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Object tracking explained in 3Blue1Brown style. Learn about the tracking loop, kalman filters, why occlusion breaks and one way to fix it. Try it out

129,711 Aufrufe • vor 1 Monat •via X (Twitter)

11 Kommentare

Profilbild von Ben
Benvor 1 Monat

14 box is huge tf

Profilbild von Sebastian Rojo
Sebastian Rojovor 1 Monat

You are so crack 😍😍😍

Profilbild von Alex Bodner
Alex Bodnervor 1 Monat

Thanks!

Profilbild von TheDuke
TheDukevor 1 Monat

Simulated IMU data with heading and gate analyzed. That’s what I would do.

Profilbild von Akash Dwivedi
Akash Dwivedivor 1 Monat

But the core learning from ai is ... Desisit from designing these case specific algorithms.. Just good data and learning for these and 1000 other cases. . delving in single case appears smart but doesn't scale.

Profilbild von Alex Bodner
Alex Bodnervor 1 Monat

i dont think the bitter lesson applies to everything. We still need ligthweight algorithms for a lot of use cases. A big model wont run 30 fps on an edge device, this does

Profilbild von Akash Dwivedi
Akash Dwivedivor 1 Monat

Indeed a good point ... A single fast algorithm has its merit .. the con side is disconnected from a generic web of intelligence ... Breaks at too many edge cases ... Maybe use a very small nn over there ... Many layers are possible..

Profilbild von Steve Colon
Steve Colonvor 1 Monat

What type of science or mathematics would this be .

Profilbild von Lee Hayward
Lee Haywardvor 1 Monat

Dude was never seen again!

Profilbild von Isaiah Love - Oregon
Isaiah Love - Oregonvor 1 Monat

Just say she's fat

Profilbild von Josh Madeiros
Josh Madeirosvor 1 Monat

Great explainer - Squash has been my occlusion test; two players in one box, crossing on every shot. Here's how it looks so far

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