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Advances in Multimedia
Volume 2017 (2017), Article ID 8317590, 19 pages
https://doi.org/10.1155/2017/8317590
Research Article

A No-Reference Modular Video Quality Prediction Model for H.265/HEVC and VP9 Codecs on a Mobile Device

IP Communications Laboratory, School of Information Technology, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand

Correspondence should be addressed to Debajyoti Pal; moc.liamg@lap.itoyjabed

Received 14 September 2017; Revised 25 October 2017; Accepted 6 November 2017; Published 23 November 2017

Academic Editor: Constantine Kotropoulos

Copyright © 2017 Debajyoti Pal and Vajirasak Vanijja. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. 2013 Video Index-TV is no longer a single screen in your Living Room, Ooyala Corp, USA, 2013.
  2. Cisco Global Mobile Data Traffic Forecast Update Report 2014–2019, Cisco Corp, USA, 2016.
  3. “Definitions of Terms related to Quality of Service,” ITU-T Recommendation E.800, September, 2008.
  4. P. Le Callet, S. Möller, and A. Perkis, Qualinet White Paper on Definitions of Quality of Experience- 2012, Lausanne, Switzerland, 2012.
  5. T. Hoßfeld, R. Schatz, M. Varela, and C. Timmerer, “Challenges of QoE management for cloud applications,” IEEE Communications Magazine, vol. 50, no. 4, pp. 28–36, 2012. View at Publisher · View at Google Scholar · View at Scopus
  6. “Subjective Video Quality Assessment Methods for Multimedia Applications,” ITU-T Recommendation P.910, June 200.
  7. “Methodology for the Subjective Assessment of the Quality of Television Pictures,” ITU-T Recommendation BT.500, January 2012.
  8. “Methods for Subjective Determination of Transmission Quality,” ITU-T Recommendation P.800, August 1996.
  9. F. M. Moss, K. Wang, F. Zhang, R. Baddeley, and D. R. Bull, “On the optimal presentation duration for subjective video quality assessment,” IEEE Transactions on Circuits and Systems for Video Technology, vol. PP, no. 99, 2015. View at Publisher · View at Google Scholar · View at Scopus
  10. M. Pinson and S. Wolf, “Comparing subjective video quality testing methodologies,” in Proceedings of the Visual Communications and Image Processing 2003, pp. 573–582, Switzerland, July 2003. View at Publisher · View at Google Scholar · View at Scopus
  11. D. M. Rouse, R. Pépion, P. Le Callet, and S. S. Hemami, “Tradeoffs in subjective testing methods for image and video quality assessment,” in Proceedings of the Human Vision and Electronic Imaging XV, USA, January 2010. View at Publisher · View at Google Scholar · View at Scopus
  12. “Reference Algorithm for Computing Peak Signal to Noise Ratio of a Processed Video Sequence with Compensation for Constant Spatial Shifts, Constant Temporal Shift, and Constant Luminance Gain and Offset,” TU-T Recommendation J.340, June 2010.
  13. Z. Wang, A. C. Bovik, H. R. Sheikh, and 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. View at Publisher · View at Google Scholar · View at Scopus
  14. “Objective Perceptual Video Quality Measurement Techniques for Digital Cable Television in the Presence of a Full Reference,” ITU-T Recommendation J.144, March 2001.
  15. “Objective Perceptual Video Quality Measurement Techniques for Standard Definition Digital Broadcast Television in the Presence of a Full Reference,” ITU-R Recommendation BT.1683, June 2004.
