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IEEE Std 3333.1.3-2022

contributor authorIEEE - The Institute of Electrical and Electronics Engineers, Inc.
date accessioned2022-07-04T20:40:25Z
date available2022-07-04T20:40:25Z
date copyright27 May 2022
date issued2022
identifier other9781357.pdf
identifier urihttp://yse.yabesh.ir/std;query=autho162s6596FCDCAC4261590-%20Naval%20/handle/yse/312743
description abstractMeasuring 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.
languageEnglish
titleIEEE Standard for the Deep Learning-Based Assessment of Visual Experience Based on Human Factorsen
titleIEEE Std 3333.1.3-2022num
typeStandard
page51
treeIEEE - The Institute of Electrical and Electronics Engineers, Inc.:;2022
contenttypeFulltext
subject keywordsHVS
subject keywordssubjective assessment
subject keywordsaugmented reality
subject keywordshuman visual system
subject keywordshuman factor
subject keywordsdeep learning
subject keywordscybersickness
subject keywordssaliency detection
subject keywordsvirtual reality
subject keywordsvisual experience
subject keywordsAR
subject keywordsVR
subject keywordsIEEE 3333.1.3
subject keywordsQoE
subject keywordsquality of experience
identifier DOI10.1109/IEEESTD.2022.9781357


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