6 February 2012 Visual fatigue modeling and analysis for stereoscopic video
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Abstract
In this paper, we propose a visual fatigue prediction method for stereoscopic video. We select visual fatigue factor candidates and determine the equations for each. The candidates are then classified into their principal components, and the validity of each is confirmed using principal component analysis. Visual fatigue is predicted using multiple regression with subjective visual fatigue. In order to determine the best model, we select the visual fatigue factors that have sufficient significance in terms of subjective fatigue according to the stepwise method. The predicted visual fatigue score is presented as a linear combination of the selected visual fatigue factors. Consequently, the proposed algorithm provides more reliable performance in terms of correlation with the subjective test results compared with a conventional algorithm.
© 2012 Society of Photo-Optical Instrumentation Engineers (SPIE)
Jaeseob Choi, Jaeseob Choi, Donghyun Kim, Donghyun Kim, Sunghwan Choi, Sunghwan Choi, Kwanghoon Sohn, Kwanghoon Sohn, } "Visual fatigue modeling and analysis for stereoscopic video," Optical Engineering 51(1), 017206 (6 February 2012). https://doi.org/10.1117/1.OE.51.1.017206 . Submission:
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