Psychological vision experiments for visual discomfort measurement

in stereoscopic displays

2010 . 01 ~ Current

 

1. Quantitative measurement of binocular color fusion limit for non-spectral colors

As 3DTV has spread, it is necessary to measure how color differences between left and right images of non-spectral colors as well as spectral colors initiate color rivalry. In particular, the color fusion limit of non-spectral colors needs to be measured in the color gamut of 3DTV. Thus far, no attempt has been made to measure the color fusion limit for non-spectral colors. In this Research, we measured the binocular color fusion limit for non-spectral colors within the color gamut of a conventional LCD (Liquid Cristal Display) 3DTV. The color fusion limit is measured for eight chromaticity points, covering the entire area in the standard CIE 1976 u´v´ chromaticity diagram.

1.1. Visual stimulus

To cover the entire area of the chromaticity diagram, we uniformly sampled the points in the CIE 1976 uniform chromaticity scale diagram. Fig. 1 shows all eight sample points in the CIE 1976 chromaticity diagram, where we measured the color fusion limit. The numbers in Fig. 1 indicate the sample numbers to be observed for the color fusion limit and the triangle represents the color gamut of the LCD display used in our experiments. In the experiments, the colors of the sampled points were presented for the right eye.

To prepare the stimuli for the left eye, which were coupled with the stimulus given for the right eye, we sampled neighbors along the straight lines of six directions from the origin point given for the right eye. The six directions consisted of:

          Three main directions to the red (R), green (G), and blue (B) primaries.

          Three sub-directions representing an equiangular division between R and G, G and B, and B and R, respectively.

We used a black background and a circular object filled with the sampled colors. The binocular disparity was zero, indicating no depth perception. Fig. 2 shows an example of a stimulus. It consists of different colors for the left and right eyes.

 

Fig. 1. The total of 8 sample points in the CIE 1976 chromaticity diagram where we quantify color fusion limit through our experiment.
The triangle represents the color gamut of the LCD display used in our experiments. The numbers indicate the sample numbers (from No. 1 to No. 8). These sample points were presented for the right eye. [1]

 

Fig. 2. Example of a stimulus used in the binocular color fusion limit experiment (a) for the left eye and (b) for the right eye.
The test field size was 2° in diameter, and the surrounding field size was 33°.

1.2. Results

For the eight chromaticity points, the results of the color fusion limit were represented as a series of ellipses. The semi-minor axis of the ellipses ranged from 0.0415 to 0.0923 in the Euclidean distance in the u´v´ chromaticity diagram while the semi-major axis ranged from 0.0640 to 0.1560. The shapes and directions of rotation of the ellipses were similar to those of MacAdam ellipses for the just-noticeable differences of chromaticity.

 

Fig. 3. Overall results of the color fusion limit plotted on the CIE 1976 chromaticity diagram.
For clarity, the ellipses are downscaled to one third of their actual lengths.[1]

 

[1] Y. J. Jung, H. Sohn, S. Lee, Y. M. Ro, and H. W. Park, “Quantitative Measurement of Binocular Color Fusion Limit for Non-spectral Colors,” Optics Express, vol. 19, no. 8, pp. 7325-7338, 2011 (also selected by the Editors for publication in the most recent issue of the Virtual Journal for Biomedical Optics)

 

2. Subjective measurement of visual discomfort induced by disparity characteristic

This experiment assesses the visual discomfort induced by disparity magnitude. Psychophysical experiments have been conducted to investigate the relationship between subjective visual comfort and the amount of binocular disparity.

2.1. Visual stimulus

Fig. 4 shows an example of the visual stimulus used in this experiment. The visual stimulus consists of two overlapped squares and background. Luminance of the foreground square and the surrounding square was respectively set to 50 cd/m2 and 25 cd/m2 (CIE daylight D65) with the field size of 2º and 10º visual angles. To avoid the visual effect of background, luminance of the background was set to 0 cd/m2. Note that the size of visual field for the foreground square and the surrounding square were determined to cover the size of the fovea and the parafovea respectively. Binocular disparity was only given to the foreground square in the range of +3.7º to –3.7º with a step size of 0.6 º, where positive polarity refers to crossed disparity while negative polarity refers to uncrossed disparity.

