised Deep Learning Models.Sensors (Basel, Switzerland) · 2026Article
- A Sliding Window-Based CNN-BiGRU Approach for Human Skeletal Pose Estimation Using mmWave Radar.Sensors (Basel, Switzerland) · 2025Article
- Development of a MediaPipe-based framework for biomechanical quantification of table tennis forehand strokes.Frontiers in sports and active living · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
In recent years, significant research has been conducted on video-based human pose estimation (HPE). While monocular two-dimensional (2D) HPE has been shown to achieve high performance, monocular three-dimensional (3D) HPE poses a more challenging problem. However, since human motion happens in a 3D space, 3D HPE offers a more accurate representation of the human, granting increased usability for complex tasks like analysis of physical exercise. We propose a method based on MediaPipe Pose, 2D HPE on stereo cameras and a fusion algorithm without prior stereo calibration to reconstruct 3D poses, combining the advantages of high accuracy in 2D HPE with the increased usability of 3D coordinates. We evaluate this method on a self-recorded database focused on physical exercise to research what accuracy can be achieved and whether this accuracy is sufficient to recognize errors in exercise performance. We find that our method achieves significantly improved performance compared to monocular 3D HPE (median RMSE of 30.1 compared to 56.3,
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.