3D surface texture analysis of high-resolution normal fields for facial skin condition assessment

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.

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."

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.

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.