A Study of the Frameworks for Digital Humans: Analyzing Facial Tracking evolution and New Research Directions with AI

Carlos Vilchis, Miguel Gonzalez-Mendoza, Leonardo Chang, Sergio A. Navarro-Tuch, Gilberto Ochoa Ruiz, Isaac Rudomin

2022

Abstract

There actual scenario of techniques and methods to improve our perception of digitals humans is mostly oriented to increase alikeness and interactivity inside a helpful workflow. Breakthrough milestones have been achieved to improve facial expression recognition systems thanks to the effectiveness of Deep Neural Networks. This survey analyzes all the open and fully integrated frameworks (deep learning-based or not) available today. All of those can be replicated by peers to analyze their effectiveness and efficiency in real-time environments. Also, we present an overview analysis of present-day environments for digital humans that use state-of-the-art facial tracking and animation retargeting to settle a direction on the future steps in our research objectives in this field.

Paper Citation

in Harvard Style

Vilchis C., Gonzalez-Mendoza M., Chang L., Navarro-Tuch S., Ruiz G. and Rudomin I. (2022). A Study of the Frameworks for Digital Humans: Analyzing Facial Tracking evolution and New Research Directions with AI. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 2: HUCAPP; ISBN 978-989-758-555-5, SciTePress, pages 154-162. DOI: 10.5220/0010823600003124

in Bibtex Style

@conference{hucapp22,
author={Carlos Vilchis and Miguel Gonzalez-Mendoza and Leonardo Chang and Sergio A. Navarro-Tuch and Gilberto Ochoa Ruiz and Isaac Rudomin},
title={A Study of the Frameworks for Digital Humans: Analyzing Facial Tracking evolution and New Research Directions with AI},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 2: HUCAPP},
year={2022},
pages={154-162},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010823600003124},
isbn={978-989-758-555-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 2: HUCAPP
TI - A Study of the Frameworks for Digital Humans: Analyzing Facial Tracking evolution and New Research Directions with AI
SN - 978-989-758-555-5
AU - Vilchis C.
AU - Gonzalez-Mendoza M.
AU - Chang L.
AU - Navarro-Tuch S.
AU - Ruiz G.
AU - Rudomin I.
PY - 2022
SP - 154
EP - 162
DO - 10.5220/0010823600003124
PB - SciTePress