Human-centric Quality Management of Immersive Multimedia Applications

S. V. Damme, M. T. Vega, F. Turck
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引用次数: 6

Abstract

Augmented Reality (AR) and Virtual Reality (VR) multimodal systems are the latest trend within the field of multimedia. As they emulate the senses by means of omnidirectional visuals, 360° sound, motion tracking and touch simulation, they are able to create a strong feeling of presence and interaction with the virtual environment. These experiences can be applied for virtual training (Industry 4.0), tele-surgery (healthcare) or remote learning (education). However, given the strong time and task sensitiveness of these applications, it is of great importance to sustain the end-user quality, i.e. the Quality-of-Experience (QoE), at all times. Lack of synchronization and quality degradation need to be reduced to a minimum to avoid feelings of cybersickness or loss of immersiveness and concentration. This means that there is a need to shift the quality management from system-centered performance metrics towards a more human, QoE-centered approach. However, this requires for novel techniques in the three areas of the QoE-management loop (monitoring, modelling and control). This position paper identifies open areas of research to fully enable human-centric driven management of immersive multimedia. To this extent, four main dimensions are put forward: (1) Task and well-being driven subjective assessment; (2) Real-time QoE modelling; (3) Accurate viewport prediction; (4) Machine Learning (ML)-based quality optimization and content recreation. This paper discusses the state-of-the-art, and provides with possible solutions to tackle the open challenges.
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沉浸式多媒体应用以人为本的质量管理
增强现实(AR)和虚拟现实(VR)多模态系统是多媒体领域的最新发展趋势。由于它们通过全方位的视觉、360°的声音、运动跟踪和触摸模拟来模拟感官,它们能够创造出一种强烈的存在感和与虚拟环境的互动。这些经验可以应用于虚拟培训(工业4.0)、远程手术(医疗保健)或远程学习(教育)。然而,由于这些应用程序具有很强的时间和任务敏感性,因此始终保持最终用户质量(即体验质量(QoE))非常重要。缺乏同步和质量下降需要减少到最低限度,以避免晕机或失去沉浸感和注意力。这意味着需要将质量管理从以系统为中心的性能度量标准转向更人性化的、以qos为中心的方法。然而,这需要qoe管理循环的三个领域(监测、建模和控制)中的新技术。本立场文件确定了开放的研究领域,以充分实现以人为中心的沉浸式多媒体驱动管理。在此基础上,提出了四个主要维度:(1)任务和幸福感驱动的主观评价;(2)实时QoE建模;(3)准确的视口预测;(4)基于机器学习的质量优化和内容再创造。本文讨论了最新的技术,并提供了可能的解决方案,以应对开放的挑战。
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