- -

Automatic QoE evaluation for asymmetric encoding of 3D videos for DASH streaming service

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Automatic QoE evaluation for asymmetric encoding of 3D videos for DASH streaming service

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Guzman Castillo, Paola Fernanda es_ES
dc.contributor.author Arce Vila, Pau es_ES
dc.contributor.author Guerri Cebollada, Juan Carlos es_ES
dc.date.accessioned 2021-05-12T03:32:25Z
dc.date.available 2021-05-12T03:32:25Z
dc.date.issued 2020-09-01 es_ES
dc.identifier.issn 1570-8705 es_ES
dc.identifier.uri http://hdl.handle.net/10251/166219
dc.description.abstract [EN] The paper is based on the study of the performance of a Dynamic Adaptive Streaming over HTTP (DASH) system in the context of 3D video streaming, using different scenarios and network conditions, specifically with bandwidth variations. The objective is the development of a framework for the evaluation of QoE in 3D adaptive video streaming scenarios, which allows to analyze the impact on the user's Quality of Experience (QoE) using different bandwidth variation patterns (switching frequency, range and type of variation), among other aspects. A set of subjective tests will be carried out, with the aim of identifying the correlation between the quality of the user experience and the frequency, type, range and temporal location of the bandwidth switching events. The proposed framework allows performance measurements to be carried out in an automated and systematic way for the evaluation of DASH systems in 2D and 3D video streaming service. We have used Puppeteer, the Node.js library developed by Google, which provides a high-level API, to automate actions on Chrome Devtools Protocol, such as starting playback, causing bandwidth changes and saving the results of quality change processes, timestamps, stalls and so on. From this data, a processing is made to allow the reconstruction of the visualized video, as well as the extraction of quality metrics and the users' QoE assessment using the ITU-T P.1203 recommendation. es_ES
dc.description.sponsorship This work has been partially supported by Spanish Ministry of Science, Innovation and Universities and by European Union through grant RTI2018-098085-BC41 (MCUI/AEI/FEDER), SSENCE project (Telefonica Chair UPV), PROMETEO/2019/109 (Generalitat Valenciana) and UPV Line I + D + i "Technologies for distribution and processing of multimedia information and QoE". es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Ad Hoc Networks es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Performance evaluation es_ES
dc.subject 3D video es_ES
dc.subject DASH es_ES
dc.subject Puppeteer es_ES
dc.subject Quality of Experience es_ES
dc.subject Testbed evaluation es_ES
dc.subject ITU-T P.1203 es_ES
dc.subject.classification TEORIA DE LA SEÑAL Y COMUNICACIONES es_ES
dc.subject.classification INGENIERIA TELEMATICA es_ES
dc.title Automatic QoE evaluation for asymmetric encoding of 3D videos for DASH streaming service es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.adhoc.2020.102184 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-098085-B-C41/ES/DYNAMIC ACOUSTIC NETWORKS FOR CHANGING ENVIRONMENTS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//PROMETEO%2F2019%2F109/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.description.bibliographicCitation Guzman Castillo, PF.; Arce Vila, P.; Guerri Cebollada, JC. (2020). Automatic QoE evaluation for asymmetric encoding of 3D videos for DASH streaming service. Ad Hoc Networks. 106:1-15. https://doi.org/10.1016/j.adhoc.2020.102184 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.adhoc.2020.102184 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 15 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 106 es_ES
dc.relation.pasarela S\416413 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
dc.contributor.funder Ministerio de Ciencia, Innovación y Universidades es_ES
dc.contributor.funder Cátedra Telefónica, Universitat Politècnica de València es_ES
dc.description.references Cisco, “Cisco Visual Networking Index : forecast and Trends, 2017–2022 White Paper.” 2019. es_ES
dc.description.references ISO/IEC, “ISO/IEC 23009-1 Information technology — Dynamic adaptive streaming over HTTP (DASH) — Part 1: media presentation description and segment formats Technologies, 2019,” 2019. es_ES
dc.description.references T. Su, A. Javadtalab, A. Yassine, and S. Shirmohammadi, “A DASH-based 3D multi-view video rate control system A DASH-Based 3D Multi-view Video Rate Control System,” 2014. es_ES
dc.description.references Hoßfeld, T., Seufert, M., Sieber, C., Zinner, T., & Tran-Gia, P. (2015). Identifying QoE optimal adaptation of HTTP adaptive streaming based on subjective studies. Computer Networks, 81, 320-332. doi:10.1016/j.comnet.2015.02.015 es_ES
dc.description.references Barman, N., & Martini, M. G. (2019). QoE Modeling for HTTP Adaptive Video Streaming–A Survey and Open Challenges. IEEE Access, 7, 30831-30859. doi:10.1109/access.2019.2901778 es_ES
dc.description.references “Puppeteer.” [Online]. Available: https://github.com/GoogleChrome/puppeteer. [Accessed: 01-Jul-2019]. es_ES
dc.description.references Akar, G. B., Tekalp, A. M., Fehn, C., & Civanlar, M. R. (2007). Transport Methods in 3DTV—A Survey. IEEE Transactions on Circuits and Systems for Video Technology, 17(11), 1622-1630. doi:10.1109/tcsvt.2007.905365 es_ES
