Publications

A personal visual comfort model: Predict individual’s visual comfort using occupant eye pupil size and machine learning

Abstract

Lighting, as a significant component of indoor environmental quality, was found to be a primary contributor to deficient indoor environments in today's workplace. This resulted from the fact that current guidelines are derived from empirical values and neglect the prevalence of computer-based tasks in current offices. A personal visual comfort model was designed to predict the degree of an individual's visual comfort, as a way of evaluating the indoor lighting of the environment. Development of the model relied on experimental data, including individual eye pupil sizes, visual sensations, and visual satisfaction in response to various illuminance levels used for tests of six human subjects. The results showed that (1) A personal comfort model was needed,(2) the personal comfort model produced a median accuracy of 0.7086 for visual sensation and 0.65467 for visual satisfaction for all subjects;(3) To develop a …

Date
September 1, 2019
Authors
Lingkai Cen, Joon-Ho Choi, Xiaomeng Yao, Yolanda Gil, Shrikanth Narayanan, Maryann Pentz
Journal
IOP Conference Series: Materials Science and Engineering
Volume
609
Issue
4
Pages
042097
Publisher
IOP Publishing