A Portable System of Visual Fatigue Evaluation for Stereoscopic Display

2017 ◽  
pp. 296-306
Author(s):  
Yue Bai ◽  
Jun-Dong Cho ◽  
Ghulam Hussain ◽  
Song-Yun Xie
Keyword(s):  
Stereoscopic Display ◽  
Visual Fatigue ◽  
Portable System ◽  
Fatigue Evaluation

scholarly journals Visual fatigue and discomfort after stereoscopic display viewing

2012 ◽  
Vol 91 (2) ◽  
pp. e149-e153 ◽  
Author(s):  
Li Zhang ◽  
Ya-Qin Zhang ◽  
Jing-Shang Zhang ◽  
Liang Xu ◽  
Jost B. Jonas
Keyword(s):  
Stereoscopic Display ◽  
Visual Fatigue

Visual fatigue evaluation and enhancement for 2D-plus-depth video

2010 ◽  
Author(s):  
Jaeseob Choi ◽  
Donghyun Kim ◽  
Bumsub Ham ◽  
Sunghwan Choi ◽  
Kwanghoon Sohn
Keyword(s):  
Visual Fatigue ◽  
Depth Video ◽  
Fatigue Evaluation

Visual fatigue evaluation based on depth in 3D videos

2013 ◽  
Author(s):  
Feng-jiao Wang ◽  
Xin-zhu Sang ◽  
Yangdong Liu ◽  
Guo-zhong Shi ◽  
Da-xiong Xu
Keyword(s):  
Visual Fatigue ◽  
Fatigue Evaluation

scholarly journals The Impact of Color Rendering on Visual Fatigue in Interior Zone of Tunnel

2021 ◽  
Vol 276 ◽  
pp. 02008
Author(s):  
Peng Liu ◽  
LiLi Dong ◽  
YingQi Jiang
Keyword(s):  
Traffic Safety ◽  
Visual Fatigue ◽  
Mesopic Vision ◽  
The Difference ◽  
Fatigue Evaluation ◽  
Critical Fusion Frequency ◽  
Color Rendering ◽  
Human Eyes ◽  
The Impact ◽  
Positive Effect

Judicious use of lamps is of profound significance to improve the internal traffic safety of tunnels. This study evaluated the effect of LED color on human visual fatigue under mesopic vision category. According to the difference of human eyes’ response to different wavelengths of light radiation, the mesopic vision spectral luminous efficiency curve is applied to the visual fatigue evaluation methods. Taking the critical fusion frequency as the physiological index, the detection experiment of human visual fatigue was carried out in the simulated tunnel environment. The results show that spectrum with high color rendering index has a positive effect on alleviating drivers’ visual fatigue, and is more suitable for tunnel interior lighting.

scholarly journals EEG-Based 3D Visual Fatigue Evaluation Using CNN

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1208 ◽  
Author(s):  
Kang Yue ◽  
Danli Wang
Keyword(s):  
Feature Extraction ◽  
Temporal Structure ◽  
Visual Fatigue ◽  
Eeg Signals ◽  
Visual Evaluation ◽  
Time Frequency ◽  
Multi Scale ◽  
Temporal Features ◽  
Depth Analysis ◽  
Fatigue Evaluation

Visual fatigue evaluation plays an important role in applications such as virtual reality since the visual fatigue symptoms always affect the user experience seriously. Existing visual evaluation methods require hand-crafted features for classification, and conduct feature extraction and classification in a separated manner. In this paper, we conduct a designed experiment to collect electroencephalogram (EEG) signals of various visual fatigue levels, and present a multi-scale convolutional neural network (CNN) architecture named MorletInceptionNet to detect visual fatigue using EEG as input, which exploits the spatial-temporal structure of multichannel EEG signals. Our MorletInceptionNet adopts a joint space-time-frequency features extraction scheme in which Morlet wavelet-like kernels are used for time-frequency raw feature extraction and inception architecture are further used to extract multi-scale temporal features. Then, the multi-scale temporal features are concatenated and fed to the fully connected layer for visual fatigue evaluation using classification. In experiment evaluation, we compare our method with five state-of-the-art methods, and the results demonstrate that our model achieve overally the best performance better performance for two widely used evaluation metrics, i.e., classification accuracy and kappa value. Furthermore, we use input-perturbation network-prediction correlation maps to conduct in-depth analysis into the reason why the proposed method outperforms other methods. The results suggest that our model is sensitive to the perturbation of β (14–30 Hz) and γ (30–40 Hz) bands. Furthermore, their spatial patterns are of high correlation with that of the corresponding power spectral densities which are used as evaluation features traditionally. This finding provides evidence of the hypothesis that the proposed model can learn the joint time-frequency-space features to distinguish fatigue levels automatically.

Visual Fatigue Assessment Based on Multi-task Learning

2019 ◽  
Vol 63 (6) ◽  
pp. 60414-1-60414-8
Author(s):  
Danli Wang ◽  
Xueyu Wang ◽  
Yaguang Song ◽  
Qian Xing ◽  
Nan Zheng
Keyword(s):  
Rapid Development ◽  
Assessment Model ◽  
Learning Method ◽  
Stereoscopic Display ◽  
Visual Fatigue ◽  
Fatigue Assessment ◽  
Task Learning ◽  
Eeg Data ◽  
Display Technology ◽  
Electroencephalogram Eeg

Abstract In recent years, with the rapid development of stereoscopic display technology, its applications have become increasingly popular in many fields, and, meanwhile, the number of audiences is also growing. The problem of visual fatigue is becoming more and more prominent. Visual fatigue is mainly caused by vergence‐accommodation conflicts. An evaluation experiment was conducted, and the electroencephalogram (EEG) data of the subjects were collected when they were watching stereoscopic content, and then the stereoscopic fatigue state of the subjects during the viewing process was analyzed. As deep learning is proved to be an effective end-to-end learning method and multi-task learning can alleviate the problem of lacking annotated data, the authors establish a user visual fatigue assessment model based on EEG by using multi-task learning, which can effectively obtain the user’s visual fatigue status, so as to make the comfort designs to avoid the harm caused by user’s visual fatigue.

Subjective evaluation of visual fatigue due to misalignment of motion and still images in a stereoscopic display

2012 ◽  
Vol 20 (2) ◽  
pp. 94 ◽  
Author(s):  
Shoji Yamamoto ◽  
Mitomo Maeda ◽  
Norimichi Tsumura ◽  
Toshiya Nakaguchi ◽  
Ryutaro Okamoto ◽  
...  
Keyword(s):  
Subjective Evaluation ◽  
Stereoscopic Display ◽  
Visual Fatigue ◽  
Still Images
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