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Subjective Quality Assessment for Impaired Videos with Varying Spatial and Temporal Information

Authors: Muhammad Rehan Usman, Muhammad Arslan Usman, Soo Young Shin

Abstract:

The new era of digital communication has brought up many challenges that network operators need to overcome. The high demand of mobile data rates require improved networks, which is a challenge for the operators in terms of maintaining the quality of experience (QoE) for their consumers. In live video transmission, there is a sheer need for live surveillance of the videos in order to maintain the quality of the network. For this purpose objective algorithms are employed to monitor the quality of the videos that are transmitted over a network. In order to test these objective algorithms, subjective quality assessment of the streamed videos is required, as the human eye is the best source of perceptual assessment. In this paper we have conducted subjective evaluation of videos with varying spatial and temporal impairments. These videos were impaired with frame freezing distortions so that the impact of frame freezing on the quality of experience could be studied. We present subjective Mean Opinion Score (MOS) for these videos that can be used for fine tuning the objective algorithms for video quality assessment.

Keywords: Frame freezing, mean opinion score, objective assessment, subjective evaluation.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1107517

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References:


[1] Index, Cisco Visual Networking. "Global mobile data traffic forecast update, 2010-2015," White Paper, Feb. 2011.
[2] J. Nightingale, Qi Wang, C. Grecos, and S. Goma, "The impact of network impairment on quality of experience (QoE) in H. 265/HEVC video streaming," IEEE Transactions on Consumer Electronics, vol.60, issue.2, pp. 242-250, May 2014.
[3] Video Quality Experts Group VQEG, “Final rep. from the video quality experts group on the validation of objective models of video quality assessment VQEG,” 2000. (Online). Available: www.vqeg.org
[4] Tutorial, I. T. U. T. "Objective perceptual assessment of video quality: full reference television." ITU-T Telecommunication Standardization Bureau, 2004. (Online). Available www.itu.int/ITU-T.
[5] Yuen, Michael, and H. R. Wu. "A survey of hybrid MC/DPCM/DCT video coding distortions." Signal processing 70.3 (1998): 247-278.
[6] Winkler, Stefan, and Ruth Campos. "Video quality evaluation for Internet streaming applications." Electronic Imaging 2003. International Society for Optics and Photonics, 2003.
[7] Muntean, Gabriel-Miro, Philip Perry, and Liam Murphy. "Subjective assessment of the quality-oriented adaptive scheme." Broadcasting, IEEE Transactions on51.3 (2005): 276-286.
[8] Zhai, Guangtao, et al. "Cross-dimensional perceptual quality assessment for low bit-rate videos." Multimedia, IEEE Transactions on 10.7 (2008): 1316-1324.
[9] M. Shahid, A. K. Singam, A. Rossholm, and B. Lovstrom, "Subjective quality assessment of H. 264/AVC encoded low resolution videos," IEEE 5th International Congress on Image and Signal Processing (CISP), pp. 63-67., Oct. 2012.
[10] ITU-T RECOMMENDATION, P, "Subjective video quality assessment methods for multimedia applications," pp. 34-35, 1999.
[11] “ITU-R Radio communication Sector of ITU, Recommendation ITU-R BT.500-12,” 2009.