We compare skin texture classification using various 2D texture descriptors and their extensions to 3D surface orientation data. We perform a multi-resolution analysis on both the 2D and 3D data. Rotation-Invariant Local Binary Patterns, Multiple Orientations Gabor Filters and Center-Symetric Autocorrelation are used to extract 2D texture features from high resolution facial skin albedo patches. For extracting texture feature directly from the corresponding normal map patches, we propose extensions of these texture measures in both the slant/tilt and tangent spaces. We compare the results of classifying facial wrinkles and pores using the 2D-based and 3D-based texture features. We use the 3DRFE dataset which consists of high resolution 3D facial scans along with the corresponding photometric and albedo images. We notice a net improvement on classifying both wrinkle and pore using the 3D orientation based features over the 2D ones.
|Enw||International Conference on Pattern Recognition|
|Cyhoeddwr||IEEE Computer Society|
|Cynhadledd||22nd International Conference on Pattern Recognition|
|Cyfnod||24 Awst 2014 → 28 Awst 2014|