Machine Learning-Based Human Movements Mimicking System for Animation and Virtual Reality

A trend, which can be noticed over the last several years, is the increasing interest to the machine learning methods in the animation and virtual reality (VR) industries to process the human motion data. The present abstract studies the possible contribution of human like machine learning simulations on human motions, which aim to improve animation and motion synthesis personalization. In this research, we propose a novel framework that utilizes camera-captured human motion data. This technique, which takes advantage of comes of motion data to simulate these animated characters movements in real time, will allow animators to create more creature-like animated figures with subtle actions as seen in real life. Additionally, in virtual reality, it links users’ movements with their avatars so the whole interaction is more engaging and realistic.