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A Review of Various State of Art Eye Gaze Estimation Techniques

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Advances in Computational Intelligence and Communication Technology

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1086))

Abstract

Eye gaze tracking is a technique to track an individual’s focus of attention. This paper provides a review on eye gaze trackers (EGTs) classified on the basis of intrusive and non-intrusive techniques. According to the numerous applications of EGTs in human–computer interface, neuroscience, psychology and in advertising and marketing, this paper brings forward a deep insight into recent and future advancements in the field of eye gaze tracking. Finally, comparative analyses on various EGT techniques along with its applications in various fields are discussed.

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References

  1. S. Chandra, G. Sharma, S. Malhotra, D. Jha, A.P. Mittal, Eye tracking based human computer interaction: applications and their uses. in Man and Machine Interfacing (MAMI), 2015 International Conference on (IEEE, 2015 Dec), (pp. 1–5)

    Google Scholar 

  2. S. Wibirama, H.A. Nugroho, K. Hamamoto, Evaluating 3D gaze tracking in virtual space: a computer graphics approach. Entertain. Comput. 21, 11–17 (2017)

    Google Scholar 

  3. T.O. Zander, M. Gaertner, C. Kothe, R. Vilimek, Combining eye gaze input with a brain–computer interface for touchless human–computer interaction. Intl. J. Hum.-Comput. Interact. 27(1), 38–51 (2010)

    Google Scholar 

  4. X. Zhu, D. Ramanan, Face detection, pose estimation, and landmark localization in the wild. in Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on (IEEE, 2012 June), pp. 2879–2886

    Google Scholar 

  5. B. Noris, J.B. Keller, A. Billard, A wearable gaze tracking system for children in unconstrained environments. Comput. Vis. Image Underst. 115(4), 476–486 (2011)

    Google Scholar 

  6. K.W. Choe, R. Blake, S.H. Lee, Pupil size dynamics during fixation impact the accuracy and precision of video-based gaze estimation. Vision. Res. 118, 48–59 (2016)

    Google Scholar 

  7. A. Bulling, D. Roggen, G. Tröster, Wearable EOG goggles: seamless sensing and context-awareness in everyday environments. J. Ambient. Intell. Smart Environ. 1(2), 157–171 (2009)

    Google Scholar 

  8. D.A. Robinson, A method of measuring eye movement using a scieral search coil in a magnetic field. IEEE Trans. Bio-med. Electron. 10(4), 137–145 (1963)

    Google Scholar 

  9. R.S. Remmel, An inexpensive eye movement monitor using the scleral search coil technique. IEEE Trans. Biomed. Eng. 4, 388–390 (1984)

    Google Scholar 

  10. C. Anderson, A.M. Chang, J.P. Sullivan, J.M. Ronda, C.A. Czeisler, Assessment of drowsiness based on ocular parameters detected by infrared reflectance oculography. J. Clin. Sleep Med. 9(09), 907–920 (2013)

    Google Scholar 

  11. E. Skodras, V.G. Kanas, N. Fakotakis, On visual gaze tracking based on a single low cost camera. Sig. Process. Image Commun. 36, 29–42 (2015)

    Google Scholar 

  12. J. Turner, A. Bulling, H. Gellersen, Extending the visual field of a head-mounted eye tracker for pervasive eye-based interaction. in Proceedings of the Symposium on Eye Tracking Research and Applications (ACM, 2012 March), pp. 269–272

    Google Scholar 

  13. Y. Sugano, Y. Matsushita, Y. Sato, H. Koike, An incremental learning method for unconstrained gaze estimation. in European Conference on Computer Vision (Springer, Berlin, Heidelberg, 2008 Oct), pp. 656–667

    Google Scholar 

  14. R. Valenti, N. Sebe, T. Gevers, Combining head pose and eye location information for gaze estimation. IEEE Trans. Image Process. 21(2), 802–815 (2012)

    MathSciNet  MATH  Google Scholar 

  15. Z. Zhu, Q. Ji, K.P. Bennett, Nonlinear eye gaze mapping function estimation via support vector regression. in Pattern Recognition, 2006. ICPR 2006. 18th International Conference on, vol. 1 (IEEE, 2006 Aug), pp. 1132–1135

    Google Scholar 

  16. T. Nagamatsu, R. Sugano, Y. Iwamoto, J. Kamahara, N. Tanaka, User-calibration-free gaze estimation method using a binocular 3D eye model. IEICE Trans. Inf. Syst. 94(9), 1817–1829 (2011)

    Google Scholar 

  17. E. Wood, T. Baltrušaitis, L.P. Morency, P. Robinson, A. Bulling, A 3D morphable eye region model for gaze estimation. in European Conference on Computer Vision (Springer, Cham, 2016 Oct), pp. 297–313

    Google Scholar 

  18. J. Chen, Q. Ji, A probabilistic approach to online eye gaze tracking without explicit personal calibration. IEEE Trans. Image Process. 24(3), 1076–1086 (2015)

    MathSciNet  MATH  Google Scholar 

  19. I.F. Ince, J.W. Kim, A 2D eye gaze estimation system with low-resolution webcam images. EURASIP J. Adv. Signal Process. 2011(1), 40 (2011)

