Grey Forecasting Model for Patching Blinking in Video-Oculography

Article Preview

Abstract:

Video-oculography (VOG) is a non-invasive method used for the eye tracking detecting. A most important work of VOG is to accurately estimate the pupil center. However, VOG cannot acquire eye movement when the eye blinks. A Grey forecasting model was proposed to predict the pupil center for the blinking frame of VOG video. The Grey forecasting model used GM(1,1) model to carry on the modeling. Then an experiment is provided. The experiment results show that the predicted data of the Grey forecasting meet the characteristics of the patients with nystagmus. The Grey forecasting model is a viable means of accurately predict the pupil center for blinking in VOG.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

3955-3959

Citation:

Online since:

October 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Giulio Pasquariello, Mario Cesarelli, Paolo Bifulco, Antonio Fratini, Antonio La Gatta, Maria Romano: Biomedical Signal Processing and Control, Vol. 4(2009), pp.102-107.

DOI: 10.1016/j.bspc.2009.01.003

Google Scholar

[2] J. Zanelli, J. MacCabe, T. Toulopoulou, M. Walshe, C. McDonald, R. Murray: Psychiat. Res. 168 (2009), pp.193-197.

DOI: 10.1016/j.psychres.2008.05.008

Google Scholar

[3] L. Ling, A.F. Fuchs, J.O. Phillips, E. G. Freedman: J. Neurophysiol., Vol. 82 (1999), pp.2808-2811.

Google Scholar

[4] A.H. Clarke, W. Teiwes, H. Scherer: Acta Astronaut, Vol. 23 (1991), pp.307-309.

Google Scholar

[5] M. Grozinger, J. Roschke: Neuropsychobiology, Vol. 33 (1996), pp.155-159.

Google Scholar

[6] K. Rayner, C.M. Rotello, A.J. Stewart, J. Keir, S.A. Duffy: J. Exp. Psychol. Appl., Vol. 7 (2001), pp.155-159.

Google Scholar

[7] G.L. Lohse: J. Advertising, Vol. 26(1997), pp.61-73.

Google Scholar

[8] E Marg: A. M. A. Arch. Ophthalmol., Vol. 45(1951) , pp.169-185.

Google Scholar

[9] D.A. Robinson: IEEE Trans. Biomed. Eng. , BM10 (1963), p.137–145.

Google Scholar

[10] S. Anders, N. Weiskopf, D. Lule, N. Birbaumer: Neuroimage, Vol. 22 (2004), pp.767-770.

DOI: 10.1016/j.neuroimage.2004.01.024

Google Scholar

[11] E. Magosso, M. Ursino, A. Zaniboni, E. Gardella: Appl. Math. Comput., Vol. 207(2009), pp.42-62.

Google Scholar

[12] H. D. Schworm, J. Ygge, T. Pansell, G. Lennerstrand: Invest. Ophth. Vis. Sci., Vol. 43(2002), pp.662-667.

Google Scholar

[13] C.A. McGibbon, T. Palmer, D. Goldvasser, D. E. Krebs: J. Neurosci. Meth., Vol. 106(2001), pp.171-178.

Google Scholar

[14] Zhang, G.P.: Neurocomputing, Vol. 50 (2003), P. 159-175.

Google Scholar

[15] W.K. Wong, M. Xia, W.C. Chu: Eur. J. Oper. Res., Vol. 207(2010), pp.807-816.

Google Scholar

[16] J.L. Deng: Syst. Control Lett., Vol. 1(1982), P. 288-294.

Google Scholar

[17] J.L. Deng: Huazhong University of Science and Technology Press, Wuhan, 1986, pp.97-134.

Google Scholar

[18] J.L. Deng: J. Grey Syst., Vol. 1 (1989), pp.1-24.

Google Scholar