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Learning-Based Inverse Dynamics for Human Motion Analysis / Titelei/Inhaltsverzeichnis
Learning-Based Inverse Dynamics for Human Motion Analysis / Titelei/Inhaltsverzeichnis
Contents
Chapter
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Page
I–XIV
Titelei/Inhaltsverzeichnis
I–XIV
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1–14
1 Introduction
1–14
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1.1 Applications and Challenges of Inverse Dynamics
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1.2 Learning Inverse Dynamics
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1.3 Contributions
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1.4 Structure of the Thesis
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1.5 Publications
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15–22
2 Related work
15–22
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2.1 Inverse Dynamics by Physical Simulation
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2.1.1 Inverse Approaches
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2.1.2 Forward Approaches
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2.1.3 Implicit Approaches
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2.2 Learning-Based Inverse Dynamics
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2.3 Decreasing Supervision
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23–61
3 Fundamentals
23–61
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3.1 Rigid Body Motion
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3.1.1 Representation of Position
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3.1.2 Representation of Orientation
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3.1.3 Homogeneous Transformations
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3.2 Kinematics of a Rigid Body System
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3.2.1 Kinematic Trees
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3.2.2 The Denavit-Hartenberg Convention
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3.2.3 Velocity and Acceleration Kinematics
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3.3 Dynamics of a Rigid Body System
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3.3.1 TMT-Method
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3.4 Machine Learning
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3.4.1 Terminology and General Concepts
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3.4.2 Support Vector Machines
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3.4.3 Ridge Regression
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3.4.4 Random Forests
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3.4.5 Neural Networks
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3.4.6 Generalization
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3.4.7 Transfer Learning
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62–75
4 Human motion dataset
62–75
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4.1 Motion Capture and Kinematic Optimization
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4.2 Force Plate Measurements
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4.3 Estimation of Inertial Properties
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4.4 Optimization of Joint Torques
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4.5 Data Specification
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4.6 Generation of Training Data Points
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76–94
5 Supervised learning of inverse dynamics
76–94
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5.1 Methodology
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5.1.1 End-to-End Regression
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5.1.2 Multi-Stage Regression
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5.2 Experimental Evaluation
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5.2.1 Predictive Dynamics Dataset
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5.2.2 Public Dataset
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5.2.3 Application to Reconstructed Motions
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5.3 Discussion
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95–122
6 Self-supervision by dynamics-based layers
95–122
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6.1 Datasets
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6.2 Dynamics Network
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6.2.1 Forward Layer
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6.2.2 Inverse Layer
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6.2.3 Contact Loss
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6.2.4 Training Modes
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6.3 Experimental Evaluation
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6.3.1 Comparison in the Supervised Setting
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6.3.2 Semi-Supervision with Small Labeled Datasets
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6.3.3 Domain Adaptation
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6.3.4 Ablation of Input Structure
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6.3.5 Effect of Noise
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6.4 Discussion
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123–126
7 Conclusions
123–126
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127–129
a Appendix
127–129
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a.1 Evaluation Based on Additional Metrics
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a.2 Data-Driven Inverse Dynamics Optimization
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130–152
Bibliography
130–152
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Learning-Based Inverse Dynamics for Human Motion Analysis , page I - XIV
Titelei/Inhaltsverzeichnis
Autoren
Petrissa Zell
DOI
doi.org/10.51202/9783186877109-I
ISBN print: 978-3-18-387710-2
ISBN online: 978-3-18-687710-9
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doi.org/10.51202/9783186877109-I
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