ZooBuilder: 2D and 3D Pose Estimation for Quadrupeds Using Synthetic Data
This work addresses the challenge of creating animations for wildlife, which is incremental as it builds on existing pose estimation methods with synthetic data.
The paper tackled the problem of automating wildlife animation by developing ZooBuilder, a pipeline for 2D and 3D pose estimation of quadrupeds using synthetic data from keyframe animations, achieving motion capture data generation from wild animal videos.
This work introduces a novel strategy for generating synthetic training data for 2D and 3D pose estimation of animals using keyframe animations. With the objective to automate the process of creating animations for wildlife, we train several 2D and 3D pose estimation models with synthetic data, and put in place an end-to-end pipeline called ZooBuilder. The pipeline takes as input a video of an animal in the wild, and generates the corresponding 2D and 3D coordinates for each joint of the animal's skeleton. With this approach, we produce motion capture data that can be used to create animations for wildlife.