Open Access3D surface texture analysis of high‐resolution normal fields for facial skin condition assessment
Author(s) -
Seck Alassane,
Dee Hannah,
Smith William,
Tiddeman Bernard
Publication year - 2020
Publication title -
skin research and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.521
H-Index - 69
eISSN - 1600-0846
pISSN - 0909-752X
DOI - 10.1111/srt.12793
Subject(s) - artificial intelligence , texture (cosmology) , computer science , orientation (vector space) , high resolution , computer vision , ground truth , pattern recognition (psychology) , image (mathematics) , mathematics , geology , remote sensing , geometry
Background This paper investigates the use of a light stage to capture high‐resolution, 3D facial surface textures and proposes novel methods to use the data for skin condition assessment. Materials and Methods We introduce new methods for analysing 3D surface texture using high‐resolution normal fields and apply these to the detection and assessment of skin conditions in human faces, specifically wrinkles, pores and acne. The use of high‐resolution normal maps as input to our texture measures enables us to investigate the 3D nature of texture, while retaining aspects of some well‐known 2D texture measures. The main contributions are as follows: the introduction of three novel methods for extracting texture descriptors from high‐resolution surface orientation fields; a comparative study of 2D and 3D skin texture analysis techniques; and an extensive data set of high‐resolution 3D facial scans presenting various skin conditions, with human ratings as “ground truth.” Results Our results demonstrate an improvement on state‐of‐the‐art methods for the analysis of pores and comparable results to the state of the art for wrinkles and acne using a considerably more compact model. Conclusions The use of high‐resolution normal maps, captured by a light stage, and the methods described, represent an important new set of tools in the analysis of skin texture.