 

Fig. 4.  Visual stimulus used for subjective assessment of the visual discomfort induced by disparity characteristics.[2]

2.2. Results

Fig. 5 shows the degree of visual comfort with diverse amount of binocular disparities. In Fig. 5, x-axis indicates binocular disparity while y-axis indicates a mean opinion score (MOS). As shown in the figure, human observers reported higher degree of visual discomfort as binocular disparity increases. Increase in binocular disparity imposes higher operating load of human oculomotor system, which may induce physiological symptoms of visual discomfort. Fig. 5(b) represents the degree of each symptom obtained from the questionnaire according to the amount of binocular disparity. From the result, it can be observed that as binocular disparity increases, overall symptoms of visual discomfort become severe and its major symptoms are focusing difficulty and eye strain.

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Fig. 5.  Visual discomfort induced by binocular disparities: (a) MOS of visual comfort (b) the degree of each symptoms of visual discomfort. [2]

 

[2] H. Sohn, Y.J. Jung, S. Lee, H.W. Park, and Y.M. Ro, “Attention Model-Based Visual Comfort Assessment for Stereoscopic Depth Perception,” IEEE International Conference on Digital Signal Processing (DSP 2011), Greece

 

3. Subjective measurement of visual discomfort induced by motion characteristics

This experiment assesses the visual discomfort induced by planar motion and in-depth motion  characteristics: 1) velocity of horizontal motion: the average change in horizontal visual angle and apparent depth for the planar motion, 2) velocity of vertical motion: the average change in vertical visual angle and apparent depth for the planar motion, and 3) velocity of in-depth motion: the average change in angular disparity.

3.1. Visual stimulus

A set of visual stimuli was generated with various velocities and directions of object motion using a computer graphics tool. As shown in Fig. 6, these visual stimuli consisted of a grey meteor object (chromaticity: D65, illumination: 25 cd/m2), background (chromaticity: D65, illumination: 50 cd/m2), and a guide for zero parallax position. A total of 49 visual stimuli were generated (21 stimuli for horizontal motion, 21 stimuli for vertical motion, and 7 stimuli for depth motion). 42 visual stimuli had horizontal and vertical motions at seven different velocities, moving at 1° crossed disparity, zero disparity, and 1° uncrossed disparity, respectively. 7 visual stimuli had depth motion at seven different velocities. The visual stimulus with horizontal and vertical motions contained a pair of high contrast colored bars and the visual stimulus with depth motion contained a high contrast colored ring. The bars and ring were positioned at the zero disparity so as to provide a depth plane of reference for viewers.

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Fig. 6. Examples of visual stimulus. (a) Horizontal motion at 1° crossed disparity; (b) vertical motion at 1° crossed disparity; and (c) depth motion. For depth motion, the meteor object periodically moves back-and-forth between 1° crossed disparity and 1° uncrossed disparity.[3]

3.2. Results

3.2.1 Horizontal motion

Fig. 7 shows the experimental results of horizontal motion. In the figure, y-axis represents mean opinion score of the perceived visual comfort and x-axis denotes velocity of horizontal motion. The results show that increase in velocity of horizontal motion induces more visual discomfort. Fig. 8 represents the results of the accompanied questionnaire. In the figure, y-axis is the severity of the symptoms of visual discomfort (5: none, 1: severe). The x-axis of Fig. 8 is the velocity of horizontal motion. The accompanied questionnaire reveals that the subjects felt the focusing difficulty. This phenomenon was caused by motion blur and motion judder in an object.

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Fig. 7. Visual comfort models for horizontal motion, which represent the relation between visual comfort and motion velocity. The models were obtained by fitting the results of subjective assessment. (a) 1° crossed disparity; (b) zero disparity; and (c) 1° uncrossed disparity. Error bars represent standard deviation of median rating scores.[3]

 

 

 

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Fig. 8. The degree of the symptoms of visual discomfort for horizontal motion. (a) 1° crossed disparity; (b) zero disparity; and (c) 1° uncrossed disparity.[3]

3.2.2 Vertical motion

Fig. 9 shows the experimental results of vertical motion. As in the horizontal motion, more visual discomfort was induced as the velocity of vertical motion increased. Fig. 10 represents the result of the accompanied questionnaire. The accompanied questionnaire reveals that the subjects have felt the focusing difficulty. This phenomenon was caused by motion blur and motion judder in an object.

