naveen_k
Joined 6 years ago
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Apr 18
Joined 6 years ago
The challenge is recording and syncing the motion at a higher frequency and being able to save without much drift and the performance of these landmark/gaze models is often slow.
One more option to speed it up is not to do the eye tracking at record time, just record a crop video of the face and the screen first at 60Hz and then run the model on each frame and update the metadata of the dataset.
That said, I'm definitely interested in learning more about processor-specific optimizations for EPYC. If there are server-focused equivalents to what you've mentioned that would work better than frequency capping, I'd love to explore them!
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Email: [hey] @ [naveen] . [ing]