Depth Perception Assessment of a 3D Video Based on Spatial Resolution

Year 2022, Volume: 2 Issue: 1, 1 - 7, 30.06.2022

Gökçe Nur Yılmaz , Yücel Çimtay

Abstract

Burgeoning advances in 3 Dimensional (3D) video technologies can only be emphasized by considering the impact of these technologies on the perception of 3D videos from a user point of view. It is a fact that enabling this can be achieved by considering key factors characterizing the nature of a 3D video. Under the light of this fact, spatial resolution and perceptually significant depth levels, which are two effective factors for the depth perception of a 3D video, are used to develop a Reduced Reference (RR) model for the depth perception prediction of a 3D video. While determining the perceptually significant features, bilateral filter is exploited. Structural SIMilarity metric (SSIM) is used to predict the depth perception enabled considering the degradation in the perceptually important features of depth maps having different spatial resolutions. The performance results of the developed model prove that it is quite effective in the depth perception prediction of a 3D video.

Keywords

depth perception, 3D video, spatial resolution

Supporting Institution

Scientific and Technological Research Council of Turkey (TÜBITAK)

Project Number

Tubitak 114E551

References

• [1] Nur Yilmaz G. and Battisti F., “Depth Perception Prediction of 3D Video for Ensuring Advanced Multimedia Services,” IEEE 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video, Stockholm-Helsinki, Sweden-Finland, 3-5 June 2018.
• [2] Nur G. and Bozdagi Akar G., “An Abstraction Based Reduced Reference Depth Perception Metric for 3D Video,” International Conference on Image Processing (ICIP), Orlando, Florida, USA, 30 September-3 October 2012.
• [3] Nur Yilmaz G., “A Novel Depth Perception Prediction Metric for Advanced Multimedia Applications,” Springer Multimedia Systems, 2019.
• [4] Perkis et.al., “QUALINET White Paper on Definitions of Immersive Media Experience (IMEx),” arXiv:2007.07032, 2020. [5] Huynh-Thu and Ghanbari, “Scope of validity of PSNR in image/video quality M. assessment,” IET Electronics Letters, vol. 44, no. 13, pp. 800–801, Jun. 2008.
• [6] Wang Z., Lu L., and Bovik A. C., “Video Quality Assessment Based on Structural Distortion Measurement,” Proc. of Signal Processing: Image Com., vol. 19, no. 2, pp. 121-132, Feb. 2004.
• [7] Pinson M.H. and Wolf S., “A New Standardized Method for Objectively Measuring Video Quality,” IEEE Trans. Broadcasting, vol. 50, no. 3, pp. 312-322, Sep. 2004.
• [8] Kim D. and Min D., Oh J., Jeon S., and Sohn K., “Depth Map Quality Metric for Three-Dimensional Video,” SPIE Stereoscopic Displays and Applications, San Jose, CA, USA, 18 Jan. 2009.
• [9] De Silva D.V.S.X., Nur G., Ekmekcioglu E., and Kondoz A., “QoE of 3D Media Delivery Systems,” Media Networks: Architectures, Applications, and Standards, CRC Press Taylor and Francis Group, May 2012.
• [10] Lebreton P., Raake A., Barkowsky M., Le Callet P., “Evaluating Depth Perception of 3D Stereoscopic Videos,” IEEE Journal of Selected Topics in Signal Processing, vol.6, pp. 710-720, October 2012.
• [11] Chaminda T.E.R. and Martini M. G., “Quality Evaluation for Real-Time Video Services,” IEEE international Conference on Multimedia and Expo, 11-15 July 2011.
• [12] Nur G., Dogan S., Kodikara Arachchi H., and Kondoz A.M., “Impact of Depth Map Spatial Resolution on 3D Video Quality and Depth Perception,” IEEE 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video, Tampere, Finland, 7-9 June 2010.
• [13] Advanced Video Coding for Generic Audiovisual Services, ITU-T Rec. H.264 (03/2005) Std., MPEG-4 AVC/H.264 Video Group.
• [14] JSVM 9.13.1. CVS Server [Online]. Available Telnet: garcon.ient.rwth aachen.de:/cvs/jvt
• [15] ITU-R BT.500–11, Methodology for the subjective assessment of the quality of television pictures.