Gaze Estimation Based on Single Camera

Abstract:

A new gaze tracking method used in single camera gaze tracking system is proposed. The method can be divided into human face and eye location, human features detection and gaze parameters extraction, and ELM based gaze point estimation. In face and eye location, a face detection method which combines skin color model with Adaboost method is used for fast human face detection. In eye features and gaze parameters extraction, many image processing methods are used to detect eye features such as iris center, inner eye corner and so on. And then gaze parameter which is the vector from iris center to eye corner is obtained. After above an ELM based gaze point on the screen estimation method is proposed to establish the mapping relationship between gaze parameter and gaze point. The experimental results illustrate that the method in this paper is effective to do gaze estimation in single camera gaze tracking system.

• Periodical: Advanced Materials Research (Volumes 655-657)
• Pages: 1066-1076
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.655-657.1066
• Online since: January 2013
• Authors: Bo Zhu, Peng Yun Zhang, Jian Nan Chi, Tian Xia Zhang
• Keywords: Elm, Eye Features and Gaze Parameters Extraction, Gaze Estimation, Gaze Tracking, Human Face and Eye Location

References

[1] Duchowski T. Eye Tracking Methodology: Theory and Practice. New York: Springer-Verlag (2003).

[2] Jacob R J K. The use of eye movements in human computer interaction techniques: what you look at is what you get. ACM Trans Inf Syst, 1991, 9: 152–169.

DOI: 10.1145/123078.128728

[3] Zhu Z, Ji Q. Eye and gaze tracking for interactive graphic display. Mach Vis Appl, 15: 139–148(2004).

[3] Zhiwei Zhu and Qiang Ji. Eye and gaze tracking for interactive graphic display., Machine Vision and Applications, 15, 139–148(2004).

DOI: 10.1007/s00138-004-0139-4

[4] Xie X, Sudhakar R, Zhuang H. A cascaded scheme for eye tracking and head movement compensation. IEEE Trans Syst Man Cybern Part A-Syst Hum, 28: 487-490(1998).

DOI: 10.1109/3468.686709

[5] Jixu Chen Qiang Ji . 3D Gaze Estimation with a Single Camera without IR Illumination[A]. in Proc. 19th IEEE ICPR[C], Tampa, FL( 2008).

DOI: 10.1109/icpr.2008.4761343

[6] Zhiwei Zhu and Qiang Ji. Novel eye gaze tracking techniques under natural head movement. IEEE Trans Biomed Eng, 54: 2246–2260(2007).

DOI: 10.1109/tbme.2007.895750

[7] Rein-Lien Hsu, Mohaned Abdel-Mottaleb, Anil K. Jain. Face detection in color image[J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 24(5): 696-706(2002).

DOI: 10.1109/34.1000242

[8] Wang Peng, Ji Qiang. Multi-View Face and Eye Detection Using Discriminant Features[J]. Computer Vision and Image Understanding, 105( 2) : 99-111(2007).

DOI: 10.1016/j.cviu.2006.08.008

[9] Guang-Bin Huang, Qin-Yu Zhu, Chee-Kheong Siew. Extreme learning machine: Theory and applications. Proceedings of International Joint Conference on Neural Networks (IJCNN2004), 126(12): 489-501(2005).

DOI: 10.1109/ijcnn.2004.1380068

[10] H. Rowley, S. Baluja, and T. Kanade. Neural network-based face detection. In IEEE Patt. Anal. Mach. Intell., volume 20, pages 22–38(1998).

DOI: 10.1109/34.655647

[11] Zhao Nannan. Multi-View Face Detection Based on the Adaboost Algorithm and the Skin Color Model., Computer Engineering & Science, 33(5), 85–90( 2011).

[12] Bo ZHU, Peng-yun ZHANG, Chuang ZHANG, Wei ZHOU, Jian-nan CHI, Tian-xia ZHANG. Research and Design of Real-time Eye Location and Algorithm[C]. /COCA International Conference of Transportation Professionals 2012(CICTP2012), ASCE: 2289-2230(2012).

DOI: 10.1061/9780784412442.232

[13] Otsu Nobuyuki. A threshold selection method from graylevel histograms [J]. IEEE Transactions on Systems, Man, and Cybernetics, 9 : 62-66(1979).

DOI: 10.1109/tsmc.1979.4310076

[14] Z. Ramdane Cheri，Nait-Ali，J F. Motsch，M. 0. Krebs. AN ADAPTIVE CALIBRATION OF AN INFRARED LIGTH DEVICE USEDFOR GAZE TRACKING[C]/: IEEE Instrumentation and Measurement Technology Conference Anchorage, AK, USA: 1029-1033(2002).

DOI: 10.1109/imtc.2002.1007096

[15] G. Di Leo, C. Liguori, A. Paolillo, P. Sommella. An improved procedure for the automatic detection of dermoscopic structures in digital ELM images of skin lesions. IEEE International Conference on Virtual Environments, Human-Computer Interfaces and Measurement Systems, Turkey, 14-16, July: 190-194(2008).

DOI: 10.1109/vecims.2008.4592778

[16] Rui Zhang, Yuan Lan, Guang-Bin Huang, Zong-Ben Xu. Universal Approximation of Extreme Learning Machine With Adaptive Growth of Hidden Nodes. Transactions on Neural Networks and Learning Systems IEEE, 23(2): 365-371 (2012).

DOI: 10.1109/tnnls.2011.2178124

[17] Carlos H. Morimoto, Marcio R.M. Mimica. Eye gaze tracking techniquesfor interactive applications [J]. Computer Vision and Image Understanding, 98: 4-24(2005).

DOI: 10.1016/j.cviu.2004.07.010

[18] Guojian Shao，Ming Che，Bingyi Zhang，Kunfang Cen, Wei Gao. A Novel Simple 2D Model of Eye Gaze Estimation[C]/: 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics（IHMSC 2010）. IEEE Computer Society Press, (10)：300-304(2010).

DOI: 10.1109/ihmsc.2010.81

[19] Zhiwei Zhu, Qiang Ji, Kristin P. Bennett. Nonlinear Eye Gaze Mapping Function Estimation via Support Vector Regression[C]/: Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006). IEEE Computer Society Press, 1: 3443-3448(2006).

DOI: 10.1109/icpr.2006.864