@misc{RamasubbuKaupHerglotz, author = {Ramasubbu, Geetha and Kaup, Andr{\´e} and Herglotz, Christian}, title = {Modeling the Energy Consumption of the HEVC Software Encoding Process using Processor events}, series = {IEEE 26th International Workshop on Multimedia Signal Processing (MMSP)}, journal = {IEEE 26th International Workshop on Multimedia Signal Processing (MMSP)}, publisher = {IEEE}, isbn = {979-8-3503-8725-4}, issn = {2473-3628}, doi = {10.1109/MMSP61759.2024.10743858}, abstract = {Developing energy-efficient video encoding algorithms is highly important due to the high processing complexities and, consequently, the high energy demand of the encoding process. To accomplish this, the energy consumption of the video encoders must be studied, which is only possible with a complex and dedicated energy measurement setup. This emphasizes the need for simple energy estimation models, which estimate the energy required for the encoding. Our paper investigates the possibility of estimating the energy demand of a HEVC software CPU-encoding process using processor events. First, we perform energy measurements and obtain processor events using dedicated profiling software. Then, by using the measured energy demand of the encoding process and profiling data, we build an encoding energy estimation model that uses the processor events of the ultrafast encoding preset to obtain the energy estimate for complex encoding presets with a mean absolute percentage error of 5.36\% when averaged over all the presets. Additionally, we present an energy model that offers the possibility of obtaining energy distribution among various encoding sub-processes. energy models from literature. By using a unified evaluation framework we show how accurately the required decoding energy for different decoding systems can be approximated. We give thorough explanations on the model parameters and explain how the model variables are derived. To show the modeling capabilities in general, we test the estimation performance for different decoding software and hardware solutions, where we find that the proposed model outperforms the models from literature by reaching frame-wise mean estimation errors of less than 7\% for software and less than 15\% for hardware based systems.}, language = {en} } @misc{RamasubbuKaupHerglotz, author = {Ramasubbu, Geetha and Kaup, Andr{\´e} and Herglotz, Christian}, title = {Towards Video Codec Performance Evaluation: A Rate-Energy-Distortion Perspective}, series = {16th International Conference on Quality of Multimedia Experience (QoMEX)}, journal = {16th International Conference on Quality of Multimedia Experience (QoMEX)}, issn = {2472-7814}, doi = {10.1109/QoMEX61742.2024.10598269}, pages = {96 -- 99}, abstract = {The Bj{\o}ntegaard Delta rate (BD-rate) objectively assesses the coding efficiency of video codecs using the rate-distortion (R-D) performance but overlooks encoding energy, which is crucial in practical applications, especially for those on handheld devices. Although R-D analysis can be extended to incorporate encoding energy as energy-distortion (E-D), it fails to integrate all three parameters seamlessly. This work proposes a novel approach to address this limitation by introducing a 3D representation of rate, encoding energy, and distortion through surface fitting. In addition, we evaluate various surface fitting techniques based on their accuracy and investigate the proposed 3D representation and its projections. The overlapping areas in projections help in encoder selection and recommend avoiding the slow presets of the older encoders (x264, x265), as the recent encoders (x265, VVenC) offer higher quality for the same bitrate-energy performance and provide a lower rate for the same energy-distortion performance.}, language = {en} }