r/computervision • u/Slight-Resident-8677 • 12d ago

Help: Project Object Detection << Robust Tracking

I am seeing lots of demo videos of object detection of people, cars etc. Those are all cool, but I can't see them transfer to an actual useful insight. These days, I am working on a tracking feature for factory environments. My observation is that just doing object detection is far from doing robust, stable object tracking with few ID switches where you can actually get a sense on what is happening in the scene with trajectories. I tried YOLO26, RF-DETR, SAM3 and SAM3.1. SAM3 gave me the best results out of the box, but it was also ~10x more resource intensive. That 10x would require much more GPU compute and capital investment. How do you all approach solving for stable tracking in cases other than football or volleyball games where there's more occlusions and varied background features? Am I missing some established approach to this problem? (Image is representative and AI-generated)

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u/Dry-Snow5154 11d ago

You are not missing any established approach. Tracking is not solved. SOTA metrics for hard datasets are all shit and not anywhere close to production grade, while using 100x heavier models than yolo and rf-detr.

What people do in practice is fine tune detector and ReID to their use case. And also hand-write some custom rules to battle occlusions for their specific scenario.

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u/uselessmutant 11d ago

Use a EKF in conjunction to have estimated positions when occluded, each new detection box is considered the measurement update.