May 2024 - Present
Developed a non-autoregressive transformer model for predicting human motion trajectories in hallways. Collected markerless motion capture data on 8 participants in a T-shaped hallway. Processed with C-motion software to extract key body joint information like positions, angles, velocity, and acceleration time derivatives. Preprocessed and tokenized body tracking data with NumPy/Pandas and implemented attention mechanisms to process this continuous state information using PyTorch. Evaluated model performance w/ MPJPE metric and compared against state-of-the-art STPOTR, performing about 50% better with the highest at 0.15 m error compared to STPOTR's highest at 0.3 m.
TBD