  16. S. Kanumuri, P. C. Cosman, A. R. Reibman, and V. A. Vaishampayan, “Modeling Packet-Loss Visibility in MPEG-2 Video,” IEEE Transactions on Multimedia, vol. 8, no. 2, pp. 341–355, 2006. View at Publisher · View at Google Scholar · View at Scopus
  17. J. Søgaard, S. Forchhammer, and J. Korhonen, “No-Reference Video Quality Assessment Using Codec Analysis,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 25, no. 10, pp. 1637–1650, 2015. View at Publisher · View at Google Scholar · View at Scopus
  18. M. Shahid, A. Rossholm, B. Lövström, and H.-J. Zepernick, “No-reference image and video quality assessment: a classification and review of recent approaches,” Eurasip Journal on Image and Video Processing, vol. 2014, no. 1, article no. 40, 2014. View at Publisher · View at Google Scholar · View at Scopus
  19. “Opinion Model for Video Telephony Applications,” ITU-T Recommendation G.1070, July 2012.
  20. M. Mu, P. Romaniak, A. Mauthe, M. Leszczuk, L. Janowski, and E. Cerqueira, “Framework for the integrated video quality assessment,” Multimedia Tools and Applications, vol. 61, no. 3, pp. 787–817, 2012. View at Publisher · View at Google Scholar · View at Scopus
  21. “Parametric Bit-stream based Quality Assessment of Progressive Download and Adaptive Audio-visual Streaming Services over Reliable Transport,” ITU-T Recommendation P.1203, January 2017, ITU-T Recommendation P.1203.
  22. “Objective Quality Measurement of Telephone Band (300-3400 Hz) Speech Codec,” ITU-T Recommendation P.861, August 1996.
  23. S. Khirman and P. Henricksen, “Relationship between Quality of Service and Quality of Experience for Public Internet Services,” in Proceedings of the 3rd Workshop on Passive and Active Measurement, pp. 23–28, March 2002.
  24. M. Fiedler, T. Hossfeld, and P. Tran-Gia, “A generic quantitative relationship between quality of experience and quality of service,” IEEE Network, vol. 24, no. 2, pp. 36–41, 2010. View at Publisher · View at Google Scholar · View at Scopus
  25. P. Reichl, S. Egger, R. Schatz, and A. D'Alconzo, “The logarithmic nature of QoE and the role of the Weber-Fechner law in QoE assessment,” in Proceedings of the IEEE International Conference on Communications (ICC '10), pp. 1–5, Cape Town, South Africa, May 2010. View at Publisher · View at Google Scholar · View at Scopus
  26. J. A. Lozano, A. Castro, B. Fuentes, J. M. González, and Á. Rodríguez, “Adaptive QoE measurement on Video streaming IP services,” in Proceedings of the 7th International Conference on Network and Service Management, pp. 1–4, Paris, fra, 2011.
  27. H. J. Kim and S. G. Choi, “QoE assessment model for multimedia streaming services using QoS parameters,” Multimedia Tools and Applications, pp. 1–13, 2013. View at Publisher · View at Google Scholar · View at Scopus
  28. W. Song, D. Tjondronegoro, and M. Docherty, “Exploration and optimization of user experience in viewing videos on a mobile phone,” International Journal of Software Engineering and Knowledge Engineering, vol. 20, no. 8, pp. 1045–1075, 2010. View at Publisher · View at Google Scholar
  29. H. Knoche, J. D. McCarthy, and M. A. Sasse, “Can small be beautiful? assessing image resolution requirements for mobile TV,” in Proceedings of the 13th ACM International Conference on Multimedia, MM 2005, pp. 829–838, Singapore, November 2005. View at Publisher · View at Google Scholar · View at Scopus
  30. Y.-F. Ou, Y. Xue, Z. Ma, and Y. Wang, “A perceptual video quality model for mobile platform considering impact of spatial, temporal, and amplitude resolutions,” in Proceedings of the 2011 IEEE 10th IVMSP Workshop: Perception and Visual Signal Analysis, IVMSP 2011, pp. 117–122, usa, June 2011. View at Publisher · View at Google Scholar · View at Scopus
