Performance Evaluation of AVC and HEVC for E-Learning: Optimizing Quality and Reducing Bandwidth Usage

Yıl 2023, , 581 - 591, 31.12.2023

Oğuz Kırat , Tarık Yerlikaya , Emir Öztürk

https://doi.org/10.24012/dumf.1335369

Öz

E-learning has experienced a surge in popularity, particularly during and after the COVID-19 pandemic. Online learning has proven to be a vital tool for students and educators to continue academic activities while adhering to social distancing guidelines and during the times of natural disasters that disrupt the conventional learning environments. It also offers accessibility to disabled students and those facing challenges to reach to the traditional learning. But due to increased demand, it is crucial to optimize cost of transmission while minimizing bandwidth usage while maintaining high-quality video transmission. To optimize cost and reduce network load, it is essential to minimize bandwidth usage while maintaining high-quality video. In response to this need, we present a novel dataset consisting of four e-learning scenarios. We encoded this dataset using various resolutions, bit rates, and encoder presets, and evaluated it in terms of encoding time, and quality using full-reference objective quality metrics such as MSE, PSNR, and SSIM. After experimenting with more than 1400 videos and configurations of encoders and codecs, we found out that it is possible to transmit videos in exceptional quality at bitrates as low as 5 Mbps for e-learning scenarios. We also present detailed results about correlation between file size, quality and encoding time to make optimizations for specific bandwidth, target quality or encoding speed.

Anahtar Kelimeler

AVC, Compression, E-Learning, HEVC, Video Encoding, Video Quality Assessment

Kaynakça

• [1] T. Barnett, S. Jain, U. Andra, “Cisco visual networking index (vni) complete forecast update, 2017–2022,” Americas/EMEAR Cisco Knowledge Network (CKN) Presentation, 2018, Accessed: Feb. 04, 2023. [Online]. Available: https://get.drivenets.com/hubfs/1211_BUSINESS_SERVICES_CKN_P DF.pdf
• [2] “The WebM Project | Welcome to the WebM Project.” https://www.webmproject.org/ (accessed Feb. 04, 2023).
• [3] D. Mukherjee, J. Han, J. Bankoski, R. Bultje, A. Grange,J Koleszar, P. Wilkins, Y. Xu, “A technical overview of VP9 - The latest open-source video codec,” SMPTE Annual Technical Conference and Exhibition 2013, SMPTE 2013, pp. 376–392, 2013, doi: 10.5594/M001518.
• [4] Standard ISO/IEC 23090-3, Versatile Video Coding. 2020.
• [5] O. Rippel, A. G. Anderson, K. Tatwawadi, S. Nair, C. Lytle, L. Bourdev, “ELF-VC: Efficient Learned Flexible-Rate Video Coding,” Proceedings of the IEEE International Conference on Computer Vision, pp. 14459–14468, Apr. 2021, doi: 10.48550/arxiv.2104.14335.
• [6] Information Technology, “General Video Coding—Part 2: Low Complexity Enhancement Video Coding,” Standard ISO/IEC 230942:2021. Nov. 2021.
• [7] Recommendation ITU-T H.264 and ISO/IEC 14496-10 (AVC), “Advanced Video Coding for Generic Audio-Visual Services,” ITU-T and ISO/IEC JTC 1. May 2003.
• [8] Recommendation ITU-T H.265 and ISO/IEC 23008-2 (HEVC), “High Efficiency Video Coding,” ITU-T and ISO/IEC JTC 1. Apr. 2013.
• [9] G. J. Sullivan, J. R. Ohm, W. J. Han, T. Wiegand, “Overview of the high efficiency video coding (HEVC) standard,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 22, no. 12, pp. 1649– 1668, 2012, doi: 10.1109/TCSVT.2012.2221191.
• [10] L. Guo, J. de Cock, A. Aaron, “Compression Performance Comparison of x264, x265, libvpx and aomenc for On-Demand Adaptive Streaming Applications,” 2018 Picture Coding Symposium, PCS 2018 - Proceedings, pp. 26–30, Sep. 2018, doi: 10.1109/PCS.2018.8456302.
• [11] N. Barman, M. G. Martini, “H.264/MPEG-AVC, H.265/MPEG-HEVC and VP9 codec comparison for live gaming video streaming,” 2017 9th International Conference on Quality of Multimedia Experience, QoMEX 2017, Jun. 2017, doi: 10.1109/QOMEX.2017.7965686.
• [12] M. Cali, N. Ozbek, “Comparative analysis of adaptive streaming with CBR and VBR encoded scalable videos,” SIU 2021 - 29th IEEE Conference on Signal Processing and Communications Applications, Proceedings, Jun. 2021, doi: 10.1109/SIU53274.2021.9477909.
• [13] T. Kilic, A. M. Gulbahce, M. Yildiz, “Performance Evaluation of Next Generation Video Compression Approaches Using Objective Quality Measurement Methods,” 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings, Oct. 2020, doi: 10.1109/SIU49456.2020.9302130.
• [14] T. Nguyen, A. Wieckowski, B. Bross, D. Marpe, “Objective Evaluation of the Practical Video Encoders VVenC, x265, and aomenc AV1,” 2021 Picture Coding Symposium, PCS 2021 - Proceedings, Jun. 2021, doi: 10.1109/PCS50896.2021.9477482.
• [15] Z. Shang, Y. Chen, Y.Wu, H. Wei, S. Sethuraman “Subjective and Objective Video Quality Assessment of High Dynamic Range Sports Content”, IEEE/CVF Winter Conference on Applicaions of Computer Vision (WACV), 2023, pp. 556-564
• [16] A. Telili, S. A. Fezza, W. Hamidouche, and H. F. Z. B. Meftah, ‘2BiVQA: Double Bi-LSTM Based Video Quality Assessment of UGC Videos’, ACM Trans. Multimedia Comput. Commun. Appl., Nov. 2023.
• [17] Z. Wang, A. C. Bovik, H. R. Sheikh, E. P. Simoncelli, “Image quality assessment: From error visibility to structural similarity,” IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 600–612, Apr. 2004, doi: 10.1109/TIP.2003.819861.
• [18] J. Kufa, T. Kratochvil, “Comparison of H.265 and VP9 coding efficiency for full HDTV and ultra HDTV applications,” Proceedings of 25th International Conference Radioelektronika, RADIOELEKTRONIKA 2015, pp. 168–171, Jun. 2015, doi: 10.1109/RADIOELEK.2015.7128999.