Skip to main content
Log in

Eye detection based on the Viola-Jones method and corners points

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Eyes detection is a very interesting field of research that verifies the presence of eyes and locates their positions in an image. Similarly, it is often the first step in such applications such as face recognition, human machine interaction systems, facial expression recognition, and driver fatigue monitoring systems. In this paper, we proposed a robust eye detection method based on the Viola and Jones method and corner points. Firstly, faces are detected by a system composed of two detectors of Viola-Jones (one for the frontal faces and the other for the profile faces). Secondly, we used the Shi-Tomasi detector (to detect corner points) and K-means (for clustering the neighbor corner points) to determine eye candidate regions. Thirdly, the localization of eyes is achieved by matching of these regions with an eye template. The results obtained show that our method is robust and provides superior performance compared to other recently published methods.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Abdel-Kader RF, Atta R, El-Shakhabe S (2014) An efficient eye detection and tracking system based on particle swarm optimization and adaptive block-matching search algorithm. Eng Appl Artif Intell 31:90–100. doi:10.1016/j.engappai.2013.06.017i

    Article  Google Scholar 

  2. Al-Rahayfeh A, Faezipour M (2013) Eye tracking and head movement detection: a state-of-art survey. IEEE J Transl Eng Health Med 1(14):11–22. doi:10.1109/JTEHM.2013.2289879

    Google Scholar 

  3. Bhatta LK, Rana D (2014) Facial feature extraction of color image using gray scale intensity value. Int J Eng Res Technol (IJERT) 3(3):1177–1180

    Google Scholar 

  4. Cheddad A, Mohamad D, Manaf AA (2008) Exploiting Voronoi diagram properties in face segmentation and feature extraction. Pattern Recogn 41:3842–3859. doi:10.1016/j.patcog.2008.06.007

    Article  MATH  Google Scholar 

  5. Chen S, Liu C (2015) Eye detection using discriminatory Haar features and a new efficient SVM. Elsevier, Image Vision Comput 33:68–77. doi:10.1016/j.imavis.2014.10.007

    Article  Google Scholar 

  6. Choi I, Kim D (2017) A variety of local structure patterns and their hybridization for accurate eye detection. Pattern Recogn 61:417–432. doi:10.1016/j.patcog.2016.08.009

    Article  Google Scholar 

  7. Choi S-I, Lee Y, Kim C (2015) Confidence measure using composite features for eye detection in a face recognition system. IEEE Signal Process Lett 22(2):225–228. doi:10.1109/LSP.2014.2335198

    Article  Google Scholar 

  8. Cyganek B, Gruszczyński S (2014) Hybrid computer vision system for drivers' eye recognition and fatigue monitoring. Neural Comput 126:78–94. doi:10.1016/j.neucom.2013.01.048

    Google Scholar 

  9. El Kaddouhi S, Saaidi A, Abarkan M (2014) A new robust face detection method based on corner points. International Journal of Software Engineering and Its Applications 8(11):25–40. doi:10.14257/ijseia.2014.8.11.03

    Google Scholar 

  10. Ge S, Yang R, He Y, Xie K, Zhu H, Chen S (2016) Learning multi-channel correlation filter bank for eye localization. Neurocomputing 173(2):418–424. doi:10.1016/j.neucom.2015.03.125

    Article  Google Scholar 

  11. Ghazali KH, Jadin MS, Ma J, Xiao R (2015) Novel automatic eye detection and tracking algorithm. Opt Lasers Eng 67:49–56. doi:10.1016/j.optlaseng.2014.11.003

    Article  Google Scholar 

  12. Gonzalez-Ortega D, Diaz-Pernas FJ, Anton-Rodriguez M, Martinez-Zarzuela M, Diez-Higuera JF (2013) Real-time vision-based eye state detection for driver alertness monitoring. Pattern Anal Applic 16(3):285–306. doi:10.1007/s10044-013-0331-0

    Article  MathSciNet  Google Scholar 

  13. Han Z, Tieming S, Zongying O, XuPrecise W (2014) Precise localization of eye centers with multiple cues. Multimed Tools Appl 68(3):931–945. doi:10.1007/s11042-012-1090-4

    Article  Google Scholar 

  14. Hansen DW, Ji Q (2010) In the eye of the beholder: a survey of models for eyes and gaze. IEEE Trans Pattern Anal Mach Intell 32(3):478–500. doi:10.1109/TPAMI.2009.30

    Article  Google Scholar 

  15. Hassaballah M, Kanazawa T, Ido S (2010) Efficient eye detection method based on grey intensity variance and independent components analysis. IET Comput Vis 4(4):261–271. doi:10.1049/iet-cvi.2009.0097

    Article  Google Scholar 

  16. Ibrahim LF, Abulkhair M, AlShomrani AD, AL-Garni M, AL-Mutiry A, AL-Gamdi F, Kalenen R (2014) Using Haar classifiers to detect driver fatigue and provide alerts. Multimed Tools Appl 71(3):1857–1877. doi:10.1007/s11042-012-1308-5

    Article  Google Scholar 

  17. Jesorsky O, Kirchberg KJ, Frischholz R (2001) Robust face detection using the hausdorff distance. Third International Conference, AVBPA 2001 Halmstad, Sweden, (Proceedings), pp:90–95

  18. Jian M, Lam K-M (2013) Fast eye detection and localization using a salient map. Era Interactive Media:89–99. doi:10.1007/978-1-4614-3501-3_8

