A Bitstream Feature Based Model for Video Decoding Energy Estimation

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Details zur Publikation

Autor(en): Herglotz C, Wen Y, Dai B, Kränzler M, Kaup A
Jahr der Veröffentlichung: 2016
ISBN: 978-1-5090-5966-9
ISSN: 2472-7822
Sprache: Englisch


Abstract

In this paper we show that a small amount of bit stream features can be used to accurately estimate the energy consumption of state-of-the-art software and hardware accelerated decoder implementations for four different video codecs. By testing the estimation performance on HEVC, H.264, H.263, and VP9 we show that the proposed model can be used for any hybrid video codec. We test our approach on a high amount of different test sequences to prove the general validity. We show that less than 20 features are sufficient to obtain mean estimation errors that are smaller than 8%. Finally, an example will show the performance trade-offs in terms of rate, distortion, and decoding energy for all tested codecs.


FAU-Autoren / FAU-Herausgeber

Herglotz, Christian Dr.-Ing.
Lehrstuhl für Multimediakommunikation und Signalverarbeitung
Kaup, André Prof. Dr.-Ing.
Lehrstuhl für Multimediakommunikation und Signalverarbeitung


Zitierweisen

APA:
Herglotz, C., Wen, Y., Dai, B., Kränzler, M., & Kaup, A. (2016). A Bitstream Feature Based Model for Video Decoding Energy Estimation. In Proceedings of the Picture Coding Symposium (PCS). Nürnberg, DE.

MLA:
Herglotz, Christian, et al. "A Bitstream Feature Based Model for Video Decoding Energy Estimation." Proceedings of the Picture Coding Symposium (PCS), Nürnberg 2016.

BibTeX: 

Zuletzt aktualisiert 2019-18-04 um 23:10