Various subjective and objective methods have been investigated to evaluate stereoscopic visual fatigue in terms of improving the accuracy and practicability. But none of those methods are perfect for all kinds of shortages. Objective measures are more preferred for their capability to quantify the degree of human visual fatigue without being affected by individual variation.
In our previous study which was based on non-expert experiment, we proposed a method combining subjective assessment and objective measures to evaluate stereoscopic visual fatigue, and a visual fatigue predictive model (non-expert model) using two simple objective indicators. In this study, we conducted the same experiment, but on expert-only viewers. A visual fatigue predictive model (expert-only model) was developed from the results and was evaluated comparing with the non-expert model. Both visual fatigue predictive models showed high correlation with subjective data, and the expert-only model performed slightly better than the non-expert model. The method we proposed is basically insusceptible to viewers and practical experiments, and is a promising approach to evaluate visual fatigue efficiently and objectively.
• Conducted an expert-only experiment to evaluate visual fatigue of viewers watching stereoscopic videos. The results show that the correlation between three objective indicators and the subjectively assessed visual fatigue have closely related variation trends in time series.
• Built a predictive model to evaluate subjective visual fatigue, according to three physiological indicators. The model is more precise than the former model built on ordinary subjective experiment
• Used SPSS to analyze the results of a user study about viewing stereoscopic videos comfort influenced by four factors (Relative disparity, the size, the velocity and the number of moving objects). The results show that the first three factors are significantly affecting the visual comfort.
Danli Wang, Tingting Wang, Yining Shi. Stereoscopic Visual Fatigue Evaluation Based on Subjective Assessments and Objective Measures. Submitted to Journal of the Society for Information Display (JSID).
Team: Danli Wang, Tingting Wang, Yining Shi.