Authors:
Ciprian Paduraru
1
;
Petru-Liviu Bouruc
1
and
Alin Stefanescu
2
;
1
Affiliations:
1
Department of Computer Science, University of Bucharest, Academiei Street 14, Bucharest, Romania
;
2
Institute for Logic and Data Science, Romania
Keyword(s):
Generative AI, Body Emotions, Parametric Models, Animations.
Abstract:
Accurate and expressive representation of human emotions in 3D models remains a major challenge in various industries, including gaming, film, healthcare, virtual reality and robotics. This work aims to address this challenge by utilizing a new dataset and a set of baseline methods within an open-source framework developed to improve realism and emotional expressiveness in human 3D representations. At the center of this work is the use of a novel and diverse dataset consisting of short video clips showing people mimicking specific emotions: anger, happiness, surprise, disgust, sadness, and fear. The dataset was further processed using state-of-the-art parametric body models that accurately reproduce these emotions. The resulting 3D meshes were then integrated into a generative pose generation model capable of producing similar emotions.