Název:	Transferring 3D facial expressions from adults to children
Autoři:	Alomar, Antonia Morales, Araceli Porras, Antonio R. Linguraru, Marius G. Piella, Gemma Sukno, Federico
Citace zdrojového dokumentu:	WSCG 2022: full papers proceedings: 30. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 109-118.
Datum vydání:	2022
Nakladatel:	Václav Skala - UNION Agency
Typ dokumentu:	conferenceObject
URI:	http://hdl.handle.net/11025/49584
ISBN:	978-80-86943-33-6
ISSN:	2464-4617
Klíčová slova:	dětské výrazy obličeje;bi-lineární model;automatická neutralizace skenování;přenos obličeje
Klíčová slova v dalším jazyce:	baby facial expressions;bi-linear model;automatic scan neutralization;face transfer
Abstrakt v dalším jazyce:	Diagnosis of craniofacial conditions is shifting towards pre- and peri-natal stages, since early assessment has shown to be crucial for the effective treatment of functional and developmental aspects of children. 3D Morphable Models are a valuable tool for such evaluation. However, limited data availability on 3D newborn geometry, and highly variable imaging environments, challenge the construction of 3D baby face models. Our hypothesis is that constructing a bi-linear baby face model that allows identity and expression decoupling, enables to improve craniofacial and brain function assessments. Thus, given that adult and infants facial expression configurations are very similar and that 3D facial expressions in babies are difficult to be scanned in a controlled manner, we propose transferring the facial expressions from the available FaceWarehouse (FW) database to baby scans, to construct a baby-specific bi-linear expression model. First, we defined a spatial mapping between the BabyFM and the FW. Then, we propose an automatic neutralization to remove the expressions from the facial scans. Finally, we apply expression transfer to obtain a complete data tensor. We test the performance and generalization of the resulting bi-linear model with a test set. Results show that the obtained model allow us to successfully and realistically manipulate facial expressions of babies while keeping them decoupled from identity variations.
Práva:	© Václav Skala - UNION Agency
Vyskytuje se v kolekcích:	WSCG 2022: Full Papers Proceedings

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