  19. Jian M, Lam K-M, Dong J (2014) Facial-feature detection and localization based on a hierarchical scheme. Inf Sci 262:1–14. doi:10.1016/j.ins.2013.12.001

    Article  Google Scholar 

  20. Jiayu G, Liu C (2013) Feature local binary patterns with application to eye detection. Neurocomputing 113:138–152. doi:10.1016/j.neucom.2013.01.007

    Article  Google Scholar 

  21. Jung C, Sun T, Jiao L (2013) Eye detection under varying illumination using the retinex theory. Neurocomputing 113:130–137. doi:10.1016/j.neucom.2013.01.038

    Article  Google Scholar 

  22. Karaaba MF, Schomaker L, Wiering M (2014) Machine learning for multi-view eye-pair detection. Eng Appl Artif Intell 33:69–79. doi:10.1016/j.engappai.2014.04.008

    Article  Google Scholar 

  23. Kim C, Choi S-I, Turk M, Choi C-H (2012) A new biased discriminant analysis using composite vectors for eye detection. IEEE Trans Syst, Man, Cybern—Part B: Cybern 42(4):1095–1106. doi:10.1109/TSMCB.2012.2186798

    Article  Google Scholar 

  24. Lin Y-T et al (2013) Real-time eye-gaze estimation using a low-resolution webcam. Multimed Tools Appl 65(3):543–568. doi:10.1007/s11042-012-1202-1

    Article  Google Scholar 

  25. MacQueen JB (1967) Some methods for classification and analysis of multivariate observations, Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability, Berkeley, University of California Press, 1:281–297.

  26. Mingxin Y, Yingzi L, Xiangzhou W (2016) An efficient hybrid eye detection method. Turk J Electr Eng Comput Sci 24:1586–1603. doi:10.3906/elk-1312-150

  27. Monzo D, Albiol A, Sastre J, Albiol A (2011) Precise eye localization using HOG descriptors. Mach Vis Appl 22:471–480. doi:10.1007/s00138-010-0273-0

    Google Scholar 

  28. Nanaa K et al (2013) Eye detection using composite cross-correlation. Am J Appl Sci 10(11):1448–1456. doi:10.3844/ajassp.2013.1448.1456

    Article  Google Scholar 

  29. Ren J, Jiang X, Yuan J (2013) A complete and fully automated face verification system on mobile devices. Pattern Recogn 46:45–56. doi:10.1016/j.patcog.2012.06.013

    Article  Google Scholar 

  30. Ren Y, Wang S, Hou B, Ma J (2014) A novel eye localization method with rotation invariance. IEEE Trans Image Process 23(1):226–239. doi:10.1109/TIP.2013.2287614

    Article  MathSciNet  Google Scholar 

  31. Rusek K, Guzik P (2014) Two-stage neural network regression of eye location in face images. Multimed Tools Appl (Open Access):1–14. doi:10.1007/s11042-014-2114-z

  32. Savakis RSA (2015) Lean histogram of oriented gradients features for effective eye detection. J Electron Imaging 24(6):1–12. doi:10.1117/1.JEI.24.6.063007

    Google Scholar 

  33. Shi J, Tomasi C (1994) Good features to track. Proceedings of the IEEE Conference of Computer Vision and Pattern Recognition (CVPR’94). Seattle. doi: 10.3844/ajassp.2013.1448.1456

  34. Siddiqi MH, Ali R, Khan AM, Kim ES, Kim GJ, Lee S (2015) Facial expression recognition using active contour-based face detection, facial movement-based feature extraction, and non-linear feature selection. Multimedia Systems 21:541–555. doi:10.1007/s00530-014-0400-2

    Article  Google Scholar 

  35. Skodras E, Fakotakis N (2015) Precise localization of eye centers in low resolution color images. Image Vis Comput 36:51–60. doi:10.1016/j.imavis.2015.01.006

    Article  Google Scholar 

  36. Song F, Tan X, Chen S, Zhou Z-H (2013) A literature survey on robust and efficient eye localization in real-life scenarios. Pattern Recogn 46(12):3157–3173. doi:10.1016/j.patcog.2013.05.009i

    Article  Google Scholar 

  37. Srutekand M, Matuszak L (2010) Eye tracking system for human computer interaction. Springer-Verlag Berlin Heidelberg, Advances in Intelligent and Soft Computing, pp:361–369

  38. Sun Y, Wang X, Tang X (2013) Deep convolutional network cascade for facial point detection. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp: 3474–3481. doi: 10.1109/CVPR.2013.446

  39. The BioID Face Database (2016) http://www.bioid.com

  40. The FEI face database (2016) http://fei.edu.br/~cet/facedatabase.html

  41. Valenti R, Gevers T (2012) Accurate eye center location through invariant Isocentric patterns. IEEE Trans Pattern Anal Mach Intell 34(09):1785–1798. doi:10.1109/TPAMI.2011.251

    Article  Google Scholar 

  42. Viola P, Jones M (2004) Robust real-time face detection. Int J Comput Vis 57(2):137–154. doi:10.1023/B:VISI.0000013087.49260.fb

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to S. El Kaddouhi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

El Kaddouhi, S., Saaidi, A. & Abarkan, M. Eye detection based on the Viola-Jones method and corners points. Multimed Tools Appl 76, 23077–23097 (2017). https://doi.org/10.1007/s11042-017-4415-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-017-4415-5

Keywords

Navigation