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Machine Vision and Applications
Erschienen in: Machine Vision and Applications 4/2014

01.05.2014 | Original Paper

Fully automatic expression-invariant face correspondence

verfasst von: Augusto Salazar, Stefanie Wuhrer, Chang Shu, Flavio Prieto

Erschienen in: Machine Vision and Applications | Ausgabe 4/2014

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Abstract

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.
Vorheriger Artikel Face relighting using discriminative 2D spherical spaces for face recognition
Nächster Artikel Fusing the information in visible light and near-infrared images for iris recognition

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Metadaten
Titel
Fully automatic expression-invariant face correspondence
verfasst von
Augusto Salazar
Stefanie Wuhrer
Chang Shu
Flavio Prieto
Publikationsdatum
01.05.2014
Verlag
Springer Berlin Heidelberg
Erschienen in
Machine Vision and Applications / Ausgabe 4/2014
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-013-0579-9

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