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

Fuente: arXiv
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Main Authors: Eichermüller, Lena, Chaudhari, Gaurang, Katsavounidis, Ioannis, Lei, Zhijun, Tmar, Hassene, Herglotz, Christian, Kaup, André
Format: Preprint
Published: 2024
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author Eichermüller, Lena
Chaudhari, Gaurang
Katsavounidis, Ioannis
Lei, Zhijun
Tmar, Hassene
Herglotz, Christian
Kaup, André
author_facet Eichermüller, Lena
Chaudhari, Gaurang
Katsavounidis, Ioannis
Lei, Zhijun
Tmar, Hassene
Herglotz, Christian
Kaup, André
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2401_16067
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Encoding Time and Energy Model for SVT-AV1 based on Video Complexity
Eichermüller, Lena
Chaudhari, Gaurang
Katsavounidis, Ioannis
Lei, Zhijun
Tmar, Hassene
Herglotz, Christian
Kaup, André
Image and Video Processing
Multimedia
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.
title Encoding Time and Energy Model for SVT-AV1 based on Video Complexity
topic Image and Video Processing
Multimedia
url https://arxiv.org/abs/2401.16067