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QoS to QoE Mapping Function for Iptv Quality Assessement Based on Kohonen Map: A Pilot Study Cover

QoS to QoE Mapping Function for Iptv Quality Assessement Based on Kohonen Map: A Pilot Study

Open Access
|Jun 2020

References

  1. 1. Akhtar, Z., Siddique, K., Rattani, A., Lutfi S.L., Falk, T.H. (2019) Why is Multimedia Quality of Experience Assessment a Challenging Problem? IEEE Access, 7, pp. 117897-117915.10.1109/ACCESS.2019.2936470
  2. 2. Anegekuh, L., Sun, L., Jammeh, E., Mkwawa, I., Ifeachor, E. (2015) Content-Based Video Quality Prediction for HEVC Encoded Videos Streamed Over Packet Networks. IEEE Transactions on Multimedia, 17(8), pp. 1323-1334.10.1109/TMM.2015.2444098
  3. 3. Bampis, C.G., Li Z., Bovik, A.C. (2019) Spatiotemporal Feature Integration and Model Fusion for Full Reference Video Quality Assessment. IEEE Transactions on Circuits and Systems for Video Technology, 29(8), pp. 2256-2270.10.1109/TCSVT.2018.2868262
  4. 4. Blazekova, O., Vojtekova. M. (2019) Using of Parallel Coordinates in Finding Minimum Distance in Time-Space. Communications - Scientific Letters of the University of Zilina, 21(3), pp. 3-7.10.26552/com.C.2019.3.3-7
  5. 5. Carvalho, F.D.T., Bertrand, P., Simoes, E.C. (2016) Batch SOM algorithms for interval-valued data with automatic weighting of the variables. Neurocomputing, vol. 182, pp. 66-81.10.1016/j.neucom.2015.11.084
  6. 6. Cheng, Z., Ding, L., Huang, W., Yang, F., Qian, L. (2017) A unified QoE prediction framework for HEVC encoded video streaming over wireless networks. IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), pp. 1-6.10.1109/BMSB.2017.7986156
  7. 7. Dybskaya, V. V., Sverchkov, P. A. (2017) Designing a Rational Distribution Network for Trading Companies. Transport and Telecommunication Journal, 18(3), pp. 181-193.10.1515/ttj-2017-0016
  8. 8. Frnda, J., Nedoma, J., Vanus, J., Martinek, R. (2019) A Hybrid QoS-QoE Estimation System for IPTV Service. Electronics, 8(5), 585.10.3390/electronics8050585
  9. 9. Gu, K., Tao, D., Qiao J., Lin, W. (2018) Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data. IEEE Transactions on Neural Networks and Learning Systems, 29(4), pp. 1301-1313.10.1109/TNNLS.2017.2649101
  10. 10. International Telecommunications Union, ITU-T P.910. (2008) Subjective video quality assessment methods for multimedia applications.
  11. 11. International Telecommunications Union, ITU-T P.913. (2016) Methods for the subjective assessment of video quality, audio quality and audiovisual quality of Internet video and distribution quality television in any environment.
  12. 12. Kohonen, T. (1998) The self-organizing map. Neurocomputing, 21, pp. 1-6.10.1016/S0925-2312(98)00030-7
  13. 13. Loh, W., Bong, D.B.L. (2018) A Just Noticeable Difference-Based Video Quality Assessment Method with Low Computational Complexity. Sensing and Imaging, 19, Article number: 33.10.1007/s11220-018-0216-9
  14. 14. Loktev, Daniil A., Loktev, Alexey A., Salnikova, Alexandra V., Shaforostova, Anna A. (2019) Determination of the Dynamic Vehicle Model Parameters by Means of Computer Vision. Communications - Scientific letters of the University of Zilina, 21(3), pp. 28-34.10.26552/com.C.2019.3.28-34
  15. 15. Mocanu, D.C., Pokhrel, J., Pablo Garella, J., Seppänen, J., Liotou, E., Narwaria, M. (2015) No-reference video quality measurement: added value of machine learning. Journal of Electronic Imaging, 24(6).10.1117/1.JEI.24.6.061208
  16. 16. Mohamed, S., Rubino, G. (2002) A Study of Real-Time Packet Video Quality Using Random Neural Networks. IEEE Transactions on Circuits and Systems for Video Technology, 12(12).10.1109/TCSVT.2002.806808
  17. 17. Mustafa, S., Hameed, A. (2019) Perceptual quality assessment of video using machine learning algorithm. Signal, Image and Video Processing, 13, pp. 1495–1502.10.1007/s11760-019-01494-5
  18. 18. Ramirez-Alonso, G., Chacon-Murguia, M.I. (2016) Object detection in video sequences by a temporal modular self-adaptive SOM. Neural Computing & Applications, 27, pp. 411-430.10.1007/s00521-015-1859-2
  19. 19. Sevcik, L., Voznak, M., Frnda, J. (2014) QoE Prediction Model for Multimedia Services in IP Network Applying Queuing Policy. In: 17th International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS) part of SummerSim Multiconference, pp. 593-598.10.1109/SPECTS.2014.6879998
  20. 20. Søgaard, J., Forchhammer, S., Korhonen, J. (2015) Video quality assessment and machine learning: Performance and interpretability. In: 7th International Workshop on Quality of Multimedia Experience (QoMEX).10.1109/QoMEX.2015.7148149
  21. 21. Song, L., Tang, X., Zhang, W., Yang, X., Xia, P. (2013) The SJTU 4K video sequence dataset. In: 5th International Workshop on Quality of Multimedia Experience (QoMEX).10.1109/QoMEX.2013.6603201
  22. 22. Valderrama, D., Gómez, N. (2016) Nonintrusive Method Based on Neural Networks for Video Quality of Experience Assessment. Advances in Multimedia, volume 2016.10.1155/2016/1730814
  23. 23. Yuana, Y., Wang, C. (2019) IPTV video quality assessment model based on neural network. Journal of Visual Communication and Image Representation, 64, 102629.10.1016/j.jvcir.2019.102629
DOI: https://doi.org/10.2478/ttj-2020-0014 | Journal eISSN: 1407-6179 | Journal ISSN: 1407-6160
Language: English
Page range: 181 - 190
Published on: Jun 25, 2020
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2020 Jaroslav Frnda, Marek Durica, Mihail Savrasovs, Philippe Fournier-Viger, Jerry Chun-Wei Lin, published by Transport and Telecommunication Institute
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.