3D visual discomfort predictor based on neural activity statistics

Heeseok Oh; Jongyoo Kim; Sanghoon Lee; Alan C. Bovik

doi:10.1109/ICIP.2015.7351467

3D visual discomfort predictor based on neural activity statistics

Heeseok Oh, Jongyoo Kim, Sanghoon Lee, Alan C. Bovik

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Visual discomfort assessment (VDA) on stereoscopic images is of fundamental importance for making decisions regarding visual fatigue caused by unnatural binocular alignment. Nevertheless, no solid framework exists to quantify this discomfort using models of the responses of visual neurons. Binocular vision is realized by means of neural mechanisms that subserve the sensorimotor control of eye movements. We propose a neuronal model-based framework called Neural 3D Visual Discomfort Predictor (N3D-VDP) that automatically predicts the level of visual discomfort experienced when viewing stereoscopic 3D (S3D) images. The N3D-VDP model extracts features derived by estimating the neural activity associated with the processing of binocular disparities. In this regard we deploy a model of disparity processing in the extra-striate middle temporal (MT) region of occipital lobe. We compare the performance of N3D-VDP with other recent VDA algorithms using correlations against reported subjective visual discomfort, and show that N3D-VDP is statistically superior to the other methods.

Original language	English
Title of host publication	2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
Publisher	IEEE Computer Society
Pages	3560-3564
Number of pages	5
ISBN (Electronic)	9781479983391
DOIs	https://doi.org/10.1109/ICIP.2015.7351467
Publication status	Published - 2015 Dec 9
Event	IEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada Duration: 2015 Sep 27 → 2015 Sep 30

Publication series

Name	Proceedings - International Conference on Image Processing, ICIP
Volume	2015-December
ISSN (Print)	1522-4880

Other

Other	IEEE International Conference on Image Processing, ICIP 2015
Country	Canada
City	Quebec City
Period	15/9/27 → 15/9/30

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

All Science Journal Classification (ASJC) codes

Software
Computer Vision and Pattern Recognition
Signal Processing

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10.1109/ICIP.2015.7351467

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Oh, H., Kim, J., Lee, S., & Bovik, A. C. (2015). 3D visual discomfort predictor based on neural activity statistics. In 2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings (pp. 3560-3564). [7351467] (Proceedings - International Conference on Image Processing, ICIP; Vol. 2015-December). IEEE Computer Society. https://doi.org/10.1109/ICIP.2015.7351467

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abstract = "Visual discomfort assessment (VDA) on stereoscopic images is of fundamental importance for making decisions regarding visual fatigue caused by unnatural binocular alignment. Nevertheless, no solid framework exists to quantify this discomfort using models of the responses of visual neurons. Binocular vision is realized by means of neural mechanisms that subserve the sensorimotor control of eye movements. We propose a neuronal model-based framework called Neural 3D Visual Discomfort Predictor (N3D-VDP) that automatically predicts the level of visual discomfort experienced when viewing stereoscopic 3D (S3D) images. The N3D-VDP model extracts features derived by estimating the neural activity associated with the processing of binocular disparities. In this regard we deploy a model of disparity processing in the extra-striate middle temporal (MT) region of occipital lobe. We compare the performance of N3D-VDP with other recent VDA algorithms using correlations against reported subjective visual discomfort, and show that N3D-VDP is statistically superior to the other methods.",

author = "Heeseok Oh and Jongyoo Kim and Sanghoon Lee and Bovik, {Alan C.}",

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doi = "10.1109/ICIP.2015.7351467",

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Oh, H, Kim, J, Lee, S & Bovik, AC 2015, 3D visual discomfort predictor based on neural activity statistics. in 2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings., 7351467, Proceedings - International Conference on Image Processing, ICIP, vol. 2015-December, IEEE Computer Society, pp. 3560-3564, IEEE International Conference on Image Processing, ICIP 2015, Quebec City, Canada, 15/9/27. https://doi.org/10.1109/ICIP.2015.7351467

3D visual discomfort predictor based on neural activity statistics. / Oh, Heeseok; Kim, Jongyoo; Lee, Sanghoon; Bovik, Alan C.

2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings. IEEE Computer Society, 2015. p. 3560-3564 7351467 (Proceedings - International Conference on Image Processing, ICIP; Vol. 2015-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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3D visual discomfort predictor based on neural activity statistics

Abstract

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