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A project where motion capture data is created based on the AI solution MediaPipe Holistic and applied to a 3D character in Blender

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DFKI-SignLanguage/sl-animation-blender

 
 

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sl-animation-blender

A project where motion capture data is created based on the AI solution MediaPipe Holistic and applied to a Daz 3D character in Blender

Prerequisites

The noted versions are the ones that were used during the project.

  • Blender 2.91.2
  • Python 3.7/3.8
  • mediapipe 0.8.3.1
  • opencv-python 4.5.1.48

Folder contents

animation_results

  • .blend file that contains a Daz 3D character with animation actions
  • exported .bvh motion capture files
  • exported .fbx version of the .blend file

blender_scripts

  • load_mp_landmarks.py, a script to create motion capture data from RBG videos. Is attached to make_bvh_files.blend
  • assign_animation_to_avatar.py, a script to map bone rotations from .bvh files to a Daz 3D character. Is attached to animate_avatar.blend that contains the prepared character

Both scripts have an instruction of how to use them at the top of the file. The easiest way to test them is to use the prepared Blender files.

mp-landmark-annotation

  • main.py, a script that analyzes video files with the MediaPipe AI, annotates all video frames and saves them in the folder annotated_images

sign_videos

  • German Sign Language video clips to capture the motion data from
  • Sign language interpreter: Mathias Schäfer

Daz 3D character

The 3D character was created in Daz Studio and has been customized with free assets. It was transferred to Blender with the Daz to Blender Bridge.

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A project where motion capture data is created based on the AI solution MediaPipe Holistic and applied to a 3D character in Blender

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