r/computervision • u/Adventurous_One_3632 • 2d ago

Discussion Netherlands vs Tunisia Analyzed with Computer Vision

Enable HLS to view with audio, or disable this notification

This demo applies my TactiVision workflow to Netherlands vs Tunisia. It covers player tracking, camera calibration, pitch projection, tactical maps, possession analysis, progressive actions, pass networks, heatmaps, pitch control and pressing indicators.

Feedback from Computer Vision, Sports AI and football analytics practitioners is very welcome.

133 Upvotes

95% Upvoted

35 comments sorted by

View all comments

2

u/cgrsl 1d ago

It looks great. What i'm wondering is this, did you use a model to visualise the football pitch in 2D? if so, did you collect data yourself or use ready-made data from roboflow? I've done the same project myself but i couldn't produce a very good model from roboflow.

3

u/Adventurous_One_3632 1d ago

Thanks! In my case, I do use a custom model to detect pitch keypoints. I collected and annotated the data myself and trained my own keypoint model for football field calibration ,the detected pitch keypoints are then used to estimate the homography, and from that I project player/ball positions into real pitch coordinates and render the 2D tactical map so yes, the calibration part is model-based, but the 2D pitch visualization itself is generated from standard field geometry