In live streaming applications, a fixed set of bitrate-resolution pairs (known as bitrate ladder) is generally used to avoid additional pre-processing run-time to analyze the complexity of every video content and determine the optimized bitrate ladder. Furthermore, live encoders use the fastest available preset for encoding to ensure the minimum possible latency in streaming. For live encoders, it is expected that the encoding speed is equal to the video framerate. An optimized encoding preset may result in (i) increased Quality of Experience (QoE) and (ii) improved CPU utilization while encoding. In this light, this paper introduces a Content-Adaptive encoder Preset prediction Scheme (CAPS) for adaptive live video streaming applications. In this scheme, the encoder preset is determined using Discrete Cosine Transform (DCT)-energy-based low-complexity spatial and temporal features for every video segment, the number of CPU threads allocated for each encoding instance, and the target encoding speed. Experimental results show that CAPS yields an overall quality improvement of 0.83 dB PSNR and 3.81 VMAF with the same bitrate, compared to the fastest preset encoding of the HTTP Live Streaming (HLS) bitrate ladder using x265 HEVC open-source encoder. This is achieved by maintaining the desired encoding speed and reducing CPU idle time.
翻译:在实时流流应用中,通常使用一套固定的比特率分辨率配对(称为比特率梯子)来避免额外的预处理运行时间,以分析每个视频内容的复杂性,并确定最佳比特率梯子。此外,实时编码器使用最快的编码预设,以确保流流中最小可能的延迟性。对于实时编码器,预计编码速度等于视频框架速率。优化编码预设可能导致:(一) 提高经验质量(QoE)和(二)在编码时提高CPU的利用率。在此光线下,本文为适应性实时视频流应用引入了内容-Adaptial 编码器预设预测计划(CAPS) 。在此计划中,编码预设的编码器使用Discrete Cosine 变换(DCT)-基于能源的低兼容性空间和时间特性,为每个编码实例分配的CPU(QoEEE) 和目标编码速度。实验结果显示,CAPS产生一个总体质量改进的x-Adaptarial Streal 的比额,使用S-rentral PSLA.81和STRegreglex 之前的SB 和SBRVTHR) 。