Optics and Precision Engineering, Volume. 32, Issue 4, 595(2024)
Spatiotemporal multi-feature evaluation of visually induced motion sickness in virtual reality
[1] KOURTESIS P, AMIR R, LINNELL J et al. Cybersickness, cognition, & motor skills: the effects of music, gender, and gaming experience[J]. IEEE Transactions on Visualization and Computer Graphics, 29, 2326-2336(2023).
[2] HSIAO C Y, KUO C C, LIOU Y A et al. Determining work-rest schedules for visual tasks that use optical head-mounted displays based on visual fatigue and visually induced motion sickness recovery[J]. International Journal of Environmental Research and Public Health, 20, 1880(2023).
[3] YIP S H, SAUNDERS J A. Restricting the distribution of visual attention reduces cybersickness[J]. Cognitive Research: Principles and Implications, 8, 18(2023).
[4] OH H, SON W, OH H, SON W. Cybersickness and its severity arising from virtual reality content: a comprehensive study[J]. Sensors, 22, 1314(2022).
[5] LOU R D, MÉRIENNE F, SO R H Y et al. Geometric Simplification for Reducing Optic Flow in VR[C], 682-685(2022).
[6] KENNEDY R S, LANE N E, BERBAUM K S et al. Simulator sickness questionnaire: an enhanced method for quantifying simulator sickness[J]. The International Journal of Aviation Psychology, 3, 203-220(1993).
[7] GUNA J, GERŠAK G, HUMAR I et al. Influence of video content type on users' virtual reality sickness perception and physiological response[J]. Future Generation Computer Systems, 91, 263-276(2019).
[8] KIM J, KIM W et al. Virtual Reality Sickness Predictor: Analysis of Visual-Vestibular Conflict and VR Contents[C], 1-6(2018).
[9] KIM J, KIM W et al. A deep motion sickness predictor induced by visual stimuli in virtual reality[J]. IEEE Transactions on Neural Networks and Learning Systems, 33, 554-566(2022).
[10] KIM W, LEE S, BOVIK A C. VR sickness versus VR presence: a statistical prediction model[J]. IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society, 30, 559-571(2021).
[11] LEE S M, KIM S, KIM H G et al. Physiological fusion net: quantifying individual VR sickness with content stimulus and physiological response[C], 440-444(2019).
[12] LEE S M, KIM J U, KIM H G et al.
[13] KIM H G, LIM H T, LEE S M et al. VRSA net: VR sickness assessment considering exceptional motion for 360° VR video[J]. IEEE Transactions on Image Processing, 28, 1646-1660(2019).
[14] KIM S, LEE S M, RO Y M. Estimating VR sickness caused by camera shake in VR videography[C], 3433-3437(2020).
[15] KIM H G, LEE S M, KIM S et al. Towards a better understanding of VR sickness: physical symptom prediction for VR contents[J]. Proceedings of the AAAI Conference on Artificial Intelligence, 35, 836-844(2021).
[16] LEE S M, KIM S, KIM H G et al. Assessing individual VR sickness through deep feature fusion of VR video and physiological response[J]. IEEE Transactions on Circuits and Systems for Video Technology, 32, 2895-2907(2022).
[17] LUO S H, REN P, ZHU C F. A model for predicting the level of motion sickness caused by virtual reality content by using attention and effective visual field mechanism[C], 400-407(2023).
[18] PADMANABAN N, RUBAN T, SITZMANN V et al. Towards a machine-learning approach for sickness prediction in 360° stereoscopic videos[J]. IEEE Transactions on Visualization and Computer Graphics, 24, 1594-1603(2018).
[19] LU Z A, YU M, JIANG G Y et al. Prediction of motion sickness degree of stereoscopic panoramic videos based on content perception and binocular characteristics[J]. Digital Signal Processing, 132, 103787(2023).
[20] WEI J, WANG S H, WU Z et al. Label decoupling framework for salient object detection[C], 13022-13031(2020).
[21] LIU C, FREEMAN W T, ADELSON E H et al. Human-assisted motion annotation[C], 1-8(2008).
[22] SUMAYLI Y, YE Y. Motion sickness during roll motion: VR HMD view versus monitor view[J]. Vibration, 6, 45-56(2023).
[23] ROGERS C, RUSHTON S K, WARREN P A. Peripheral visual cues contribute to the perception of object movement during self-movement[J]. i-Perception, 8, 2041669517736072(2017).
[24] [24] 江本赤, 卞仕磊, 史晨阳, 等. 基于色貌尺度相位一致性的全参考图像质量评价[J]. 光学 精密工程, 2023, 31(10): 1509-1521. doi: 10.37188/ope.20233110.1509JIANGB C, BIANS L, SHIC Y, et al. Full reference image quality assessment based on color appearance-based phase consistency[J]. Opt. Precision Eng., 2023, 31(10): 1509-1521.(in Chinese). doi: 10.37188/ope.20233110.1509
[25] ZHOU Y, LIANG Y S, LIU W et al. Research on video motion characteristics extraction and description based on human visual characteristics[C], 936-940(2017).
[26] [26] 权巍, 王超, 耿雪娜, 等. 基于运动感知的VR体验舒适度研究[J]. 系统仿真学报, 2023, 35(1): 169-177.QUANW, WANGC, GENGX N, et al. Research on VR experience comfort based on motion perception[J]. Journal of System Simulation, 2023, 35(1): 169-177.(in Chinese)
[27] ZHOU Y, YU W L, LI Z et al. Stereoscopic visual discomfort prediction using multi-scale DCT Features[C], 184-191(2019).
[28] LOHMAN J, TURCHET L. Evaluating cybersickness of walking on an omnidirectional treadmill in virtual reality[J]. IEEE Transactions on Human-Machine Systems, 52, 613-623(2022).
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Qifeng DONG, Mei YU, Zhidi JIANG, Ziang LU, Gangyi JIANG. Spatiotemporal multi-feature evaluation of visually induced motion sickness in virtual reality[J]. Optics and Precision Engineering, 2024, 32(4): 595
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Received: Sep. 2, 2023
Accepted: --
Published Online: Apr. 2, 2024
The Author Email: Mei YU (yumei@nbu.edu.cn)