In AR, it is necessary to manage virtual 3D objects in space. In real life, we ​​use our hands which have 6 DoF and fingers for fine movements. The need for touchless interaction creates an opportunity to take advantage of hand movements and gestures.

HandyTrack - HPC for Hand Gesture Dataset Generation and Deep Learning Training for Detection & Tracking is dedicated to Artificial Intelligence and specifically to Computer Vision and Machine Learning applied to the use of HPC for training neural networks and for generating data based on 3D models in order to reduce the time required for training algorithms and allow for more accurate performance in hand gesture recognition and tracking.