Detecting Wetness on Skin using RGB Camera

Abstract

In this study, we propose a method to detect wetness on the surface of human skin and skin phantoms using an RGB camera. Recent research on affect analysis has addressed the non-contact multi-modal analysis of affect aimed at such applications as automated questionnaires. New modalities are needed to develop a more accurate system for analyzing affects than the current system. Thus we focus on emotional sweating, which is among the most reliable modalities in contact methods for affect analysis. However, sweat detection on the human skin has not been achieved by other researchers, and thus it is unclear whether their feature values are useful. The proposed method is based on feature values of color and glossiness obtained from images. In tests of this method, the error rate was approximately 6.5% on a skin phantom and at least approximately 12.7% on human skin. This research will help to develop non-contact affect analysis.