KineST: Enhancing Human Motion Tracking with Kinematics-Guided State Space Models
Analysis
This research explores a novel approach to human motion tracking, leveraging kinematics to improve performance with sparse signals. The use of state space models offers potential advantages in modeling complex temporal dependencies within motion data.
Key Takeaways
Reference
“KineST: A Kinematics-guided Spatiotemporal State Space Model for Human Motion Tracking from Sparse Signals”