IEEE - 3333.1.3
The Deep Learning‐Based Assessment of Visual Experience Based on Human Factors
| Organization: | IEEE |
| Publication Date: | 9 February 2022 |
| Status: | active |
| Page Count: | 51 |
scope:
This standard defines deep learning-based metrics of content analysis and quality of experience (QoE) assessment for visual contents, which is an extension of the standard for the QoE and visual-comfort assessments of three-dimensional (3D) contents based on psychophysical studies (IEEE Std 3333.1.1™) and the standard for the perceptual quality assessment of 3D and ultra-high definition (UHD) contents (IEEE Std 3333.1.2™). The scope covers the following:
- Deep learning models for QoE assessment (multilayer perceptrons, convolutional neural networks, deep generative models)
- Deep metrics of visual experience from high definition (HD), UHD, 3D, high dynamic range (HDR), virtual reality (VR) and mixed reality (MR) contents
- Deep analysis of clinical (electroencephalogra
- Deep personalized preference assessment of visual contents
- Building image and video databases for performance benchmarking purpose if necessary
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