Abstract

Augmented reality (AR) aims to combine elements of the surrounding environment with additional virtual content into a combined viewing scene. Displaying virtual human faces is a widespread practical application of AR technology, which can be challenging in optical see- through AR (OST-AR), due to limitations in its color reproduction. Specifically, OST-AR’s additive optical blending introduces transparency and color-bleeding, which is exacerbated especially for faces having darker skin tones, and for brighter and more chromatic ambient environments. Given the increasing prevalence of social AR applications, it is essential to better understand how facial color reproduction is impacted by skin tone and ambient lighting in OST- AR. While past research has examined challenges in color reproduction in OST-AR due to optical blending, this work fills the gap by systematically varying skin tones, simulating diverse ambient conditions with controlled luminance and chromaticity, highlighting human face perception, and quantifying perceptual color adjustments needed to best reproduce OST-AR faces. In this study, a psychophysical experiment was conducted to investigate how participants’ adjusted colorimetric dimensions of OST-AR-displayed faces to match the color of the same faces viewed on a conventional emissive display. These adjustments were made for faces having six different skin tones, while under different simulated ambient luminance (‘low’ vs. ‘high’) and chromaticity (warm, neutral, cool). Additionally, participants rated their adjustments based on how well their adjusted faces matched the reference appearance and how much they thought the person depicted would like the appearance. The results indicate that the magnitude and specific dimensions of colorimetric adjustments needed to make matches varied across skin tones and ambient conditions. The current work is expected to facilitate virtual human face reproduction in AR applications and to foster more equitable and immersive extended reality environments.

Library of Congress Subject Headings

Augmented reality--Quality control; Imaging systems--Image quality; Human skin color

Publication Date

7-2025

Document Type

Thesis

Student Type

Graduate

Degree Name

Color Science (MS)

Department, Program, or Center

Color Science

College

College of Science

Advisor

Susan Farnand

Comments

This thesis has been embargoed. The full-text will be available on or around 1/30/2026.

Campus

RIT – Main Campus

Plan Codes

CLRS-MS

Download

Available for download on Monday, January 26, 2026

Share

COinS