IEEE Standard for the Deep Learning-Based Assessment of Visual Experience Based on Human Factors

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引用次数: 2

Abstract

Measuring quality of experience (QoE) aims to explore the factors that contribute to a user’s perceptual experience including human, system, and context factors. Since QoE stems from human interaction with various devices, the estimation should be started by investigating the mechanism of human visual perception. Therefore, measuring QoE is still a challenging task. In this standard, QoE assessment is categorized into two subcategories which are perceptual quality and virtual reality (VR) cybersickness. In addition, deep learning models considering human factors for various QoE assessments are covered, along with a reliable subjective test methodology and a database construction procedure.
基于人为因素的基于深度学习的视觉体验评估IEEE标准
体验质量测量(QoE)旨在探索影响用户感知体验的因素,包括人、系统和环境因素。由于QoE源于人类与各种设备的相互作用,因此应该从研究人类视觉感知的机制开始估计。因此,衡量QoE仍然是一项具有挑战性的任务。在该标准中,QoE评估分为感知质量和虚拟现实(VR)晕动症两个子类。此外,还涵盖了用于各种QoE评估的考虑人为因素的深度学习模型,以及可靠的主观测试方法和数据库构建过程。
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