  31. W. Song, Y. Xiao, D. Tjondronegoro, and A. Liotta, “QoE modelling for VP9 and H.265 videos on mobile devices,” in Proceedings of the 23rd ACM International Conference on Multimedia, MM 2015, pp. 501–510, Australia, October 2015. View at Publisher · View at Google Scholar · View at Scopus
  32. A. Khan, L. Sun, and E. Ifeachor, “Content clustering based video quality prediction model for MPEG4 video streaming over wireless networks,” in Proceedings of the 2009 IEEE International Conference on Communications, ICC 2009, Germany, June 2009. View at Publisher · View at Google Scholar · View at Scopus
  33. H. Koumaras, A. Kourtis, C.-H. Lin, and C.-K. Shieh, “A theoretical framework for end-to-end video quality prediction of MPEG-based sequences,” in Proceedings of the 3rd International Conference on Networking and Services, ICNS 2007, Greece, June 2007. View at Publisher · View at Google Scholar · View at Scopus
  34. Z. Duanmu, A. Rehman, K. Zeng, and Z. Wang, “Quality-of-experience prediction for streaming video,” in Proceedings of the 2016 IEEE International Conference on Multimedia and Expo, ICME 2016, USA, July 2016. View at Publisher · View at Google Scholar · View at Scopus
  35. P. Calyam, E. Ekici, C.-G. Lee, M. Haffner, and N. Howes, “A "GAP-model" based framework for online VVoIP QoE measurement,” Journal of Communications and Networks, vol. 9, no. 4, pp. 446–455, 2007. View at Publisher · View at Google Scholar · View at Scopus
  36. A. Khan, L. Sun, and E. Ifeachor, “Learning models for video quality prediction over wireless local area network and universal mobile telecommunication system networks,” IET Communications, vol. 4, no. 12, pp. 1389–1403, 2010. View at Publisher · View at Google Scholar · View at Scopus
  37. D. Yun and K. Chung, “DASH-based Multi-view Video Streaming System,” IEEE Transactions on Circuits and Systems for Video Technology, pp. 1–1. View at Publisher · View at Google Scholar
  38. S. Colonnese, F. Cuomo, T. Melodia, and I. Rubin, “A Cross-Layer Bandwidth Allocation Scheme for HTTP-Based Video Streaming in LTE Cellular Networks,” IEEE Communications Letters, vol. 21, no. 2, pp. 386–389, 2017. View at Publisher · View at Google Scholar · View at Scopus
  39. K. Jia, Y. Guo, Y. Chen, and Y. Zhao, “Measuring and Predicting Quality of Experience of DASH-based Video Streaming over LTE,” in Proceedings of the 19th International Symposium on Wireless Personal Multimedia Communications (WPMC), pp. 102–107, Shenzhen, China, 2016.
  40. T. Maki, M. Varela, and D. Ammar, “A Layered Model for Quality Estimation of HTTP Video from QoS Measurements,” in Proceedings of the 11th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2015, pp. 591–598, tha, November 2015. View at Publisher · View at Google Scholar · View at Scopus
  41. J. Jiang, V. Sekar, and H. Zhang, “Improving fairness, efficiency, and stability in HTTP-based adaptive video streaming with festive,” IEEE/ACM Transactions on Networking, vol. 22, no. 1, pp. 326–340, 2014. View at Publisher · View at Google Scholar · View at Scopus
  42. Y. Chen, K. Wu, and Q. Zhang, “From QoS to QoE: A tutorial on video quality assessment,” IEEE Communications Surveys & Tutorials, vol. 17, no. 2, pp. 1126–1165, 2015. View at Publisher · View at Google Scholar · View at Scopus
  43. M. Seufert, S. Egger, M. Slanina, T. Zinner, T. Hoßfeld, and P. Tran-Gia, “A survey on quality of experience of HTTP adaptive streaming,” IEEE Communications Surveys & Tutorials, vol. 17, no. 1, pp. 469–492, 2015. View at Publisher · View at Google Scholar · View at Scopus
  44. P. Juluri, T. Venkatesh, and D. Medhi, “Measurement of quality of experience of video-on-demand services: a survey,” IEEE Communications Surveys & Tutorials, 2015. View at Publisher · View at Google Scholar
  45. “VQEG Standard Database maintained,” http://www.its.bldrdoc.gov/vqeg/downloads.aspx.
