A Bitstream Feature Based Model for Video Decoding Energy Estimation
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.
arXiv comment5 pages, 2 figures, 2016 Picture Coding Symposium (PCS)
References in corpus (2)
Cited by in corpus (5)
- Decoding-Energy-Rate-Distortion Optimization for Video Coding
- Video Decoding Energy Estimation Using Processor Events
- Decoding Energy Modeling For Versatile Video Coding
- Extending Video Decoding Energy Models for 360° and HDR Video Formats in HEVC
- A Bit Stream Feature-Based Energy Estimator for HEVC Software Encoding