An Automatic 3D Facial Landmarking Algorithm Using 2D Gabor Wavelets

In this paper, we present a novel approach to automatic 3D facial landmarking using 2D Gabor wavelets. Our algorithm considers the face to be a surface and uses map projections to derive 2D features from raw data. Extracted features include texture, relief map, and transformations thereof. We extend...

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Veröffentlicht in:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 25(2016), 2 vom: 09. Feb., Seite 580-8
1. Verfasser: de Jong, Markus A (VerfasserIn)
Weitere Verfasser: Wollstein, Andreas, Ruff, Clifford, Dunaway, David, Hysi, Pirro, Spector, Tim, Fan Liu, Niessen, Wiro, Koudstaal, Maarten J, Kayser, Manfred, Wolvius, Eppo B, Bohringer, Stefan
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2016
Zugriff auf das übergeordnete Werk:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
Beschreibung
Zusammenfassung:In this paper, we present a novel approach to automatic 3D facial landmarking using 2D Gabor wavelets. Our algorithm considers the face to be a surface and uses map projections to derive 2D features from raw data. Extracted features include texture, relief map, and transformations thereof. We extend an established 2D landmarking method for simultaneous evaluation of these data. The method is validated by performing landmarking experiments on two data sets using 21 landmarks and compared with an active shape model implementation. On average, landmarking error for our method was 1.9 mm, whereas the active shape model resulted in an average landmarking error of 2.3 mm. A second study investigating facial shape heritability in related individuals concludes that automatic landmarking is on par with manual landmarking for some landmarks. Our algorithm can be trained in 30 min to automatically landmark 3D facial data sets of any size, and allows for fast and robust landmarking of 3D faces
Beschreibung:Date Completed 31.10.2016
Date Revised 30.12.2016
published: Print-Electronic
Citation Status MEDLINE
ISSN:1941-0042
DOI:10.1109/TIP.2015.2496183