A Bitstream Feature Based Model for Video Decoding Energy Estimation

Herglotz C, Wen Y, Dai B, Kränzler M, Kaup A (2016)


Publication Language: English

Publication Type: Conference contribution

Publication year: 2016

Event location: Nürnberg DE

ISBN: 978-1-5090-5966-9

URI: https://doi.org/10.48550/arXiv.2204.10151

DOI: 10.1109/PCS.2016.7906400

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.

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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. 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.

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