| DOI | Trouver le DOI : https://doi.org/10.1007/s00138-013-0579-9 |
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| Auteur | Rechercher : Salazar, A.; Rechercher : Wuhrer, S.; Rechercher : Shu, C.1; Rechercher : Prieto, F. |
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| Affiliation | - Conseil national de recherches du Canada
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| Format | Texte, Article |
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| Résumé | We consider the problem of computing accurate point-to-point correspondences among a set of human face scans with varying expressions. Our fully automatic approach does not require any manually placed markers on the scan. Instead, the approach learns the locations of a set of landmarks present in a database and uses this knowledge to automatically predict the locations of these landmarks on a newly available scan. The predicted landmarks are then used to compute point-to-point correspondences between a template model and the newly available scan. To accurately fit the expression of the template to the expression of the scan, we use as template a blendshape model. Our algorithm was tested on a database of human faces of different ethnic groups with strongly varying expressions. Experimental results show that the obtained point-to-point correspondence is both highly accurate and consistent for most of the tested 3D face models. © 2013 Springer-Verlag Berlin Heidelberg. |
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| Date de publication | 2013 |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Numéro NPARC | 21270717 |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | c44a3083-a9b7-4bf4-b60a-4081e5b4439b |
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| Enregistrement créé | 2014-02-17 |
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| Enregistrement modifié | 2020-04-22 |
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