A Deep Learning based Framework for Detecting and Reducing onset of Cybersickness
A Deep Learning based Framework for Detecting and Reducing onset of Cybersickness
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基于深度学习的框架，用于检测和减少网络病的发生
DOI：
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发表时间：
2020
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通讯作者：
Rifatul Islam
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作者：
Rifatul Islam
Cybersickness是与虚拟现实（VR）应用相关的显著不适之一。随着机器学习的最新进展，我们可以训练深度神经网络来从生理和VR图像数据中检测网络病的严重程度。先前的研究发现生理和VR图像数据与晕电病之间的相关性。在本研究中，我假设检测发病严重程度的电脑病。最后，根据严重程度，实时自动应用不同的减少晕电技术。
Cybersickness is one of the notable discomforts associated with virtual reality(VR) applications. With the recent advancement of machine learning, we can train deep neural networks to detect cyber-sickness severity from the physiological and VR-image data. Prior researches found a correlation between physiological and VR-image data with cybersickness. In this study, I hypothesize to detect the onset severity of cybersickness. Finally, based on the severity level, automatically apply different cybersickness reduction techniques in real-time.