Visual fatigue modeling for stereoscopic video shot based on camera motion

Guozhong Shi; Xinzhu Sang; Xunbo Yu; Yangdong Liu; Jing Liu

doi:10.1117/12.2072894

24 November 2014 Visual fatigue modeling for stereoscopic video shot based on camera motion

Guozhong Shi, Xinzhu Sang, Xunbo Yu, Yangdong Liu, Jing Liu

Proceedings Volume 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition; 93012P (2014) https://doi.org/10.1117/12.2072894
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China

Abstract

As three–dimensional television (3-DTV) and 3-D movie become popular, the discomfort of visual feeling limits further applications of 3D display technology. The cause of visual discomfort from stereoscopic video conflicts between accommodation and convergence, excessive binocular parallax, fast motion of objects and so on. Here, a novel method for evaluating visual fatigue is demonstrated. Influence factors including spatial structure, motion scale and comfortable zone are analyzed. According to the human visual system (HVS), people only need to converge their eyes to the specific objects for static cameras and background. Relative motion should be considered for different camera conditions determining different factor coefficients and weights. Compared with the traditional visual fatigue prediction model, a novel visual fatigue predicting model is presented. Visual fatigue degree is predicted using multiple linear regression method combining with the subjective evaluation. Consequently, each factor can reflect the characteristics of the scene, and the total visual fatigue score can be indicated according to the proposed algorithm. Compared with conventional algorithms which ignored the status of the camera, our approach exhibits reliable performance in terms of correlation with subjective test results.

Citation Download Citation

Guozhong Shi, Xinzhu Sang, Xunbo Yu, Yangdong Liu, and Jing Liu "Visual fatigue modeling for stereoscopic video shot based on camera motion", Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012P (24 November 2014); https://doi.org/10.1117/12.2072894

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KEYWORDS

Visualization

Video

Cameras

Visual process modeling

Motion models

3D modeling

3D displays

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