Evaluation Model of the Visual Fatigue on the 3D Stereoscopic Video

So, Gil-Ja; Kim, Sang-Hyun; Kim, Jeong-Yeop

doi:10.7763/ijcte.2016.v8.1068

Cited by 4 publications

(5 citation statements)

References 17 publications

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“…For example, Sohn et al proposed object-dependent disparity features to predict the visual discomfort in stereoscopic 3D images [17]. So et al combined the strength and size of the excessive disparity range, the complexity of the background objects, the variation of the motion-depth, and the contrast of the objects in the scene to evaluate visual fatigue [18]. Ying et al proposed a visual comfort assessment based on scene mode classification and showed that the proposed method performs higher assessment accuracy than some state-of-the-art methods [19].…”

Section: Resultsmentioning

confidence: 99%

Excessive Crossed Disparity Detection by Visual Evoked Potentials to Reduce Visual Discomfort in 3D Viewing

Wang

Yao

Qian

et al. 2018

Computational Intelligence and Neuroscience

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As excessive crossed disparity is known to cause visual discomfort, this study aims to establish a classification model to discriminate excessive crossed disparity in stereoscopic viewing in combination with subjective assessment of visual discomfort. A stereo-visual evoked potentials (VEPs) experimental system was built up to obtain the VEPs evoked by stereoscopic stimulus with different disparities. Ten volunteers participated in this experiment, and forty VEP datasets in total were extracted when the viewers were under comfortable viewing conditions. Six features of VEPs from three electrodes at the occipital lobe were chosen, and the classification was established using the Fisher's linear discriminant (FLD). Based on FLD results, the correct rate for determining the excessive crossed disparity was 70%, and it reached 80% for other stimuli. The study demonstrated cost-effective discriminant classification modelling to distinguish the stimulus with excessive crossed disparity which inclines to cause visual discomfort.

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Section: Resultsmentioning

confidence: 99%

Excessive Crossed Disparity Detection by Visual Evoked Potentials to Reduce Visual Discomfort in 3D Viewing

Wang

Yao

Qian

et al. 2018

Computational Intelligence and Neuroscience

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“…Visual fatigue, also known as eye fatigue, refers to the excessive strain experienced by the visual system due to prolonged or intensive visual tasks [1] [2]. It is a common issue faced by individuals who engage in activities such as prolonged computer usage, reading for extended periods, or driving long distances.…”

Section: Introductionmentioning

confidence: 99%

“…Most fatigue monitoring algorithms based on electrical signals use blink frequency and average eye closing time as indicators to determine the state. Some studies also perform time-frequency conversion on the acquired EOG signals, extract features from the frequency domain, and perform fatigue analysis [27] [28]. However, because this method is nonlinear in nature, it has its own limitations [29].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Connection between Eye Movement Parameters and Eye Fatigue

Sun,

Wang,

et al. 2024

J. Phys.: Conf. Ser.

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Eye fatigue, a prominent symptom of computer vision syndrome (CVS), has gained significant attention in various domains due to the increasing diversification of electronic display devices and their widespread usage scenarios. The COVID-19 pandemic has further intensified the reliance on these devices, leading to prolonged screen time. This study aimed to investigate the effectiveness of utilizing eye movement patterns in discriminating fatigue during the usage of electronic display devices. Eye movement data was collected from subjects experiencing different levels of fatigue, and their fatigue levels were recorded using the T/CVIA-73-2019 scale. The analysis revealed that features related to the pupils demonstrated a high level of confidence and reliability in distinguishing fatigue, especially related to pupil size. However, features associated with fixations, such as fixation duration and frequency, did not significantly contribute to fatigue discrimination. Furthermore, the study explored the influence of subjective awareness on fatigue discrimination. By modifying the experimental settings and considering the subjects’ subjective perception, it was observed that individual consciousness and self-awareness played a crucial role in fatigue discrimination. The implications of these findings extend beyond the field of computer vision syndrome, offering potential applications in developing interventions and strategies to alleviate eye fatigue and promote eye health among individuals who extensively use electronic display devices.

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“…Liuye Yao [10] used BP neural network to predict the fatigue caused by stereo vision. BP neural network has the function of nonlinear mapping, and on this basis, it can learn, organize, and adapt itself [11]. Therefore, this paper used a three-layer BP neural network to establish a predictive model of operators' mental load.…”

Section: Introductionmentioning

confidence: 99%

Classification and Recognition of Operators’ Mental Load Under Repetitive High-precision Tasks Based on BP Neural Network

Han¹,

Qiang²,

Li³

2021

Proceedings of the 2021 5th International Seminar on Education, Management and Social Sciences (ISEMSS 2021)

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In order to identify the mental load of operators under repetitive high-precision tasks effectively, 36 subjects were recruited in this study. The fine tasks on the electronic assembly line were simulated in the laboratory, and operators' behavioural performance (completion time, error rate) and the changes of Oxyhaemoglobin (O2Hb) in prefrontal channels 2, 8, 12, 17, 20 and 21 of the brain were characteristic factors for mental load recognition. A model of recognition of mental load state of operators based on BP neural network was constructed and the fatigue state of operators was divided into four levels. Finally, the recognition rate of the mental load state of operators was 86.81% by combining the experimental data. The combination of behavioural performance indicators and physiological measurement indicators can effectively identify mental work state of operators, which provides a new idea for classification and recognition of mental load state of operators under repetitive high-precision operation tasks, and provides a reference for the establishment of effective labour organization.

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Evaluation Model of the Visual Fatigue on the 3D Stereoscopic Video

Cited by 4 publications

References 17 publications

Excessive Crossed Disparity Detection by Visual Evoked Potentials to Reduce Visual Discomfort in 3D Viewing

Excessive Crossed Disparity Detection by Visual Evoked Potentials to Reduce Visual Discomfort in 3D Viewing

Exploring the Connection between Eye Movement Parameters and Eye Fatigue

Classification and Recognition of Operators’ Mental Load Under Repetitive High-precision Tasks Based on BP Neural Network

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