Paper
17 March 2015 Study of objective evaluation indicators of 3D visual fatigue based on RDS related tasks
Author Affiliations +
Proceedings Volume 9391, Stereoscopic Displays and Applications XXVI; 93910V (2015) https://doi.org/10.1117/12.2083291
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States
Abstract
Three dimensional (3D) displays have witnessed rapid progress in recent years because of its highly realistic sensation and sense of presence to humanist users. However, the comfort issues of 3D display are often reported and thus restrict its wide applications. In order to study the objective evaluation indicators associated with 3D visual fatigue, an experiment is designed in which subjects are required to accomplish a task realized with random dot stereogram (RDS). The aim of designing the task is to induce 3D visual fatigue of subjects and exclude the impacts of monocular depth cues. The visual acuity, critical flicker frequency (CFF), reaction time and correct rate of subjects during the experiment are recorded and analyzed. Correlation of the experimental data with the subjective evaluation scores is studied to find which indicator is closely related to 3D visual fatigue. Analysis of the experimental data shows that the trends of the correct rate are in line with the result of subjective evaluation.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yi Huang, Yue Liu, Bochao Zou, Yongtian Wang, and Dewen Cheng "Study of objective evaluation indicators of 3D visual fatigue based on RDS related tasks", Proc. SPIE 9391, Stereoscopic Displays and Applications XXVI, 93910V (17 March 2015); https://doi.org/10.1117/12.2083291
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Visualization

3D displays

3D visualizations

Stereoscopic displays

3D image processing

Video

Visual analytics

Back to Top