Job Description
Computer Vision Engineer – Sports Video Analytics (Padel)
About the Project
We're building a video analytics platform for padel matches. A single camera
captures the full court, and our ML pipeline processes the footage to detect
players, track them across the match, classify shots, map positions to a 2D
court minimap, and generate match statistics.
The pipeline is working end-to-end. We need someone to help improve accuracy,
fix edge cases, and extend capabilities — not build from scratch.
What You'll Work On
- Improving player identity stability — reducing false identity mints,
cross-side swaps, and gallery contamination after occlusions
- Tuning and extending the Re-ID pipeline (appearance embeddings, cosine
distance thresholds, multi-signal fusion)
- Ball tracking accuracy improvements (small/fast object detection, Kalman
filtering)
- Homography and camera geometry refinement (PnP, temporal smoothing, lens
distortion handling)
About the Project
We're building a video analytics platform for padel matches. A single camera
captures the full court, and our ML pipeline processes the footage to detect
players, track them across the match, classify shots, map positions to a 2D
court minimap, and generate match statistics.
The pipeline is working end-to-end. We need someone to help improve accuracy,
fix edge cases, and extend capabilities — not build from scratch.
What You'll Work On
- Improving player identity stability — reducing false identity mints,
cross-side swaps, and gallery contamination after occlusions
- Tuning and extending the Re-ID pipeline (appearance embeddings, cosine
distance thresholds, multi-signal fusion)
- Ball tracking accuracy improvements (small/fast object detection, Kalman
filtering)
- Homography and camera geometry refinement (PnP, temporal smoothing, lens
distortion handling)
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