dc.description.references Merkle, P., Müller, K., & Wiegand, T. (2010). 3D video: acquisition, coding, and display. IEEE Transactions on Consumer Electronics, 56(2), 946-950. doi:10.1109/tce.2010.5506024 es_ES
dc.description.references Gürler, C. G., Görkemli, B., Saygili, G., & Tekalp, A. M. (2011). Flexible Transport of 3-D Video Over Networks. Proceedings of the IEEE, 99(4), 694-707. doi:10.1109/jproc.2010.2100010 es_ES
dc.description.references Vetro, A., Wiegand, T., & Sullivan, G. J. (2011). Overview of the Stereo and Multiview Video Coding Extensions of the H.264/MPEG-4 AVC Standard. Proceedings of the IEEE, 99(4), 626-642. doi:10.1109/jproc.2010.2098830 es_ES
dc.description.references Hannuksela, M. M., Gabbouj, M., Rusanovskyy, D., Su, W., Chen, L., Li, R., … Li, H. (2013). Multiview-Video-Plus-Depth Coding Based on the Advanced Video Coding Standard. IEEE Transactions on Image Processing, 22(9), 3449-3458. doi:10.1109/tip.2013.2269274 es_ES
dc.description.references Chikkerur, S., Sundaram, V., Reisslein, M., & Karam, L. J. (2011). Objective Video Quality Assessment Methods: A Classification, Review, and Performance Comparison. IEEE Transactions on Broadcasting, 57(2), 165-182. doi:10.1109/tbc.2011.2104671 es_ES
dc.description.references T. Wiegand and G.J. Sullivan, “The H.264/AVC Video Coding Standard,” no. August 1999, pp. 148–153, 2007. es_ES
dc.description.references Sullivan, G. J., Ohm, J.-R., Han, W.-J., & Wiegand, T. (2012). Overview of the High Efficiency Video Coding (HEVC) Standard. IEEE Transactions on Circuits and Systems for Video Technology, 22(12), 1649-1668. doi:10.1109/tcsvt.2012.2221191 es_ES
dc.description.references Tech, G., Chen, Y., Muller, K., Ohm, J.-R., Vetro, A., & Wang, Y.-K. (2016). Overview of the Multiview and 3D Extensions of High Efficiency Video Coding. IEEE Transactions on Circuits and Systems for Video Technology, 26(1), 35-49. doi:10.1109/tcsvt.2015.2477935 es_ES
dc.description.references Wang, J., Wang, S., & Wang, Z. (2017). Asymmetrically Compressed Stereoscopic 3D Videos: Quality Assessment and Rate-Distortion Performance Evaluation. IEEE Transactions on Image Processing, 26(3), 1330-1343. doi:10.1109/tip.2017.2651387 es_ES
dc.description.references Battisti, F., Carli, M., Le Callet, P., & Paudyal, P. (2018). Toward the Assessment of Quality of Experience for Asymmetric Encoding in Immersive Media. IEEE Transactions on Broadcasting, 64(2), 392-406. doi:10.1109/tbc.2018.2828607 es_ES
dc.description.references ITU-T, “ITU-T.P910. Subjective video quality assessment methods for multimedia applications,” 2008. es_ES
dc.description.references H.K. Yarnagula, S. Luhadia, S. Datta, and V. Tamarapalli, “Quality of Experience Assessment of Rate Adaptation Algorithms in DASH : an Experimental Study,” pp. 1–8, 2016. es_ES
dc.description.references Bentaleb, A., Taani, B., Begen, A. C., Timmerer, C., & Zimmermann, R. (2019). A Survey on Bitrate Adaptation Schemes for Streaming Media Over HTTP. IEEE Communications Surveys & Tutorials, 21(1), 562-585. doi:10.1109/comst.2018.2862938 es_ES
dc.description.references C. Timmerer, M. Maiero, and B. Rainer, “Which Adaptation Logic ? An Objective and Subjective Performance Evaluation of HTTP-based Adaptive Media Streaming Systems.” es_ES
dc.description.references Seufert, M., Egger, S., Slanina, M., Zinner, T., Hobfeld, T., & Tran-Gia, P. (2015). A Survey on Quality of Experience of HTTP Adaptive Streaming. IEEE Communications Surveys & Tutorials, 17(1), 469-492. doi:10.1109/comst.2014.2360940 es_ES
dc.description.references Chen, Y., Wu, K., & Zhang, Q. (2015). From QoS to QoE: A Tutorial on Video Quality Assessment. IEEE Communications Surveys & Tutorials, 17(2), 1126-1165. doi:10.1109/comst.2014.2363139 es_ES
dc.description.references Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004). Image Quality Assessment: From Error Visibility to Structural Similarity. IEEE Transactions on Image Processing, 13(4), 600-612. doi:10.1109/tip.2003.819861 es_ES
dc.description.references Z.L. Li and A. Aaron, “Toward A Practical Perceptual Video Quality Metric,” Netflix TechBlog. es_ES
dc.description.references ITU-T, “ITU-T. P915. Subjective assessment methods for 3D video quality,” 2016. es_ES
dc.description.references ITU Telecommunication Standardization Sector, “ITU-T Rec P 1203 Models and tools for quality assessment of streamed media,” 2017. es_ES
dc.description.references R. I.-T. J.247, “Objective perceptual multimedia video quality measurement in the presence of a full reference.,” Recomm. ITU-T J.247, 2008. es_ES
dc.description.references Shaka Player Demo. [Online]. Available:https://shaka-player-demo.appspot.com. [Accessed: 01-Jun-2019]. es_ES
dc.description.references Fiedler, M., Hossfeld, T., & Tran-Gia, P. (2010). A generic quantitative relationship between quality of experience and quality of service. IEEE Network, 24(2), 36-41. doi:10.1109/mnet.2010.5430142 es_ES
dc.description.references Big Buck Bunny. [Online]. Available: https://peach.blender.org. [Accessed: 01-May-2019]. es_ES
dc.description.references S. Lederer, C. Müller, and C. Timmerer, “Dynamic Adaptive Streaming over HTTP Dataset,” pp. 89–94, 2012. es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem