Gloss assessment with deep photometric stereo: application to human skin

Clément Joubert; Benjamin Bringier; Julien Garnier; Majdi Khoudeir; Nicolas Amalric

doi:10.1117/12.2692082

28 July 2023 Gloss assessment with deep photometric stereo: application to human skin

Clément Joubert, Benjamin Bringier, Julien Garnier, Majdi Khoudeir, Nicolas Amalric

Proceedings Volume 12749, Sixteenth International Conference on Quality Control by Artificial Vision; 127490Q (2023) https://doi.org/10.1117/12.2692082
Event: Sixteenth International Conference on Quality Control by Artificial Vision, 2023, Albi, France

Abstract

This contribution presents a novel method to extract skin physical parameters as geometry, colour and gloss with photometric stereo. Our method is based on QNN (Quaternion Neural Network) to estimate the surface geometry from images with a fixed viewpoint modifying surface illumination, i.e. photometric stereo. To that end, we assume that surface BRDF (Bidirectional Reflectance Distribution Function) can be separated by a diffuse and specular component. Once the geometry is estimated, colour is estimated from geometry to finally compute gloss. This method results on multiple gloss maps which are used to compute features that characterise surface gloss. Unlike other approaches, our method does not require polarising filters that suffer from a more complex light modelling. We demonstrate the effectiveness of our approach through experiments on rendering, cow leather and ex-vivo skin samples. The proposed method has potential for various real-world applications such as evaluating the appearance of skin care products or assessing skin health.

Citation Download Citation

Clément Joubert, Benjamin Bringier, Julien Garnier, Majdi Khoudeir, and Nicolas Amalric "Gloss assessment with deep photometric stereo: application to human skin", Proc. SPIE 12749, Sixteenth International Conference on Quality Control by Artificial Vision, 127490Q (28 July 2023); https://doi.org/10.1117/12.2692082

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