Investigation and modeling of visual fatigue caused by S3D content using eye-tracking |
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| Affiliation: | 1. École Polytechnique de Montréal, 2900 Boulevard Edouard-Montpetit, Montréal, QC H3T 1J4, Canada;2. École de technologie supérieure, 1100 Rue Notre-Dame Ouest, Montréal, QC H3C 1K3, Canada;3. Institut Philippe-Pinel de Montréal, 10905 Boul Henri-Bourassa E, Montréal, QC H1C 1H1, Canada;1. School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, Hubei, China;2. Department of Building and Real Estate, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China;3. School of Management, Huazhong University of Science and Technology, Wuhan, Hubei, China;4. Department of Computer Science, Chu Hai College of Higher Education, Tuen Mun, Hong Kong, China;5. School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan, Hubei, China |
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| Abstract: | 3D has been one of the most important technologies of the last decade having an exponential progression. Nevertheless, several problems such as visual discomfort and visual fatigue have slowed its progression for homes. This factor decreases significantly the overall quality of experience from watching 3D content and reduces the level of satisfaction of a user. This study explores the accumulation of visual fatigue when watching 3D video in close to real-life conditions. In order to obtain more information about visual discomfort, an hour of eye-tracking experiments have been conducted. Investigations have been made by analyzing information provided both by users through questionnaires and visual gaze characteristics recording. Obtained results are compared to data produced when watching 2D. The deep statistical analysis showed that time and video content have an influence on video fatigue accumulation and visual functions. With respect to the obtained results, a model has been proposed based on video characteristics (motion activity, disparity range and changes) and the previous state of visual fatigue. |
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| Keywords: | Visual fatigue Visual discomfort S3D imaging Subjective evaluation Eye-tracking Statistical analysis |
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