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Evaluation and monitoring of video quality for UMA enabled video streaming systems

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Abstract

This paper deals with monitoring user perception of multimedia presentations in a Universal Multimedia Access (UMA) enabled system using objective no-reference (NR) metrics. These NR metrics are designed for an UMA-enabled system, in a novel architecture, for a multimedia viewer. The first metric measures block-edge impairments in a video frame at the receiver end, based on the observation that they occur in regions with low spatial activity. The second metric evaluates the quality of the reconstructed video frame in the event of packet loss. Here, the structure of the artifact is itself exploited for the evaluation. Both the metrics involve low computational complexity and are feasible for real-time monitoring of streaming video in a multimedia communication scenario. Further, in rate-adaptive streaming of video, these metrics could serve as feedback parameters to dynamically adapt the bit rates based on network congestion.

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References

  1. Boyce J, Galianello R (1998) Packet loss effects on MPEG video sent over public internet. In: ACM international multimedia conference, pp 181–190

  2. Caviedes J, Gurbuz S (2002) No-reference sharpness metric based on local edge kurtosis. In: Proceedings of the international conference on image processing, vol 3. Rochester, NY, pp 53–56, 22–25 September

  3. Farias MCQ, Carli M, Mitra SK (2005) Objective video quality metric based on data hiding. IEEE Trans Consum Electron 51(3):983–992, August

    Google Scholar 

  4. Feamster N, Balakrishnan H (2002) Packet loss recovery for streaming video. In: International packet video workshop, April

  5. Gao W, Mermer C, Kim Y (2002) A de-blocking algorithm and a blockiness metric for highly compressed images. IEEE Trans Circuits Syst Video Technol 12(12):1150–1159, December

    Article  Google Scholar 

  6. Kimura J, Tobagi FA, Pulido JM, Emstad PJ (1999) Perceived quality and bandwidth characterization of layered MPEG-2 video encoding. In: SPIE intl. sym. on voice, video and data communications, September

  7. Lu L, Wang Z, Bovik AC, Kouloheris J (2002) Full-reference video quality assessment considering structural distortion and no-reference quality evaluation of mpeg video. In: IEEE international conference on multimedia and expo. Yorktown Heights, NY, USA, pp 61–64

  8. Marziliano P, Dufaux F, Winkler S, Ebrahimi T (2002) A no-reference perceptual blur metric. In: Proceedings of the international conference on image processing. vol 3. Rochester, NY, pp. 57–60, 22–25 September

  9. NTT DoCoMo. Error generating software (1996) Provided to the MPEG Resilience Ad Hoc Group Reflector on 31st October

  10. Pereira F, Burnett I (2003) Universal multimedia experiences for tomorrow. IEEE Signal Process Mag 20(2):63–73, March

    Article  Google Scholar 

  11. Perkis A, Abdejaoued Y, Christopoulos C, Ebrahimi T, Chicharo JF (2001) Universal multimedia access from wired and wireless systems. Circuits Syst Signal Process; Special issue on Multimedia Communications 20(3):387–402

    MATH  Google Scholar 

  12. Suthaharan S (2003) A perceptually significant block-edge impairment metric for digital video coding. In: Proceedings ICASSP’2003, vol 3. Hong Kong, pp 681–684

  13. Tektronix Test Sequences. ftp://ftp.tek.com/tv/test/streams/Element/index.html.

  14. Verscheure O, Frossard P, Hamdi M (1999) User-oriented QoS analysis in MPEG-2 video delivery. Real-time Imaging 5:305–314

    Article  Google Scholar 

  15. Video Quality Experts Group (VQEG). website: http://www.vqeg.org

  16. Vlachos T (2000) Detection of blocking artifacts in compressed video. Electron Lett 36(13): 1106–1108

    Article  Google Scholar 

  17. Wang Z. http://www.cns.nyu.edu/zwang/

  18. Wang Y, Zhu Q (1998) Error control and concealment for video communication: A review In: Proceedings of the IEEE, vol 86, no 5, May

  19. Wang Z, Bovik AC, Evans BL (2000) Blind measurement of blocking artifacts in images. In: Proceedings ICIP’00, vol 3, pp 981–984, September

  20. Wang Z, Sheikh HR, Bovik AC (2002) No-reference perceptual quality assessment of JPEG compressed images. In: Proceedings ICIP’02, vol 1, pp 477–480, September

  21. Winkler S (1999) A perceptual distortion metric for digital color video. In: Proceedings SPIE human vision and electronic imaging, vol 3644. San Jose, CA, USA, pp 175–184, January

  22. Winkler S, Sharma A, McNally D (2001) Perceptual video quality and blockiness metrics for multimedia streaming applications. In: Proceedings 4th international symposium on wireless personal multimedia communications. Aalborg, Denmark, pp 553–556, September

  23. Wu HR, Yuen M (1998) A generalized block-edge impairment metric for video coding. IEEE Signal Process Lett 70(3):247–278, November

    MATH  Google Scholar 

  24. Wu HR, Yuen M, Qiu B (1996) Video coding distortion classification and quantitative impairment metrics. In: International conference on signal processing, vol 2, pp 962–965, October

  25. Yang F, Wan S, Chang Y, Wu HR (2005) A novel objective no-reference metric for digital video quality assessment. IEEE Signal Process Lett 12(10):685–688, October

    Article  Google Scholar 

  26. Yuen M, Wu HR (1997) A survey of hybrid MC/DPCM/DCT video coding distortions. Signal Process 4(11):317–320, November

    Google Scholar 

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Correspondence to R. Venkatesh Babu.

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Venkatesh Babu, R., Perkis, A. & Hillestad, O.I. Evaluation and monitoring of video quality for UMA enabled video streaming systems. Multimed Tools Appl 37, 211–231 (2008). https://doi.org/10.1007/s11042-007-0140-9

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  • DOI: https://doi.org/10.1007/s11042-007-0140-9

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