Towards Efficient Multi-Codec Streaming

Reznik, Yuriy A.; Lillevold, Karl O.; Jagannath, Abhijith; Barman, Nabajeet

doi:10.5594/m001963

Cited by 4 publications

(4 citation statements)

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“…It was ensured that the training set does not include any segments from the same scenes in the test set. For a target bitrate of b t (in Mbps), the CBR encoding is achieved by setting the bitrate and vbv-maxrate 18 option of x265 as b t , and enabling strict-cbr flag 18 . Similarly, for a target bitrate of b t (in Mbps) and CRF c t , cVBR encoding is achieved by setting the crf option 18 of x265 as c t , and vbv-maxrate option as b t .…”

Section: A Test Methodologymentioning

confidence: 99%

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JND-Aware Two-Pass Per-Title Encoding Scheme for Adaptive Live Streaming

Menon¹,

Rajendran

Feldmann³

et al. 2024

IEEE Trans. Circuits Syst. Video Technol.

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Adaptive live video streaming applications utilize a predefined collection of bitrate-resolution pairs, known as a bitrate ladder, for simplicity and efficiency, eliminating the need for additional run-time to determine the optimal pairs during the live streaming session. These applications do not incorporate two-pass encoding methods due to increased latency. However, an optimized bitrate ladder could result in lower storage and delivery costs and improved Quality of Experience (QoE). This paper presents a Just Noticeable Difference (JND)-aware constrained Variable Bitrate (cVBR) Two-pass Per-title encoding Scheme (JTPS) designed specifically for live video streaming. JTPS predicts a content-and JND-aware bitrate ladder using low-complexity features based on Discrete Cosine Transform (DCT) energy and optimizes the constant rate factor (CRF) for each representation using random forest-based models. The effectiveness of JTPS is demonstrated using the open source video encoder x265, with an average bitrate reduction of 18.80% and 32.59% for the same PSNR and VMAF, respectively, compared to the standard HTTP Live Streaming (HLS) bitrate ladder using Constant Bitrate (CBR) encoding. The implementation of JTPS also resulted in a 68.96% reduction in storage space and an 18.58% reduction in encoding time for a JND of six VMAF points.

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Section: A Test Methodologymentioning

confidence: 99%

“…They use simple linear regression models to predict bitrateresolution pairs. There are per-title encoding methods developed in the industry: from Bitmovin 6 , Brightcove [18], MUX 7 , and CAMBRIA 8 . However, they are proprietary; hence, information about them is limited.…”

Section: Livementioning

confidence: 99%

JND-Aware Two-Pass Per-Title Encoding Scheme for Adaptive Live Streaming

Menon¹,

Rajendran

Feldmann³

et al. 2024

IEEE Trans. Circuits Syst. Video Technol.

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show abstract

“…They use simple linear regression models to predict bitrate-resolution pairs. There are per-title encoding methods developed in the industry: from Bitmovin 8 , Brightcove [23], MUX 9 , and CAMBRIA 10 . However, they are proprietary; hence, information about them is limited.…”

Section: Methodsmentioning

confidence: 99%

JND-aware Two-pass Per-title Encoding Scheme for Adaptive Live Streaming

Menon¹,

Rajendran²,

Feldmann³

et al. 2023

Preprint

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<p>Adaptive live video streaming applications utilize a predefined collection of bitrate-resolution pairs, known as a bitrate ladder, for simplicity and efficiency, eliminating the need for additional run-time to determine the optimal pairs for each video. These applications do not incorporate two-pass encoding methods due to increased latency. However, an optimized bitrate ladder could result in lower storage and delivery costs and improved Quality of Experience (QoE). This paper presents a Just Noticeable Difference (JND)-aware constrained Variable Bitrate (cVBR) Two-pass Per-title encoding Scheme (JTPS) designed specifically for live video streaming. JTPS predicts a content- and JND-aware bitrate ladder using low-complexity features based on Discrete Cosine Transform (DCT) energy and optimizes the constant rate factor (CRF) for each representation. The effectiveness of JTPS is demonstrated using the x265 open-source video encoder, with an average bitrate reduction of 18.80% and 32.59% for the same PSNR and VMAF, respectively, compared to the standard HTTP Live Streaming (HLS) bitrate ladder using Constant Bitrate (CBR) encoding. The implementation of JTPS also resulted in a 68.96% reduction in storage space with a negligible impact on streaming latency.</p>

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“…Apart from enabling new capabilities by leveraging mixed codec manifest, we are also inspired by the idea proposed in [16]. When we can deliver a mixed codec manifest to the client, the ABR algorithm in the client player can select the best possible quality segment based on the available bandwidth from both adaptation sets.…”

Section: Joint Multi Tagset Deliverymentioning

confidence: 99%

Best practices of mixed-codec adaptive bitrate streaming

Lei,

Zhou,

Chen

et al. 2023

Applications of Digital Image Processing XLVI

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One of the biggest challenges in Meta's video delivery system is device fragmentation. Due to the large user base of Meta's Family of Apps, our supported devices range from single-core Galaxy Y to the latest Galaxy S22, from the first generation of iPad mini to iPhone 14 pro. Moreover, for devices that do not support hardware decoding for more advanced codecs, such as AV1, we have to rely on software decoders which require high compute power and memory bandwidth. It would be ideal if we can deliver high resolution AVC or VP9 encoded ABR lanes along with low resolution AV1 encoded ABR lanes for the same video, so the client device can choose which one to play based on its compute capacity. In addition, when user uploaded videos that are already encoded with advanced codecs, such as VP9 or HEVC, while generating ABR encoding ladders from the uploaded video using AVC, we also want to deliver the original uploaded video as passthrough to maximize the quality. In both use cases, we will need to support streaming ABR manifest with multiple encoded bitstreams from different codecs and play them smoothly on the client side. On top of that, we can also optimize the ABR encoding and delivery system to select ABR lanes encoded with different codecs for different bitrate targets. In this paper, we will describe how we implemented the end-to-end mixed codec manifest support and deployed the solution in production. The proposed approach effectively generalizes encoding selection into a filtering pipeline, evaluating device capacity via a feedback loop, and being adaptive to the bandwidth estimation, viewport size and device capacity.

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Towards Efficient Multi-Codec Streaming

Cited by 4 publications

References 0 publications

JND-Aware Two-Pass Per-Title Encoding Scheme for Adaptive Live Streaming

JND-Aware Two-Pass Per-Title Encoding Scheme for Adaptive Live Streaming

JND-aware Two-pass Per-title Encoding Scheme for Adaptive Live Streaming

Best practices of mixed-codec adaptive bitrate streaming

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