Conference contribution

A Bitstream Feature Based Model for Video Decoding Energy Estimation

Publication Details
Author(s): Herglotz C, Wen Y, Dai B, Kränzler M, Kaup A
Publication year: 2016

Event details
Event: Picture Coding Symposium
Event location: Nürnberg
Start date of the event: 04/12/2016
End date of the event: 07/12/2016
Language: English


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.

How to cite
APA: Herglotz, C., Wen, Y., Dai, B., Kränzler, M., & Kaup, A. (2016). A Bitstream Feature Based Model for Video Decoding Energy Estimation. Nürnberg, DE.

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

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