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.
Similar content being viewed by others
References
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
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
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
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
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
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
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
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
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
Ge S, Yang R, He Y, **e 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
Ghazali KH, Jadin MS, Ma J, **ao R (2015) Novel automatic eye detection and tracking algorithm. Opt Lasers Eng 67:49–56. doi:10.1016/j.optlaseng.2014.11.003
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
Mingxin Y, Yingzi L, **angzhou W (2016) An efficient hybrid eye detection method. Turk J Electr Eng Comput Sci 24:1586–1603. doi:10.3906/elk-1312-150
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
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
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
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
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
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
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
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
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
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
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
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
The BioID Face Database (2016) http://www.bioid.com
The FEI face database (2016) http://fei.edu.br/~cet/facedatabase.html
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
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
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
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
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-017-4415-5