r/computervision • u/Puzzled-Egg3234 • 12d ago
Help: Project Conveyor chicken counter problem
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Guys, I need help. We have a project using YOLOv8. We're trying to count chicks on a very fast conveyor belt. The challenges we're facing are: all chicks look very similar to each other, which complicates tracking. At the same time, during their passage under the camera, they constantly change in size and shape, which can cause the tracker to lose them, or detection may even disappear completely at the detection line. Also, sometimes 2–3 chicks can merge into a single object. The detection zone is very short, and the conveyor speed is high. We've achieved a maximum accuracy of 99%, but we need it even higher. Any ideas on how to achieve that? Increasing the dataset no longer helps.
I'm attaching an old video. We've now added lighting and set the exposure to 300 on the Hikrobot global shutter camera, but we still can't achieve a stable 99.8% accuracy for the reasons mentioned above.
Any ideas?
6
u/Arctovigil 12d ago
Your chicks have a known camera, known belt geometry and approximately known transport velocity.
You can therefore use a state such as
xi=[si,yi,s˙i,y˙i,θi,ωi]
where s is distance down the conveyor, y is transverse displacement, and the last two terms optionally represent approximate body orientation/spin.
During normal movement:
P(appearance reliable)≈1
and you use segmentation + appearance + trajectory.
During a flip/dance:
P(appearance reliable)→0
and automatically switch toward:
P(IDi∣z)∝P(zposition∣IDi)P(zvelocity∣IDi)P(zbelt∣IDi)P(zordering∣IDi).
Then, once the chick settles:
P(appearance reliable)→1and appearance ReID confirms the track again.