posted on 2024-06-12, 11:54authored byBin Jiang, Jiachen Yang, Na Jiang, Zhihan Lv, Qinggang MengQinggang Meng
Virtual reality technology is a new display technology, which provides users with real viewing experience. As known, most of the virtual reality display through stereoscopic images. However, image quality will be influenced by the collection, storage and transmission process. If the stereoscopic image quality in the virtual reality technology is seriously damaged, the user will feel uncomfortable, and this can even cause healthy problems. In this paper, we establish a set of accurate and effective evaluations for the virtual reality. In the preprocessing, we segment the original reference and distorted image into binocular regions and monocular regions. Then, the Information-weighted SSIM (IW-SSIM) or Information-weighted PSNR (IW-PSNR) values over the monocular regions are applied to obtain the IW-score. At the same time, the Stereo-weighted-SSIM (SW-SSIM) or Stereo-weighted-PSNR (SW-PSNR) can be used to calculate the SW-score. Finally, we pool the stereoscopic images score by combing the IW-score and SW-score. Experiments show that our method is very consistent with human subjective judgment standard in the evaluation of virtual reality technology.
Funding
This research is partially supported by National Natural Science Foundation of China (Nos. 61471260 and 61271324) and Natural Science Foundation of Tianjin (No. 16JCYBJC16000).
History
School
Science
Department
Computer Science
Published in
Neural Computing and Applications
Volume
29
Issue
5
Pages
1199-1208
Citation
JIANG, B. ... et al, 2018. Quality assessment for virtual reality technology based on real scene. Neural Computing and Applications, 29 (5), pp. 1199-1208.
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
Acceptance date
2016-12-19
Publication date
30-12-2024
Notes
This article was retracted by the publisher on 14 May 2024. Further details can be found here: https://doi.org/10.1007/s00521-024-09950-1
This is a post-peer-review, pre-copyedit version of an article published in Neural Computing and Applications. The final authenticated version is available online at: http://dx.doi.org/10.1007/s00521-016-2828-0