3D Surface Texture Analysis of High Resolution Normal Fields for Facial Skin Condition Assessment

Abstract

This paper investigates the use of a lightstage 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, whilst retaining aspects of some well-known 2D texture measures. The main contributions are: 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 dataset 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.