DocumentCode
177809
Title
3D Facial Skin Texture Analysis Using Geometric Descriptors
Author
Seck, A. ; Dee, H. ; Tiddeman, B.
Author_Institution
Comput. Sci. Dept., Aberystwyth Univ., Aberystwyth, UK
fYear
2014
fDate
24-28 Aug. 2014
Firstpage
1126
Lastpage
1131
Abstract
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.
Keywords
Gabor filters; face recognition; feature extraction; geometry; image classification; image resolution; image texture; skin; 2D texture descriptors; 2D texture feature extraction; 2D-based texture features; 3D facial skin texture analysis; 3D orientation based features; 3D surface orientation data; 3D-based texture features; 3DRFE dataset; albedo images; center-symetric autocorrelation; facial pore classification; facial wrinkle classification; geometric descriptors; high resolution facial skin albedo patches; multiple orientations Gabor filters; multiresolution analysis; normal map patches; rotation-invariant local binary patterns; skin texture classification; tangent spaces; Feature extraction; Lighting; Rough surfaces; Skin; Surface roughness; Surface texture; Three-dimensional displays;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition (ICPR), 2014 22nd International Conference on
Conference_Location
Stockholm
ISSN
1051-4651
Type
conf
DOI
10.1109/ICPR.2014.203
Filename
6976913
Link To Document