Name
Abstract | ||
|---|---|---|
This study proposes a novel automatic method for facial landmark localization relying on geometrical properties of 3D facial surface working both on complete faces displaying different emotions and in presence of occlusions. In particular, 12 descriptors coming from Differential Geometry including the coefficients of the fundamental forms, Gaussian, mean, principal curvatures, shape index and curvedness are extracted as facial features and their local geometric properties are exploited to localize 13 soft-tissue landmarks from eye and nose areas. The method is deterministic and is backboned by a thresholding technique designed by studying the behaviour of each geometrical descriptor in correspondence to the locus of each landmark. Occlusions are managed by a detection algorithm based on geometrical properties which allows to proceed with the landmark localization avoiding the covered areas. Experimentations were carried out on 3132 faces of the Bosphorus database and of a 230-sized internal database, including expressive and occluded ones (mouth, eye, and eyeglasses occlusions), obtaining 4.75 mm mean localization error. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/s11042-017-5025-y | Multimedia Tools Appl. |
Keywords | Field | DocType |
3D face, Face analysis, Landmark localization, Differential geometry, Feature extraction | Computer vision,Pattern recognition,3d geometry,Shape index,Computer science,Principal curvature,Feature extraction,Gaussian,Differential geometry,Artificial intelligence,Thresholding,Landmark | Journal |
Volume | Issue | ISSN |
77 | 11 | 1380-7501 |
Citations | PageRank | References |
9 | 0.44 | 18 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Enrico Vezzetti | 1 | 151 | 12.98 |
| Federica Marcolin | 2 | 94 | 7.50 |
| Stefano Tornincasa | 3 | 30 | 2.99 |
| Luca Ulrich | 4 | 9 | 1.46 |
| Nicole Dagnes | 5 | 12 | 1.16 |