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Towards Optimal Multirate Encoding for HTTP Adaptive Streaming

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HTTP Adaptive Streaming (HAS) enables high-quality streaming of video content. In HAS, videos are divided into short intervals called segments, and each segment is encoded at various quality/bitrates to adapt to the available bandwidth. Multiple encodings of the same content impose high costs for video content providers. To reduce the time-complexity of encoding multiple representations, state-of-the-art methods typically encode the highest quality representation first and reuse the information gathered during its encoding to accelerate the encoding of the remaining representations. As encoding the highest quality representation requires the highest time-complexity compared to the lower quality representations, it would be a bottleneck in parallel encoding scenarios and the overall time-complexity will be limited to the time-complexity of the highest quality representation. In this paper and to address this problem, we consider all representations from the highest to the lowest quality representation as a potential, single reference to accelerate the encoding of the other, dependent representations. We formulate a set of encoding modes and assess their performance in terms of BD-Rate and time-complexity, using both VMAF and PSNR as objective metrics. Experimental results show that encoding a middle quality representation as a reference, can significantly reduce the maximum en-coding complexity and hence it is an efficient way of encoding multiple representations in parallel. Based on this fact, a fast multirate encoding method is proposed which utilizes depth and prediction mode of a middle quality representation to accelerate the encoding of the dependent representations.

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Towards Optimal Multirate Encoding for HTTP Adaptive Streaming

  1. 1. All rights reserved. ©2020 All rights reserved. ©2020 Towards Optimal Multirate Encoding for HTTP Adaptive Streaming Hadi Amirpour, Ekrem Çetinkaya, Christian Timmerer, and Mohammad Ghanbari June 2021 1 27th International Conference on Multimedia Modeling
  2. 2. All rights reserved. ©2020 ● Introduction ● HTTP adaptive streaming ● Fast multirate encoding ● Experimental results ● Conclusion All rights reserved. ©2020 2
  3. 3. Introduction In HAS: ● a video source is split into segments ● each segment is encoded at multiple bitrates ● compatibility with network condition is increased 3
  4. 4. 4 Introduction HTTP server Network Client
  5. 5. Introduction ● HEVC improve the encoding efficiency compared to AVC ● This improvement is achieved at a cost of significant increased time-complexity ● This is even more crucial for DASH-based content providers as it requires to encode multiple representations of the same video content. 5
  6. 6. Fast multirate encoding Double-bound [1] [1] H. Amirpour, E. Çetinkaya, C. Timmerer and M. Ghanbari, "Fast Multi-rate Encoding for Adaptive HTTP Streaming," In Proceedings of the 2020 Data Compression Conference (DCC), Snowbird, UT, USA, 2020, pp. 358-358. 6 reference dependent reference dependent
  7. 7. Fast multirate encoding 7 reference dependent
  8. 8. Fast multirate encoding 8
  9. 9. Fast multirate encoding 9
  10. 10. Fast multirate encoding 10
  11. 11. Thank you 11 www.athena.itec.aau.at

HTTP Adaptive Streaming (HAS) enables high-quality streaming of video content. In HAS, videos are divided into short intervals called segments, and each segment is encoded at various quality/bitrates to adapt to the available bandwidth. Multiple encodings of the same content impose high costs for video content providers. To reduce the time-complexity of encoding multiple representations, state-of-the-art methods typically encode the highest quality representation first and reuse the information gathered during its encoding to accelerate the encoding of the remaining representations. As encoding the highest quality representation requires the highest time-complexity compared to the lower quality representations, it would be a bottleneck in parallel encoding scenarios and the overall time-complexity will be limited to the time-complexity of the highest quality representation. In this paper and to address this problem, we consider all representations from the highest to the lowest quality representation as a potential, single reference to accelerate the encoding of the other, dependent representations. We formulate a set of encoding modes and assess their performance in terms of BD-Rate and time-complexity, using both VMAF and PSNR as objective metrics. Experimental results show that encoding a middle quality representation as a reference, can significantly reduce the maximum en-coding complexity and hence it is an efficient way of encoding multiple representations in parallel. Based on this fact, a fast multirate encoding method is proposed which utilizes depth and prediction mode of a middle quality representation to accelerate the encoding of the dependent representations.

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