Abstract
The interest of users towards three-dimensional (3D) video is gaining momentum due to the recent breakthroughs in 3D video entertainment, education, network, etc. technologies. In order to speed up the advancement of these technologies, monitoring quality of experience of the 3D video, which focuses on end user’s point of view rather than service-oriented provisions, becomes a central concept among the researchers. Thanks to the stereoscopic viewing ability of human visual system (HVS), the depth perception evaluation of the 3D video can be considered as one of the most critical parts of this central concept. Due to the lack of efficiently and widely utilized objective metrics in literature, the depth perception assessment can currently only be ensured by cost and time-wise troublesome subjective measurements. Therefore, a no-reference objective metric, which is highly effective especially for on the fly depth perception assessment, is developed in this paper. Three proposed algorithms (i.e., Z direction motion, structural average depth and depth deviation) significant for the HVS to perceive the depth of the 3D video are integrated together while developing the proposed metric. Considering the outcomes of the proposed metric, it can be clearly stated that the provision of better 3D video experience to the end users can be accelerated in a timely fashion for the Future Internet multimedia services.






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References
Hewage, C.T.: Perceptual quality driven 3-D video over networks. Doctoral Dissertation, University of Surrey (2008)
Yilmaz, G.N., No Reference, A.: Depth perception assessment metric for 3D video. Multimedia Tools Appl. 74(17), 6937–6950 (2015)
Chen, Z., Zhou, W., Li, W.: Blind stereoscopic video quality assessment: from depth perception to overall experience. IEEE Trans. Image Process. 27(2), 721–734 (2018)
Dumici, E., Grgic, S., Sakic, K., Rocha, P.M.R., Cruz, L.A.S.: 3D video subjective quality: a new database and grade comparison study. Multimed Tools Appl. 76, 2087–2109 (2017)
Hewage, C.T., Worrall, S.T., Dogan, S., Villette, S., Kondoz, A.M.: Quality evaluation of color plus depth map-based stereoscopic video. IEEE J. Select. Top. Signal Process. 3(2), 304–318 (2009)
Malekmohamadi, H., Fernando, A., Kondoz, A.: A new reduced reference metric for color plus depth 3D video. J. Vis. Commun. Image Represent. 25(3), 534–541 (2014)
Le, T.H., Jung, S.W., Won, C.S.: A new depth image quality metric using a pair of color and depth images. Multimedia Tools Appl. 76, 1–19 (2016)
Li, Y., Po, L.M., Cheung, C.H., Xu, X., Feng, L., Yuan, F., Cheung, K.W.: No-reference video quality assessment with 3D shearlet transform and convolutional neural networks. IEEE Trans. Circ. Syst. Video Technol. 26(6), 1044–1057 (2016)
Lv, Y., Yu, M., Jiang, G., Shao, F., Peng, Z., Chen, F.: No-reference stereoscopic image quality assessment using binocular self-similarity and deep neural network. Sig. Process. Image Commun. 47, 346–357 (2016)
Huynh-Thu, Q., Ghanbari, M.: Scope of validity of PSNR in image/video quality assessment. IET Electron. Lett. 44(30), 800–801 (2008)
Pinson, M.H., Wolf, S.: A new standardized method for objectively measuring video quality. IEEE Trans. Broadcast. 50(3), 312–322 (2004)
Wang, Z., Lu, L., Bovik, A.C.: Video quality assessment based on structural distortion measurement. Sig. Process. Image Commun. 19(2), 121–132 (2004)
Khaustova, D., Fournier, J., Le Meur, O.: An objective metric for stereoscopic 3D video quality prediction using perceptual thresholds. Motion Imaging J. 124(2), 47–55 (2015)
Beverley, K.I., Regan, D.: Visual perception of changing size: the effect of object size. Vis. Res. 19(10), 1093–1104 (1979)
Cutting, J.E., Vishton, P.M.: Perceiving layout and knowing distance: the integration, relative potency and contextual use of different information about depth. In: Rogers, S., Epstein, W. (eds.) Perception of space and motion. New York: Academic, pp. 69–117 (1995)
JSVM 9.13.1. CVS Server [Online]. Available Telnet: http://garcon.ient.rwth aachen.de:/cvs/jvt
ITU-R: BT.500-11. Methodology for the subjective assessment of the quality of television pictures
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Bayrak, H., Nur Yilmaz, G. A depth perception evaluation metric for immersive user experience towards 3D multimedia services. Multimedia Systems 25, 253–261 (2019). https://doi.org/10.1007/s00530-018-00602-8
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DOI: https://doi.org/10.1007/s00530-018-00602-8