Visual assessment of equirectangular images for virtual reality applications In Unity
Resumo
Virtual Reality (VR) applications provide an immersive experience when using panoramic images that contain a 360-degree view of the scene. Currently, the equirectangular image format is the widely used pattern to represent these panoramic images. The development of a virtual reality viewer of panoramic images should consider several parameters that define the quality of the rendered image. Such parameters include resolution configurations, texture-to-objects mappings and deciding from different rendering approach, but to select the optimal value of these parameters, visual quality analysis is required. In this work, we propose a tool integrated within Unity editor to automate this quality assessment using different settings for the visualization of equirectangular images. We compare the texture mapping of a skybox with a procedural sphere and a cubemap using full-reference objective metrics for Image Quality Analysis (IQA). Based on the assessment results, the tool decides how the final image will be rendered at the target device to produce a visually pleasing and high-quality image.
Referências
P. Fuchs, Virtual Reality Headsets-A Theoretical and Pragmatic Approach. CRC Press, 2017.
V. Zakharchenko, K. P. Choi, and J. H. Park, “Quality metric for spherical panoramic video,” in Optics and Photonics for Information Processing X, vol. 9970. International Society for Optics and Photonics, 2016, p. 99700C.
C. Dunn and B. Knott, “Resolution-defined projections for virtual reality video compression,” in Virtual Reality (VR), 2017 IEEE. IEEE, 2017, pp. 337–338.
F. Duanmu, Y. He, X. Xiu, P. Hanhart, Y. Ye, and Y. Wang, “Hybrid cubemap projection format for 360-degree video coding,” in 2018 Data Compression Conference. IEEE, 2018, pp. 404–404.
Z. Wang and A. C. Bovik, “Modern image quality assessment,” Synthesis Lectures on Image, Video, and Multimedia Processing, vol. 2, no. 1, pp. 1–156, 2006.
M. H. Pinson and S. Wolf, “Comparing subjective video quality testing methodologies,” in Visual Communications and Image Processing 2003, vol. 5150. International Society for Optics and Photonics, 2003, pp. 573–583.
C. Li, M. Xu, S. Zhang, and P. L. Callet, “State-of-the-art in 360o video/image processing: Perception, assessment and compression,” arXiv preprint arXiv:1905.00161, 2019.
S. K. Md, B. Appina, and S. S. Channappayya, “Full-reference stereo image quality assessment using natural stereo scene statistics,” IEEE Signal Processing Letters, vol. 22, no. 11, pp. 1985–1989, 2015.
A. M. Gil and T. S. Figueira, “Equirectangular image quality assessment tool integrated into the unity editor,” in International Conference on Human-Computer Interaction. Springer, 2019, pp. 374–381.
Z. Wang, A. C. Bovik, H. R. Sheikh, E. P. Simoncelli, “Image quality assessment: from error visibility to structural similarity,” IEEE transactions on image processing, vol. 13, no. 4, pp. 600–612, 2004.