Subjective Quality Assessment for Impaired Videos with Varying Spatial and Temporal Information
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.
[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.
[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.
@article{"International Journal of Information, Control and Computer Sciences:70381", author = "Muhammad Rehan Usman and Muhammad Arslan Usman and Soo Young Shin", title = "Subjective Quality Assessment for Impaired Videos with Varying Spatial and Temporal Information", 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.", volume = "9", number = "8", pages = "1861-6", }