Open Access   Article

New Iris Tracking Method using a Generalized Particle Filter

N.Yaghoobi Ershadi1

1 Universidad Politécnica de Madrid, E.T.S. Ingenieros de Telecomunicación, Madrid, Spain.

Correspondence should be addressed to:

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-9 , Page no. 7-14, Sep-2017


Online published on Sep 30, 2017

Copyright © N.Yaghoobi Ershadi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library


IEEE Style Citation: N.Yaghoobi Ershadi, “New Iris Tracking Method using a Generalized Particle Filter”, International Journal of Computer Sciences and Engineering, Vol.5, Issue.9, pp.7-14, 2017.

MLA Style Citation: N.Yaghoobi Ershadi "New Iris Tracking Method using a Generalized Particle Filter." International Journal of Computer Sciences and Engineering 5.9 (2017): 7-14.

APA Style Citation: N.Yaghoobi Ershadi, (2017). New Iris Tracking Method using a Generalized Particle Filter. International Journal of Computer Sciences and Engineering, 5(9), 7-14.

318 233 downloads 139 downloads


Precise iris tracking is an important tool in assistive technology, and has many advanced applications such as in human-computer interactions and driver fatigue detection. Features such as shape, colour, and size of the iris enable specific position and centre of the iris to be tracked during its movement. The iris tracking system is divided into four stages: image acquisition, face detection, eye detection, and eye tracking. This study proposes a new method for iris tracking using a generalized particle filter. This approach utilizes a sample set of the tracked iris which is created at the beginning of the tracking process. The prior representation and position of the tracked iris are then predicted depending on the minimization of parameters of the proposed generalized probabilistic distribution. Results of the experiments show that the proposed method has high accuracy and can be used to efficiently track the at a shorter length of time.

Key-Words / Index Term

Iris tracking; Particle filter; β-Distribution; Biometrics; Fatigue detection


[1]. E.Ghasemi-Dehkordi1, M.Mahlouji2 and H.Ebrahimpour Komleh3 “Human Eye Tracking Using Particle Filters”, IJCSI International Journal of Computer Science Issues, Vol. 10, Issue 5, No 2, September 2013.
[2]. H.R. Chennamma “A Survey on Eye-Gaze Tracking Techniques”, Indian Journal of Computer Science and Engineering (IJCSE), Vol. 4 No.5 Oct-Nov 2013.
[3]. J. Zhu, and J. Yang. “Subpixel eye gaze tracking”.5th IEEE International Conference on Automatic Face and Gesture Recognition, Page 131, May 20 - 21, 2002 .
[4]. K. Toennies, F. Behrens and M. Aurnhammer.” Feasibility of Hough-transform-based iris localization for real-timeapplication”.16th IEEE International Conference on Pattern Recognition, Quebec, Canada 11-15 Aug. 2002.
[5]. V. Raudonis, R. Simutis and G. Narvydas.” Discrete eye tracking for medical applications”. Proc. 2nd ISABEL, pp. 1–6, 2009.
[6]. S. Keerativittayanun, K. Rakjaeng, T. Kondo, W. Kongprawechnon, K. Tungpimolrut, and T. Leelasawassuk. “Eye Tracking System for Ophthalmic Operating Microscope”. ICROS-SICE International Joint Conference 2009, Fukuoka, Japan, August 18-21, 2009.
[7]. L. Ma, Y. Sun, N. Feng, Z. Liu, “Image Fast Template Matching Algorithm Based on Projection and Sequential Similarity Detecting”, Harbin Institute of Technology at Weihai, Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, China, 2009.
[8]. Y. Kuo, J. Lee and S. Kao, “Eye Tracking in Visible Environment”, Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 114-117, 2009.
[9]. J.Tang, and J. Zhang. “Eye Tracking Based on Grey Prediction.” First International Workshop on Education Technology and Computer Science. China, 7-8 March 2009.
[10]. K. D. Toennies , Beherens F., and Aurnhammer M. “Feasibility of Hough-Transform-based Iris Localisation for Real-Time-Application”, Proc Intl Symp on Eye Movements and Vision in the Natural World, Amsterdam/Rotterdam, 2002.
[11]. P. M. Daye and Optican L. M., “Saccade detection using a particle filter”, Journal of Neuroscience Methods, 235: 157–168, 2014.
[12]. D. W. Hansen and Q. Ji. In the eye of the beholder: “A survey of models for eyes and gaze”.IEEE Trans. Anal. Mach. Intell., 32(3):478–500, 2010.
[13]. W. Hotrakool, P. Siritanawan, and T. Kondo “.A realtime eye-tracking method using time-varying gradient orientation patterns”.Proc. Int. Conf. Electr. Eng., Electron. Comput. Telecommun. Inf. Technol., pp. 492–496, 2010.
[14]. B. Fu and R. Yang. “Display control based on eye gaze estimation”. Proc. 4th Int. CISP, 1:399–403, 2011.
[15]. W. Khairosfaizal and A. Nor`aini.”Eye detection in facial images using circular Hough transform”. Proc. 5th CSPA, pp. 238–242, 2009.
[16]. Y. Kuo, J. Lee, and S. Kao. “Eye tracking in visible environment”. Proc. 5th Int. Conf. IIH-MSP, pp. 114– 117, 2009.
[17]. J. Tang and J. Zhang,” Eye tracking based on grey prediction”. Proc. 1st Int. Workshop Education Technol. Computer Science, pp. 861–864, 2009.
[18]. P. Majaranta and Bulling A, “Eye Tracking and EyeBased Human–Computer Interaction”, In, S. H. Fairclough and K. Gilleade (eds.), Advances in Physiological Computing, Human–Computer Interaction Series, Springer-Verlag 2014.
[19]. M.Sadri, K. Kangarloo, F. Farokhi “Particle Filtering in the Design of an Accurate Pupil Tracking System”, International Journal of Computer Applications (IJCA), 51(8), 2012.
[20]. O. Boumbarov, Panev S., Sokolov S., and Kanchev V. IR “Based Pupil Tracking Using Particle Filtering", IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications, 21-23 September, 2009.
[21]. H. Liu and Q. Liu. Robust “real-time eye detection and tracking for rotated facial images under complex conditions”. Proc. 6th ICNC, pp. 2028–2034, 2010.
[22]. Y.Zhang, K.Jia. “A local and scale integrated feature descriptor in eye-gaze tracking”. Image and Signal Processing (CISP), 4th International Congress on, china, 15-17 Oct. 2011.