A bitstream feature based model for video decoding energy estimation

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 V...

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Bibliographic Details
Published in2016 Picture Coding Symposium (PCS) pp. 1 - 5
Main Authors Herglotz, Christian, Yongjun Wen, Bowen Dai, Kranzler, Matthias, Kaup, Andre
Format Conference Proceeding
LanguageEnglish
Published IEEE 2016
Subjects
Adaptation models
Codecs
Decoding
Encoding
Energy consumption
Estimation
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Summary: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.
ISSN:2472-7822
DOI:10.1109/PCS.2016.7906400