Skip to main content
Log in

Impact of video content and transmission impairments on quality of experience

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript


The analysis of the impact of video content and transmission impairments on Quality of Experience (QoE) is a relevant topic for the robust design and adaptation of multimedia infrastructures, services, and applications. The goal of this paper is to study the impact of video content on QoE for different levels of impairments. In more details, this contribution aims at i) the study of the impact of delay, jitter, packet loss, and bandwidth on QoE, ii) the analysis of the impact of video content on QoE, and iii) the evaluation of the relationship between content related parameters (spatial-temporal perceptual information, motion, and data rate) and the QoE for different levels of impairments.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others


  1. Amin R, Jackson F, E Gilbert J, Martin J, Shaw T (2013) Assessing the impact of latency and jitter on the perceived quality of call of duty modern warfare 2. Springer: Human-Computer Interaction, pp 97–106. Users and Contexts of Use

  2. Battisti F, Carli M, Paudyal P (2014) QoS to QoE mapping model for wired/wireless video communication. In: Proceedings of the IEEE EuroMed Telco Conference, pp 1–6

  3. Cermak G (2005) Packet loss, bandwidth and latency affect judged quality of videoconferencing. In: Proceedings of the first international workshop on video processing and quality metrics for consumer electronics, pp 1–6

  4. Chen Y, Wu K, Zhang Q (2014) From QoS to QoE: a tutorial on video quality assessment. IEEE Commun Surv Tutorials 99

  5. Cisco Visual Networking Index (2013) Forecast and methodology, 2012–2017

  6. Cisco Visual Networking Index (2013) Global mobile data traffic forecast update, 2012–2017. Retrieved, August 20, 2013

  7. Claypool M, Tanner J (1999) The effects of jitter on the peceptual quality of video. In: Proceedings of the seventh ACM international conference on Multimedia (Part 2). ACM, pp 115–118

  8. Culibrk D, Mirkovic M, Zlokolica V, Pokric M, Kukolj D (2011) Salient motion features for video quality assessment. IEEE Trans Image Process 20(4):948–958

    Article  MathSciNet  Google Scholar 

  9. de la Cruz Ramos P, Vidal FG, Leal RP (2010) Perceived video quality estimation from spatial and temporal information contents and network performance parameters in IPTV. In: Proceeding of the Fifth International Conference on Digital Telecommunications, pp 128–131

  10. De Simone F, Naccari M, Tagliasacchi M, Dufaux F, Tubaro S, Ebrahimi T (2011) Subjective quality assessment of H.264/AVC video streaming with packet losses. In: EURASIP Journal on Image and Video Processing, pp 1–12

  11. Espina F, Morato D, Izal M, Magaña E (2014) Analytical model for MPEG video frame loss rates and playback interruptions on packet networks. Multim Tools Appl 72(1):361–383

    Article  Google Scholar 

  12. ETSI (2013) Speech and multimedia Transmission Quality (STQ); End-to-end jitter transmission planning requirements for real time service in an NGN context. In: ETSI TR 103 210 V1.1.1 Recommendation. ETSI

  13. Fliegel K (2014) Qualinet multimedia databases v5.0

  14. Garcia R, Kalva H (2014) Subjective evaluation of HEVC and AVC/H.264 in mobile environments, vol 60

  15. Gulliver SR, Ghinea G (2007) The perceptual and attentive impact of delay and jitter in multimedia delivery. IEEE Trans Broadcast 53:449–458

    Article  Google Scholar 

  16. Hemminger S, et al. (2005) Network emulation with netem. In: Linux conf au. Citeseer, pp 18–23

  17. Hogg RV, Ledolter J (1987) Engineering statistics. Macmillan Pub. Co.

  18. Hussain S, Harris R, Punchihewa A, Iqbal Z (2013) Dominant factors in the network domain that influence the QoE of an IPTV service. In: Proceedings of the IEEE European Modelling Symposium, pp 629–634

  19. Huynh-Thu Q, Ghanbari M (2006) Impact of jitter and jerkiness on perceived video quality

  20. Ickin S, Fiedler M, Wac K, Arlos P, Temiz C, Mkocha K (2014) VLQoE: video QoE instrumentation on the smartphone. Multim Tools Appl:1–31

  21. Intl Telecommunication UnionTelecommunication Standardization Sector (ITU-T) Study Group 12 (2007) Definition of Quality of Experience (QoE). Liaison Statement COM 12-LS 62-E SG12 TD 44 Rev1

  22. ITU-R (2012) Methodology for the subjective assessment of the quality of television pictures. ITU-R BT.500-13 Recommendation

  23. ITU-T (2007) Framework and methodologies for the determination and application of QoS parameters. In: ITU-T Study Group 2 Recommendation. ITU

