Tag Archive for: video streaming

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IEEE ICIP’25: Machine Learning-Based Decoding Energy Modeling for VVC Streaming

Machine Learning-Based Decoding Energy Modeling for VVC Streaming

2025 IEEE International Conference on Image Processing (ICIP)

14-17 September, Anchorage, Alaska, USA

https://2025.ieeeicip.org/

Reza Farahani (AAU Klagenfurt, Austria), Vignesh V Menon (Fraunhofer HHI, Germany), and Christian Timmerer (AAU Klagenfurt, Austria)

Abstract: Efficient video streaming requires jointly optimizing encoding parameters (bitrate, resolution, compression efficiency) and decoding constraints (computational load, energy consumption) to balance quality and power efficiency, particularly for resource-constrained devices. However, hardware heterogeneity, including differences in CPU/GPU architectures, thermal management, and dynamic power scaling, makes absolute energy models unreliable, particularly for predicting decoding consumption. This paper introduces the Relative Decoding Energy Index (RDEI), a metric that normalizes decoding energy consumption against a baseline encoding configuration, eliminating device-specific dependencies to enable cross-platform comparability and guide energy-efficient streaming adaptations. We use a dataset of 1000 video sequences to extract complexity features capturing spatial and temporal variations, employ Versatile Video Coding (VVC) open-source toolchain using VVenC/VVdeC with various resolutions, framerate, encoding preset and quantization parameter (QP) sets, and model RDEI using Random Forest (RF), XGBoost, Linear Regression (LR), and Shallow Neural Networks (NN) for decoding energy prediction. Experimental results demonstrate that RDEI-based predictions provide accurate decoding energy estimates across different hardware, ensuring cross-device comparability in VVC streaming.

Keywords: Video Streaming; Energy Prediction; Versatile Video Coding (VVC); Video Complexity Analysis.

 

 

 

 

 

Hadi
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Paper accepted – On The Impact of Viewing Distance on Perceived Video Quality

Title: On The Impact of Viewing Distance on Perceived Video Quality

Link: IEEE Visual Communications and Image Processing (VCIP 2021) 5-8 December 2021, Munich, Germany

Authors: Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), Raimund Schatz (AIT Austrian Institute of Technology, Austria), Mohammad Ghanbari (School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK), and Christian Timmerer (Alpen-Adria-Universität Klagenfurt)

Abstract: Due to the growing importance of optimizing quality and efficiency of video streaming delivery, accurate assessment of user perceived video quality becomes increasingly relevant. However, due to the wide range of viewing distances encountered in real-world viewing settings, actually perceived video quality can vary significantly in everyday viewing situations. In this paper, we investigate and quantify the influence of viewing distance on perceived video quality.  A subjective experiment was conducted with full HD sequences at three different stationary viewing distances, with each video sequence being encoded at three different quality levels. Our study results confirm that the viewing distance has a significant influence on the quality assessment. In particular, they show that an increased viewing distance generally leads to an increased perceived video quality, especially at low media encoding quality levels. In this context, we also provide an estimation of potential bitrate savings that knowledge of actual viewing distance would enable in practice.
Since current objective video quality metrics do not systematically take into account viewing distance, we also analyze and quantify the influence of viewing distance on the correlation between objective and subjective metrics. Our results confirm the need for distance-aware objective metrics when accurate prediction of perceived video quality in real-world environments is required.

Tag Archive for: video streaming