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Fig. 9. Visual comfort models for vertical motion, which represent the relation between visual comfort and motion velocity. The models were obtained by fitting the results of subjective assessment. (a) 1° crossed disparity; (b) zero disparity; and (c) 1° uncrossed disparity. [3]

 

 

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Fig. 10. The degree of the symptoms of visual discomfort for vertical motion. (a) 1° crossed disparity; (b) zero disparity; and (c) 1° uncrossed disparity.[3]

 

3.2.3 In-depth motion

Fig. 11 shows the experimental results of in-depth motion. Similar to the previous results, increase in the velocity of in-depth motion induced more visual discomfort. Furthermore, the result of accompanied questionnaire presented in Fig. 9 reveals that the levels of eye strain and focusing difficulty also decreased as the velocity of in-depth motion increases.

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Fig. 11. Subjective assessment results: (a) Visual comfort model for in-depth motion, (b) the degree of the symptoms of visual discomfort for depth motion.[3]

 

[3] Y. J. Jung, S. Lee, H. Sohn, H.W. Park, and Y.M. Ro, “Visual comfort assessment metric based on salient object motion information in stereoscopic video,” Journal of Electronic Imaging, vol. 21, no. 1, 2012.

 

 

 

 Yong Ju Jung

yj.jung@kaist.ac.kr


 Associate research Professor

 Biography

Yong Ju Jung received the M.S. and Ph.D. degrees from the Korea Advanced Institute of Science and Technology (KAIST), IT Convergence Campus, Daejeon, Korea in 2000 and 2005, respectively. From 2005 to 2010, he was a research staff member at Samsung Advanced Institute of Technology, contributing to 3D display processing for 3DTV. Since 2010, he has been an associate research professor of the Department of Electrical Engineering at KAIST. His research interests include image/video processing, human 3D perception, 3D display processing, and computer vision. He co-organized special sessions on “Human 3D Perception and 3D Video Assessments” in DSP2011. He is currently charge in 3D video related research projects in KAIST.

 

 

 

 Hosik Sohn

sohnhosik@kaist.ac.kr

  Ph.D Candidate in Dept. of EE in KAIST

Researcher in IVY Lab in KAIST

Experience of Research projects

Practical safety guideline for viewing 3DTV (Korea Communications Commission, Korea)

Development and standardization of Terrestrial Stereoscopic 3DTV Broadcasting System technology (Ministry of Knowledge Economy, Korea)

Video coding framework (H.264/AVC) using a parallel process function command of reconstructed processor (Electronics Telecommunication Research Institute, Korea)

Research Interest

 

3D image/video processing, 3D visual comfort assessment, 2D/3D video quality, multimedia adaptation, biometric security

 

 

 

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 Seong-il Lee

vitallsi@kaist.ac.kr

  Ph.D Candidate in Dept. of EE in KAIST

Researcher in IVY Lab in KAIST

Experience of Research projects

Practical safety guideline for viewing 3DTV (Korea Communications Commission, Korea)

Development and standardization of Terrestrial Stereoscopic 3DTV Broadcasting System technology (Ministry of Knowledge Economy, Korea)

Research Interest

 

3D image/video processing, 3D visual comfort assessment, 2D/3D video quality, human 3D perception

 

 

 

Y. J. Jung, H. Sohn, S. Lee, Y. M. Ro, and H. W. Park, “Quantitative Measurement of Binocular Color Fusion Limit for Non-spectral Colors,” Optics Express, vol. 19, no. 8, pp. 7325-7338, 2011 (also selected by the Editors for publication in the most recent issue of the Virtual Journal for Biomedical Optics)

H. Sohn, Y.J. Jung, S. Lee, H.W. Park, and Y.M. Ro, “Attention Model-Based Visual Comfort Assessment for Stereoscopic Depth Perception,” IEEE International Conference on Digital Signal Processing (DSP 2011), Greece

Y. J. Jung, S. Lee, H. Sohn, H.W. Park, and Y.M. Ro, “Visual comfort assessment metric based on salient object motion information in stereoscopic video,” Journal of Electronic Imaging, vol. 21, no. 1, 2012.