JARVIS-MoCap/JARVIS-HybridNet
JARVIS Markerless 3D Motion Capture Pytorch Library
This project helps researchers and scientists precisely track 3D body motion of subjects using multiple video cameras, even when subjects are partially hidden. It takes raw video footage from FLIR machine vision cameras as input and outputs detailed 3D pose estimations. This is ideal for neurobiologists, biomechanics researchers, or anyone studying animal or human movement.
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Use this if you need to perform accurate 3D motion capture in a laboratory setting with multiple cameras and are looking for a robust solution that works well despite occlusions.
Not ideal if you don't have FLIR machine vision cameras or require a solution for single-camera motion tracking.
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37
Forks
10
Language
Python
License
LGPL-2.1
Category
Last pushed
Nov 27, 2023
Commits (30d)
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