Quality Of Multimedia Experience Research Articles

Dataset Column: Overview, Scope and Call for Contributions

The Dataset Column (https://records.sigmm.org/open-science/datasets/) of ACM SIGMM Records provides timely updates on the developments in the domain of publicly available multimedia datasets as enabling tools for reproducible research in numerous related areas. It is intended as a platform for further dissemination of useful information on multimedia datasets and studies of datasets covering various domains, published in peer-reviewed journals, conference proceedings, dissertations, or as results of applied research in industry. The aim of the Dataset Column is therefore not to substitute already established platforms for disseminating multimedia datasets, e.g., Qualinet Databases (https://qualinet.github.io/databases/) [2], Multimedia Evaluation Benchmark (https://multimediaeval.github.io/), but promote such platforms and particularly interesting datasets and benchmarking challenges associated with them. Multimedia Evaluation Benchmark, MediaEval 2021, registration is now open (https://multimediaeval.github.io). This year's MediaEval features a wide variety of tasks and datasets tackling a large number of domains, including video privacy, social media data analysis and understanding, news items analysis, medicine and wellbeing, affective and subjective content analysis, and game and sports associated media. The Column will also continue reporting of contributions presented within Dataset Tracks at relevant conferences, e.g., ACM Multimedia (MM), ACM Multimedia Systems (MMSys), International Conference on Quality of Multimedia Experience (QoMEX), International Conference on Multimedia Modeling (MMM).

Towards interactive QoE assessment of robotic telepresence

This article provides insights towards the Telepresence Robot (TPR) QoE research agenda and summarizes the findings of a TPR QoE study as provided in H. Z. Jahromi, I. Bartolec, E. Gamboa, A. Hines and R. Schatz, "You Drive Me Crazy! Interactive QoE Assessment for Telepresence Robot Control," 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX), Athlone, Ireland, 2020, pp. 1-6, doi: 10.1109/QoMEX48832.2020.9123117.

Slack-Time Closed-Loop Control System for Multimedia Mobile Devices

Nowadays there is a pervasive utilization of consumer-electronics mobile devices with powerful multimedia capabilities. The suitable management of their power consumption is critical in order to meet the user expectations in terms of battery lifetime. But the reduction of the dynamic-power component of the consumption may sometimes impair the quality of multimedia experience (QoE), which is not always acceptable. This paper proposes a closed-loop control system that can monitor the QoE in the form of the slack time of video decoding tasks and act on the CPU frequency to regulate it. Some results are presented in comparison with dynamic Linux governors which show a suitable behavior in guaranteeing enough QoE, even with power savings of almost 5% and low overhead. This enables its use as an assistant part of dynamic-power savers.

Quality of multimedia experience

Reference EPFL-ARTICLE-177930doi:10.1186/1687-5281-2012-5View record in Web of Science Record created on 2012-06-08, modified on 2017-05-10