Back to Search Start Over

Eye movements and visual discomfort when viewing stereoscopic 3D content.

Authors :
Zhou, Jun
Wang, Ling
Yin, Haibing
Bovik, Alan C.
Source :
Digital Signal Processing. Aug2019, Vol. 91, p41-53. 13p.
Publication Year :
2019

Abstract

The visual brain fuses the left and right images projected onto the two eyes from a stereoscopic 3D (S3D) display, perceives parallax, and rebuilds a sense of depth. In this process, the eyes adjust vergence and accommodation to adapt to the depths and parallax of the points they gazed at. Conflicts between accommodation and vergence when viewing S3D content potentially lead to visual discomfort. A variety of approaches have been taken towards understanding the perceptual bases of discomfort felt when viewing S3D, including extreme disparities or disparity gradients, negative disparities, dichoptic presentations, and so on. However less effort has been applied towards understanding the role of eye movements as they relate to visual discomfort when viewing S3D. To study eye movements in the context of S3D viewing discomfort, a Shifted-S3D-Image-Database (SSID) is constructed using 11 original nature scene S3D images and their 6 shifted versions. We conducted eye-tracking experiments on humans viewing S3D images in SSID while simultaneously collecting their judgments of experienced visual discomfort. From the collected eye-tracking data, regions of interest (ROIs) were extracted by kernel density estimation using the fixation data, and an empirical formula fitted between the disparities of salient objects marked by the ROIs and the mean opinion scores (MOS). Finally, eye-tracking data was used to analyze the eye movement characteristics related to S3D image quality. Fifteen eye movement features were extracted, and a visual discomfort predication model learned using a support vector regressor (SVR). By analyzing the correlations between features and MOS, we conclude that angular disparity features have a strong correlation with human judgments of discomfort. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10512004
Volume :
91
Database :
Academic Search Index
Journal :
Digital Signal Processing
Publication Type :
Periodical
Accession number :
136912267
Full Text :
https://doi.org/10.1016/j.dsp.2018.12.008