  24. ITU-T (2008) Subjective video quality assessment methods for multimedia applications. In: ITU-T Study Group 9 Recommendation. ITU

  25. ITU-T Recommendation P.800.1 (2006) Mean opinion score (MOS) terminology

  26. Kang Y, Chen H, Xie1 L (2013) An artificial-neural-network-based QoE estimation model for video streaming over wireless networks. In: Proceedings of the 2nd IEEE/CIC International Conference on Communications (ICCC): QRS: QoS, Reliability and Security, pp 264–269

  27. Le Callet P, Möller S, Perkis A (2012) QUALINET white paper on definitions of quality of experience. European Network on Quality of Experience in Multimedia Systems and Services (COST Action IC 1003) Version 1.2

  28. Minhas TN, Lagunas OG, Arlos P, Fiedler M (2012) Mobile video sensitivity to packet loss and packet delay variation in terms of QoE. In: Proceeding of the IEEE 19th International Packet Video Workshop (83–88)

  29. Murphy S, Searles M, Rambeau C, Murphy L (2004) Evaluating the impact of network performance on video streaming quality for categorised video content. In: Proceedings of IEEE packet video, Irvine (CA), USA, pp 221–5

  30. Nightingale J, Wang Q, Grecos C, Goma S (2014) The impact of network impairment on Quality of Experience (QoE) in H.265/HEVC video streaming. IEEE Trans Consum Electron 60(2):242–250

    Article  Google Scholar 

  31. Paudyal P, Battisti F, Carli M (2014) A study on the effects of quality of service parameters on perceived video quality. In: Proceedings of the IEEE Fifth European Visual Information Processing (EUVIP), pp 1–6

  32. Pitrey Y, Barkowsky M, Pepion R, Le Callet P, Hlavacs H (2012) Influence of the source content and encoding configuration on the perceived quality for scalable video coding. Proc SPIE Human Vision and Electronic Imaging XVII 19(2):1–6

    Google Scholar 

  33. Report ITU-R M.2290-0 (2014) Future spectrum requirements estimate for terrestrial IMT. Retrieved, August

  34. Rodriguez DZ, Abrahao J, Begazo DC, Rosa RL, Bressan G (2012) Quality metric to assess video streaming service over TCP considering temporal location of pauses. IEEE Trans Consum Electron 58(3):985–992

    Article  Google Scholar 

  35. Saad M, Bovik A, Charrier C (2014) Blind prediction of natural video quality. IEEE Trans Image Process 23(3):1352–1365

    Article  MathSciNet  Google Scholar 

  36. Seshadrinathan K, Bovik AC (2010) Motion tuned spatio-temporal quality assessment of natural videos. IEEE Trans Image Process 19(2):335–350

    Article  MathSciNet  Google Scholar 

  37. Timmerer C, Ebrahimi T, Pereira F (2015) Toward a new assessment of quality. IEEE Networks 7:8

    Google Scholar 

  38. VideoLan, V.: Media player

  39. Wan Z, Xiong N, Ghani N, Vasilakos AV, Zhou L (2014) Adaptive unequal protection for wireless video transmission over ieee 802.11 e networks. Multim Tools Appl 72(1):541–571

    Article  Google Scholar 

  40. Wang Z, Wang W, Wan Z, Xia Y, Lin W (2014) No-reference hybrid video quality assessment based on partial least squares regression. Multim Tools Appl:1–14

  41. Zhang L, Gu Z, Liu X, Li H, Lu J (2014) Training quality-aware filters for no-reference image quality assessment. MultiMedia IEEE 21(4):67–75

    Article  Google Scholar 

  42. Zhang M, Muramatsu C, Zhou X, Hara T, Fujita H (2015) Blind image quality assessment using the joint statistics of generalized local binary pattern. IEEE Signal Process Lett 22(2):207–210

    Article  Google Scholar 

  43. Zhou C, Guo Y, Chen Y, Nie X, Zhu W (2014) Characterizing user watching behavior and video quality in mobile devices. In: Proceedings of the IEEE 23rd International Conference on Computer Communication and Networks (ICCCN), pp 1–6

  44. Zhou L, Yang Z, Wen Y, Rodrigues JJ (2014) Distributed wireless video scheduling with delayed control information. IEEE Trans Circuits Syst Video Technol 24(5):889–901

    Article  Google Scholar 

  45. Zhou L, Yang Z, Wen Y, Wang H, Guizani M (2013) Resource allocation with incomplete information for qoe-driven multimedia communications. IEEE Trans Wirel Commun 12(8):3733–3745

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Pradip Paudyal.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Paudyal, P., Battisti, F. & Carli, M. Impact of video content and transmission impairments on quality of experience. Multimed Tools Appl 75, 16461–16485 (2016).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: