Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/24512

Title: Quality assessment for virtual reality technology based on real scene
Authors: Jiang, Bin
Yang, Jiachen
Jiang, Na
Lv, Zhihan
Meng, Qinggang
Keywords: Virtual reality
Stereoscopic images quality
Binocular regions
Monocular regions
Information-weighted
Stereo-weighted
Issue Date: 2016
Publisher: © The Natural Computing Applications Forum. Published by Springer
Citation: JIANG, B. ... et al, 2016. Quality assessment for virtual reality technology based on real scene. Neural Computing and Applications, doi:10.1007/s00521-016-2828-0.
Abstract: 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.
Description: This paper is closed access until 30th December 2017.
Sponsor: This research is partially supported by National Natural Science Foundation of China (Nos. 61471260 and 61271324) and Natural Science Foundation of Tianjin (No. 16JCYBJC16000).
Version: Accepted for publication
DOI: 10.1007/s00521-016-2828-0
URI: https://dspace.lboro.ac.uk/2134/24512
Publisher Link: http://dx.doi.org/10.1007/s00521-016-2828-0
ISSN: 0941-0643
Appears in Collections:Closed Access (Computer Science)

Files associated with this item:

File Description SizeFormat
NCAA.pdfAccepted version2.95 MBAdobe PDFView/Open

 

SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.