Journal of Guangxi Normal University(Natural Science Edition) ›› 2018, Vol. 36 ›› Issue (2): 134-140.doi: 10.16088/j.issn.1001-6600.2018.02.019

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Relationship between the Information Entropy of Visual Sense and Vection Induced by Virtual Rotational Drum

WEI Miaoluan1,2,LIN Jiayin1,2,LIU Ru′e3,LUO Jie1,2*   

  1. 1.School of Engineering, Sun Yat-sen University,Guangzhou Guangdong 510006,China;
    2. Key Laboratory of Sensor Technology and Biomedical Instrument of Guangdong Province, Guangzhou Guangdong 510006,China;
    3. Equipment Department of Sun Yat-sen Memorial Hospital,Sun Yat-sen University,Guangzhou Guangdong 510006,China
  • Received:2017-04-19 Online:2018-05-10 Published:2018-07-18

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Abstract: As an emerging technology, virtual reality is expected to be used in the field of medicine, rehabilitation and so on. A series of psychological phenomena, which have been reported, are affected by the rotational direction and the FOV of virtual reality scenes. However, there is no reported quantitative method to analyze the role of virtual reality scenes in vection perception. In this article, 55 participants were enrolled to view the virtual rotational drum rotating around Pitch axis and Yaw axis respectively, and were required to report vection onset and the strength orally. The two kinds of scenes were randomly displayed and repeated three times for each subject, and each display lasted for 90s. The information of the visual scenes was estimated by the first-order entropy of the optical flow. Vection perception was found to be stronger in Pitch rotation condition and the optical flow entropy of this scene was larger. In conclusion, the experiment verified that the brain is more sensitive to downward movement from the perspective of the information quantity of visual sense.

Key words: virtual reality, vection, entropy, field of view, rotational drum

CLC Number: 

  • Q426
[1] PALMISANO S, MURSIC R, KIM J. Vection and cybersickness generated by head-and-display motion in the Oculus Rift[J]. Displays, 2017, 46: 1-8.
[2] PALMISANO S, ALLISON R S, SCHIRA M M, et al. Future challenges for vection research: definitions, functional significance, measures, and neural bases[J]. Frontiers in Psychology, 2015, 6(193): 193-207.
[3] CHERTOFF D, SCHATZ S. Beyond presence: how holistic experience drives training and education[M]//Handbook of Virtual Environments: Design, Implementation, and Applications, Second Edition. United States: CRC Press, 2014: 857-871.
[4] TRUTOIU L C, MOHLER B J, SCHULTE-PELKUM J, et al. Circular, linear, and curvilinear vection in a large-screen virtual environment with floor projection[J]. Computers and Graphics, 2009, 33(1): 47-58.
[5] TSAI D Y, LEE Y, MATSUYAMA E. Information entropy measure for evaluation of image quality[J]. Journal of Digital Imaging, 2008, 21(3): 338-47.
[6] 朱桂英, 张瑞林. 信息熵在图像处理中的应用[J]. 丝绸, 2006 (12): 34-36.
[7] 孙君顶, 丁振国, 周利华. 基于图像信息熵与空间分布熵的彩色图像检索方法[J]. 红外与毫米波学报, 2005, 24(2): 135-139.
[8] 王学忠, 肖斌. 一种基于图像信息熵的自适应滤波算法[J]. 计算机应用, 2008, 28(10): 2643-2644.
[9] 吴泽鹏, 郭玲玲, 朱明超, 等. 结合图像信息熵和特征点的图像配准方法[J]. 红外与激光工程, 2013, 42(10): 2846-2852.
[10] HU S, DAVIS M S, KLOSE A H, et al. Effects of spatial frequency of a vertically striped rotating drum on vection-induced motion sickness[J]. Aviation Space and Environmental Medicine, 1997, 68(4): 306-311.
[11] BONATO F, BUBKA A, ALFIERI L. Display color affects motion sickness symptoms in an optokinetic drum[J]. Aviation Space and Environmental Medicine, 2004, 75(75): 306-311.
[12] GIBSON J J. The perception of the visual world[J]. Journal of Aesthetics and Art Criticism, 1950, 11(2): 172.
[13] LUCAS B D, KANADE T. An iterative image registration technique with an application to stereo vision[C]//International Joint Conference on Artificial Intelligence. Burlington: Organ Kaufmann Publishers Inc, 1981: 674-679.
[14] ALLISON R S, HOWARD I P, ZACHER J E. Effect of field size, head motion, and rotational velocity on roll vection and illusory self-tilt in a tumbling room[J]. Perception, 1999, 28(3): 299-306.
[15] GONZALEZ R C, WOODS R E. Digital image processing[M]. 2 ed. Upper Saddle River: Prentice Hall,2002.
[16] KANO C. The perception of self-motion induced by peripheral visual information in sitting and supine postures[J]. Ecological Psychology, 1991, 3(3): 241-252.
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