    Google Scholar 

  20. X. Fan, K. Zheng, Y. Lin, S. Wang, Combining local appearance and holistic view: dual-source deep neural networks for human pose estimation. in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2015), pp. 1347–1355

    Google Scholar 

  21. F. Lu, Y. Sugano, T. Okabe, Y. Sato, Adaptive linear regression for appearance-based gaze estimation. IEEE Trans. Pattern Anal. Mach. Intell. 36(10), 2033–2046 (2014)

    Google Scholar 

  22. Y. Sugano, Y. Matsushita, Y. Sato, Appearance-based gaze estimation using visual saliency. IEEE Trans. Pattern Anal. Mach. Intell. 35(2), 329–341 (2013)

    Google Scholar 

  23. F. Lu, T. Okabe, Y. Sugano, Y. Sato, Learning gaze biases with head motion for head pose-free gaze estimation. Image Vis. Comput. 32(3), 169–179 (2014)

    Google Scholar 

  24. F. Vicente, Z. Huang, X. Xiong, F. De la Torre, W. Zhang, D. Levi, Driver gaze tracking and eyes off the road detection system. IEEE Trans. Intell. Transp. Syst. 16(4), 2014–2027 (2015)

    Google Scholar 

  25. X. Zhang, Y. Sugano, M. Fritz, A. Bulling, It’s written all over your face: full-face appearance-based gaze estimation. in 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (IEEE, 2017 July), pp. 2299–2308

    Google Scholar 

  26. Y.M. Cheung, Q. Peng, Eye gaze tracking with a web camera in a desktop environment. IEEE Trans. Hum.-Mach. Syst. 45(4), 419–430 (2015)

    Google Scholar 

  27. R.A. Naqvi, M. Arsalan, G. Batchuluun, H.S. Yoon, K.R. Park, Deep learning-based gaze detection system for automobile drivers using a NIR camera sensor. Sensors 18(2), 456 (2018)

    Google Scholar 

  28. R.D.O.J. Dos Santos, J.H.C. de Oliveira, J.B. Rocha, J.D.M.E. Giraldi, Eye tracking in neuromarketing: a research agenda for marketing studies. Int. J. Psychol. Stud. 7(1), 32 (2015)

    Google Scholar 

  29. M. Miyamoto, Y. Shimada, M.A.K.I. Yasuhiro, K. Shibasato, Development of eye gaze software for children with physical disabilities. in Advanced Informatics: Concepts, Theory And Application (ICAICTA), 2016 International Conference On (IEEE, 2016 Aug), pp. 1–6

    Google Scholar 

  30. P. Biswas, J. DV, Eye gaze controlled MFD for military aviation. in 23rd International Conference on Intelligent User Interfaces (ACM, 2018 March), pp. 79–89

    Google Scholar 

  31. P.M. Corcoran, F. Nanu, S. Petrescu, P. Bigioi. Real-time eye gaze tracking for gaming design and consumer electronics systems. IEEE Trans. Consum. Electr. 58(2) (2012)

    Google Scholar 

  32. C.C. Wang, J.C. Hung, S.N. Chen, H.P. Chang, Tracking students’ visual attention on manga-based interactive e-book while reading: an eye-movement approach. Multimed. Tools Appl. 1–22 (2018)

    Google Scholar 

  33. R.N. Khushaba, C. Wise, S. Kodagoda, J. Louviere, B.E. Kahn, C. Townsend, Consumer neuroscience: Assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eye tracking. Expert Syst. Appl. 40(9), 3803–3812 (2013)

    Google Scholar 

  34. A. Zaraki, D. Mazzei, M. Giuliani, D. De Rossi, Designing and evaluating a social gaze-control system for a humanoid robot. IEEE Trans. Hum.-Mach. Syst. 44(2), 157–168 (2014)

    Google Scholar 

  35. B. Pires, M. Hwangbo, M. Devyver, T. Kanade, Visible-spectrum gaze tracking for sports. in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (2013), pp. 1005–1010

    Google Scholar 

  36. V. Cantoni, M. Musci, N. Nugrahaningsih, M. Porta, Gaze-based biometrics: an introduction to forensic applications. Pattern Recogn. Lett. 113, 54–57 (2018)

    Google Scholar 

  37. S. Wyder, F. Hennings, S. Pezold, J. Hrbacek, P.C. Cattin, With gaze tracking toward noninvasive eye cancer treatment. IEEE Trans. Biomed. Eng. 63(9), 1914–1924 (2016)

    Google Scholar 

  38. J. Mundel, P. Huddleston, B. Behe, L. Sage, C. Latona, An eye tracking study of minimally branded products: hedonism and branding as predictors of purchase intentions. J. Prod. & Brand. Manag. 27(2), 146–157 (2018)

    Google Scholar 

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Correspondence to Jaiteg Singh .

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Modi, N., Singh, J. (2021). A Review of Various State of Art Eye Gaze Estimation Techniques. In: Gao, XZ., Tiwari, S., Trivedi, M., Mishra, K. (eds) Advances in Computational Intelligence and Communication Technology. Advances in Intelligent Systems and Computing, vol 1086. Springer, Singapore. https://doi.org/10.1007/978-981-15-1275-9_41

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