Sports Analytics

PoseForge: Editable Pose Analytics for AI-Assisted Sports Coaching

Shuvam Swapnil Dash, Arpit Narechania

IEEE TVCG · 2027

Video Code

Teaser for PoseForge: Editable Pose Analytics for AI-Assisted Sports Coaching

Abstract

Athletic coaching increasingly relies on video analysis, yet raw footage lacks tools to quantify motion or simulate valid technique corrections. Drawing on formative interviews with eleven cricket experts, we introduce PoseForge, a visual analytics system that extracts 3D skeletal poses from single-camera sports videos for interactive movement analysis. In a cricket batting case study, PoseForge computes interpretable kinematic metrics, compares them against scientifically derived norms, and uses an AI coach to suggest targeted adjustments.

Citation

@article{dash2027poseforge,
  author = {Dash, Shuvam Swapnil and Narechania, Arpit},
  title = {{PoseForge: Editable Pose Analytics for AI-Assisted Sports Coaching}},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  year = {2027},
  publisher = {IEEE},
  note = {To appear. Presented at IEEE VIS 2026}
}