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Quality assessment for virtual reality technology based on real scene

  • Neural Computing in Next Generation Virtual Reality Technology
  • Published:
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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.

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Acknowledgements

This research is partially supported by National Natural Science Foundation of China (Nos. 61471260 and 61271324) and Natural Science Foundation of Tianjin (No. 16JCYBJC16000).

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Authors and Affiliations

  1. School of Electronic Information Engineering, Tianjin University, Tianjin, People’s Republic of China

    Bin Jiang & Jiachen Yang

  2. Management Services Company of the First Mining Area, Da Gang Oilfield, PetroChina, Tianjin, People’s Republic of China

    Na Jiang

  3. Department of Computer Science, University College London, London, UK

    Zhihan Lv

  4. Department of Computer Science, School of Science at Loughborough University, Loughborough, UK

    Qinggang Meng

Authors
  1. Bin Jiang
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  2. Jiachen Yang
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  3. Na Jiang
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  4. Zhihan Lv
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  5. Qinggang Meng
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Correspondence to Zhihan Lv.

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Jiang, B., Yang, J., Jiang, N. et al. Quality assessment for virtual reality technology based on real scene. Neural Comput & Applic 29, 1199–1208 (2018). https://doi.org/10.1007/s00521-016-2828-0

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  • DOI: https://doi.org/10.1007/s00521-016-2828-0

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