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Optical Engineering

Visual fatigue modeling and analysis for stereoscopic video
Author(s): Jaeseob Choi; Donghyun Kim; Sunghwan Choi; Kwanghoon Sohn
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Paper 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.

Paper Details

Date Published: 6 February 2012
PDF: 12 pages
Opt. Eng. 51(1) 017206 doi: 10.1117/1.OE.51.1.017206
Published in: Optical Engineering Volume 51, Issue 1
Show Author Affiliations
Jaeseob Choi, Yonsei Univ. (Korea, Republic of)
Donghyun Kim, Yonsei Univ. (Korea, Republic of)
Sunghwan Choi, Yonsei Univ. (Korea, Republic of)
Kwanghoon Sohn, Yonsei Univ. (Korea, Republic of)

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