Method evidence record
Markerless Motion Capture
Markerless motion capture infers the 3D positions and joint angles of a moving subject from video sequences using computer vision and machine learning. Pioneered by deep learning approaches such as OpenPose and MediaPipe, it eliminates the need for reflective markers or inertial sensors, making motion capture accessible and practical for real-world applications.
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Markerless Motion Capture
Taxonomic method record · process-pipeline / biomechanics
- Cao, Z., Simon, T., Wei, S. E., & Sheikh, Y. (2017). Realtime multi-person 2D pose estimation using part affinity fields. IEEE Conference on Computer Vision and Pattern Recognition (CVPR). · DOI 10.1109/CVPR.2017.143
- Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press. · URL
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