  46. J. Nightingale, Q. 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, no. 2, pp. 242–250, 2014. View at Publisher · View at Google Scholar · View at Scopus
  47. “Network Performance Objectives for IP-based Services,” TU-T Recommendation Y.1541, December 2011.
  48. K. Gu, J. Zhou, J.-F. Qiao, G. Zhai, W. Lin, and A. C. Bovik, “No-reference quality assessment of screen content pictures,” IEEE Transactions on Image Processing, vol. 26, no. 8, pp. 4005–4018, 2017. View at Publisher · View at Google Scholar · View at MathSciNet
  49. H. Malekmohamadi, W. A. C. Fernando, and A. M. Kondoz, “Content-based subjective quality prediction in stereoscopic videos with machine learning,” IEEE Electronics Letters, vol. 48, no. 21, pp. 1344–1346, 2012. View at Publisher · View at Google Scholar · View at Scopus
  50. T. Ghalut, H. Larijani, and A. Shahrabi, “Content-based video quality prediction using random neural networks for video streaming over LTE networks,” in Proceedings of the 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015, pp. 1626–1631, gbr, October 2015. View at Publisher · View at Google Scholar · View at Scopus
  51. “Framework and Methodologies for the Determination and Application of QoS Parameters,” ITU-T Recommendation E.802, February 2007.
  52. “Speech and Multimedia Transmission Quality (STQ); End-to-End Jitter Transmission Planning Requirements for Real Time Services in an NGN Context,” ETSI TR 103 210 v.1.1.1 (2013-10) Recommendation, 2013.
  53. J. Klaue, B. Rathke, and A. Wolisz, “Evalvid–a framework for video transmission and quality evaluation,” in Computer Performance Evaluation. Modelling Techniques and Tools, vol. 2794 of Lecture Notes in Computer Science, pp. 255–272, Springer, New York, NY, USA, 2003. View at Publisher · View at Google Scholar
  54. “NS2,” http://www.isi.edu/nsnam/ns/.
  55. L. H. Hardy, G. Rand, and M. C. Rittler, “Tests for the Detection and Analysis of Color-Blindness III The Rabkin Test,” Journal of the Optical Society of America, vol. 35, no. 7, p. 481, 1945. View at Publisher · View at Google Scholar
  56. T. L. Saaty, The Analytic Hierarchy Process, McGraw-Hill, New York, NY, USA, 1980. View at MathSciNet
  57. F. Zahedi, “The analytic hierarchy process-a survey of t he method and its applications,” Interfaces, vol. 16, no. 4, pp. 96–108, 1986. View at Publisher · View at Google Scholar
  58. X. Zhang, L. Wu, Y. Fang, and H. Jiang, “A study of FR video quality assessment of real time video stream,” International Journal of Advanced Computer Science and Applications, vol. 3, no. 6, 2012. View at Publisher · View at Google Scholar
  59. P. Reichl, S. Egger, S. Moller et al., “Towards a comprehensive framework for QOE and user behavior modelling,” in Proceedings of the 17th International Workshop on Quality of Multimedia Experience (QoMEX '15), pp. 1–6, IEEE, Pylos-Nestoras, Greece, May 2015. View at Publisher · View at Google Scholar
  60. L. Pierucci and D. Micheli, “A Neural Network for Quality of Experience Estimation in Mobile Communications,” IEEE MultiMedia, vol. 23, no. 4, pp. 42–49, 2016. View at Publisher · View at Google Scholar · View at Scopus
  61. E. Danish, M. Alreshoodi, A. Fernando, B. Alzahrani, and S. Alharthi, “Cross-layer QoE prediction for mobile video based on random neural networks,” in Proceedings of the IEEE International Conference on Consumer Electronics, ICCE 2016, pp. 227-228, USA, January 2016. View at Publisher · View at Google Scholar · View at Scopus