Yuchun Yan, a PhD student of Color lab made an interactive and poster presentation entitled as “Skin Balancing: Skin Color-Based Calibration for Portrait Images to Enhance the Affective Quality” at CIC27, Paris, France. In this paper, we investigated the perceived quality of portrait images depending on how the target skin color is defined: measured, memory, digital, or CCT skin color variations. A user study with 24 participants assessed the quality of white-balanced portraits on five criteria: reality, naturalness, appropriateness, preference, and emotional enhancement. The results showed that the calibration using different target skin colors affected perceived image quality.
Abstract
We investigated the perceived quality of portrait images depending on how the target skin color is defined: measured, memory, digital, or CCT skin color variations. A user study was conducted; 24 participants assessed the quality of white-balanced portraits on five criteria: reality, naturalness, appropriateness, preference, and emotional enhancement. The results showed that the calibration using measured skin color best served the aspects of reality and naturalness. With regard to appropriateness and preference, digital skin color obtained the highest score. Also, the memory skin color and skin color in diverse CCT variations were appropriate to present portraits with emotional enhancement
