Encoding Time and Energy Model for SVT-AV1 based on Video Complexity

TL;DR

This paper presents an empirical model for predicting encoding time and energy consumption of SVT-AV1 video encoder based on video complexity and encoder settings, aiding energy-efficient video compression.

Contribution

The authors develop a novel empirical model that accurately predicts encoding time and energy for SVT-AV1 considering video content and encoder parameters.

Findings

Prediction error of 19.6% for encoding time

Prediction error of 20.9% for encoding energy

Model helps optimize energy consumption in video encoding

Abstract

The share of online video traffic in global carbon dioxide emissions is growing steadily. To comply with the demand for video media, dedicated compression techniques are continuously optimized, but at the expense of increasingly higher computational demands and thus rising energy consumption at the video encoder side. In order to find the best trade-off between compression and energy consumption, modeling encoding energy for a wide range of encoding parameters is crucial. We propose an encoding time and energy model for SVT-AV1 based on empirical relations between the encoding time and video parameters as well as encoder configurations. Furthermore, we model the influence of video content by established content descriptors such as spatial and temporal information. We then use the predicted encoding time to estimate the required energy demand and achieve a prediction error of 19.6 % for encoding time and 20.9 % for encoding energy.