IEEE Standard for the Deep Learning-Based Assessment of Visual Experience Based on Human Factors
IEEE Std 3333.1.3-2022
Year: 2022
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.
Subject: HVS
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IEEE Standard for the Deep Learning-Based Assessment of Visual Experience Based on Human Factors
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| contributor author | IEEE - The Institute of Electrical and Electronics Engineers, Inc. | |
| date accessioned | 2022-07-04T20:40:25Z | |
| date available | 2022-07-04T20:40:25Z | |
| date copyright | 27 May 2022 | |
| date issued | 2022 | |
| identifier other | 9781357.pdf | |
| identifier uri | http://yse.yabesh.ir/std;query=autho162s6596FCDCAC4261590-%20Naval%20/handle/yse/312743 | |
| description 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. | |
| language | English | |
| title | IEEE Standard for the Deep Learning-Based Assessment of Visual Experience Based on Human Factors | en |
| title | IEEE Std 3333.1.3-2022 | num |
| type | Standard | |
| page | 51 | |
| tree | IEEE - The Institute of Electrical and Electronics Engineers, Inc.:;2022 | |
| contenttype | Fulltext | |
| subject keywords | HVS | |
| subject keywords | subjective assessment | |
| subject keywords | augmented reality | |
| subject keywords | human visual system | |
| subject keywords | human factor | |
| subject keywords | deep learning | |
| subject keywords | cybersickness | |
| subject keywords | saliency detection | |
| subject keywords | virtual reality | |
| subject keywords | visual experience | |
| subject keywords | AR | |
| subject keywords | VR | |
| subject keywords | IEEE 3333.1.3 | |
| subject keywords | QoE | |
| subject keywords | quality of experience | |
| identifier DOI | 10.1109/IEEESTD.2022.9781357 |

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