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Motion capture analysis and animation rebuild using machine learning.

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remotion

Blender add-on for motion capture analysis and animation re-build using LSTM RNN. (POC)

Introduction

Remotion is a POC that allow to fix frames of motion capture animation based on previous and next frame of animation and a learning process from similar movement. All is encapsuled in a Blender add-on for a user-friendly usage.

Our method

  1. First, we train a model on correct on clean motion capture movement using a LSTM-3LR network.

  2. We take a broken animmation with movement of same type as movement trained with our network and for each x frames of broken animation we trying to predict thank to our network and learning date, the next x frames of our animation.

  3. Then we compare predicted frames with broken animations frames and if the result go over a tolerance value, we replace broken animation frames by our predicted frames.

  4. We re-do step 2 and 3 a second time but this time we trying to predict previous x frames for each x frame.

Demo

Video: Motion capture analysis and animation rebuild using LSTM RNN - Youtube

Requirements

  • Anaconda python 3 environnement
  • Keras and Tenserflow (Anaconda environnement)
  • Cuda 9.0 and cudNN (required for hardware acceleration only)
  • Blender 2.7+

License

GNU GPLv3

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Motion capture analysis and animation rebuild using machine learning.

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