FaceLab: Scalable Facial Performance Capture for Visual Effects

Andrus, Curtis; Ahn, Jeong Joon; Alessi, M. E.; Dib, Abdallah; Gosselin, Philippe-Henri; Thébault, Cédric; Chevallier, Louis; Romeo, Marco

doi:10.1145/3403736.3403938

Cited by 5 publications

(1 citation statement)

References 4 publications

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“…FaceLab is a system created for the 2019 film Cats [7] to drive the animation of a 3D facial rig. The system used a facial reconstruction methodology that extracts the shape, pose, and reflectance of the face.…”

Section: Facelabmentioning

confidence: 99%

A survey on the pipeline evolution of facial capture and tracking for digital humans

Vilchis

Perez-Guerrero²,

Mendez-Ruiz³

et al. 2023

Multimedia Systems

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With the introduction of concepts for virtual interaction and digital doubles, a rich scenario has been created for embodied avatars to strive. These avatars, more recently referred to as digital humans, have become a popular area of research, resulting in various techniques and methods that focus on improving the perception of their realism, fidelity, emphatic response, and interactivity. This survey aims to explore the literature and recent advancements on the key processes behind the creation and animation of digital human faces through the view of a general pipeline. The extensive review carried out in this study explores the usual data collection protocols, the main facial codification paradigms and databases, the approaches for digital human asset creation, facial tracking solutions for performance-driven animation, the solving process, and the final rendering delivery. Different quantitative evaluation methods, visual perception tests, and empathetic response evaluations for digital humans are also included in the survey. Additionally, the paper presents an updated summary of public and private frameworks for digital humans that go through the complete general pipeline presented. Finally, the condensed knowledge is discussed, inquiring into the possible direction of future developments in the field.

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Section: Facelabmentioning

confidence: 99%