Název: Machine learning approach to automate facial expressions from physical activity
Autoři: Boukhalfi, Tarik
Desrosiers, Christian
Paquette, Eric
Citace zdrojového dokumentu: WSCG 2015: full papers proceedings: 23rd International Conference in Central Europeon Computer Graphics, Visualization and Computer Visionin co-operation with EUROGRAPHICS Association, p. 81-88.
Datum vydání: 2015
Nakladatel: Václav Skala - UNION Agency
Typ dokumentu: conferenceObject
konferenční příspěvek
URI: wscg.zcu.cz/WSCG2015/CSRN-2501.pdf
http://hdl.handle.net/11025/29354
ISBN: 978-80-86943-65-7 (print)
978-80-86943-61-9 (CD-ROM)
ISSN: 2464–4617 (print)
2464–4625 (CD-ROM)
Klíčová slova: obličejová animace;biomechanika;fyzická aktivita;strojové učení
Klíčová slova v dalším jazyce: facial animation;biomechanics;physical activity;machine learning
Abstrakt v dalším jazyce: We propose a novel approach based on machine learning to simulate facial expressions related to physical activity. Because of the various factors they involve, such as psychological and biomechanical, facial expressions are complex to model. While facial performance capture provides the best results, it is costly and difficult to use for real-time interaction during intense physical activity. A number of methods exist to automate facial animation related to speech or emotion, but there are no methods to automate facial expressions related to physical activity. This leads to unrealistic 3D characters, especially when performing intense physical activity. This research highlights the link between physical activity and facial expression, and to propose a data-driven approach providing realistic facial expressions, while leaving creative control. First, biological, mechanical, and facial expression data are captured. This information is then used to train regression trees and support vector machine (SVM) models, which predict facial expressions of virtual characters from their 3D motion. The proposed approach can be used with real-time, pre-recorded or key-framed animations, making it suitable for video games and movies as well.
Práva: © Václav Skala - UNION Agency
Vyskytuje se v kolekcích:WSCG 2015: Full Papers Proceedings

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