
Worker Posture Analysis
Evaluating computer vision-based markerless motion capture systems for real-world worker posture analysis and ergonomic assessment.
Research exploring the intersection of computer vision, deep learning, and biomechanical analysis.

Evaluating computer vision-based markerless motion capture systems for real-world worker posture analysis and ergonomic assessment.

A pose-to-kinematics framework that transforms 3D joint positions from markerless pose estimation into clinically relevant, ISB-standard biomechanical joint angles using a transformer-based mapping architecture.
A large-scale 3D pose estimation dataset of 5,966 professional tennis serves from broadcast video, enabling biomechanical analysis, player classification, and performance prediction at unprecedented scale.

A deep learning approach for predicting pediatric Crohn's disease from histopathological whole slide images, with investigation of inter-site generalizability and site-specific artifact mitigation.