Effect of markers in training dataset for markerless applications in biomechanics

Keyphrases

• Markerless 100%
• Reflective Markers 100%
• Training Dataset 100%
• Training Image 66%
• Bony Landmarks 66%
• Motion Capture 66%
• Joint Center 66%
• Visible Marker 66%
• Highly Accurate 33%
• Viable Solutions 33%
• Rigid Body 33%
• Skin Surface 33%
• Positioning Error 33%
• Markerless Motion Capture 33%
• Inpainting 33%
• Dataset Annotation 33%
• Optical Camera 33%
• Model Training 33%
• Joint Center Estimation 33%
• Dataset Quality 33%
• Bias Modeling 33%
• Capture Model 33%
• Pose Estimation Network 33%
• Marker-based Mocap 33%
• Manually Annotated Dataset 33%
• Biomechanical Application 33%
• Human Pose Estimation Algorithm 33%

Computer Science

• Annotation 100%
• Training Dataset 100%
• Biomechanics 100%
• Reflective Marker 100%
• Training Image 66%
• Pose Estimation 66%
• Estimation Algorithm 33%
• Markerless Motion Capture 33%

Engineering

• Biomechanics 100%
• Joints (Structural Components) 100%
• Pose Estimation 66%
• Rigid Structure 33%
• Position Error 33%
• Skin Surface 33%
• Test Image 33%
• Pixel Position 33%