Deep Learning requires tremendous amounts of data, while acquiring real-world data is tedious. A state-of-the-art approach is to augment data that aids in training AI. This project investigates the opportunity to generate improved data using a physiological model of an animal.
The goal is to generate IMU data using a physiological kinematic locomotion model. Real-world data comprising IMU data and videos from animals such as horses, goats, and sheep can be used to evaluate the approach.
20% Theory, 60% Simulations, 20%Writing
Jacob Kamminga, email@example.com, room ZI5011