Eye moving behaviors identification for gaze tracking interaction

Journal on Multimodal User Interfaces

Volumn 9, Issue 2, 2015, Pages 89-104

  Zhao, Qijie ^a   Yuan, Xinming ^a   Tu, Dawei ^a   Lu, Jianxia ^a  

^a SHANGHAI UNIVERSITY   (China)

Author keywords

Behavior identification; Detection algorithm; Eye moving behavior; Gaze tracking interaction

Indexed keywords

ASPECT RATIO; CURVE FITTING; HUMAN COMPUTER INTERACTION; TRACKING (POSITION);

BEHAVIOR IDENTIFICATIONS; DETECTION ALGORITHM; GAZE TRACKING; INTERACTION SYSTEMS; MEAN AND STANDARD DEVIATIONS; MOVING BEHAVIOR; RECOGNITION ALGORITHM;

EYE MOVEMENTS;

EID: 84940001622     PISSN: 17837677     EISSN: 17838738     Source Type: Journal    
DOI: 10.1007/s12193-014-0171-2     Document Type: Article

References (41)

1. Rauthmann JF, Seubert CT, Sachse P, Furtner MR (2012) Eyes as windows to the soul: gazing behavior is related to personality. J Res Pers 46:147–156
2. Courtemanche F, Aieur E, Dufresne A, Najjar M, Mpondo F (2011) Activity recognition using eye-gaze movements and traditional interactions. Interact. Comput. 23(2):202–213
3. Just MA, Carpenter PA (1976) Eye fixations and cognitive processes. Cogn. Psychol. 8(4):441–480
4. Rayner K (1998) Eye movements in reading and information processing: 20 years of research. Psychol Bull 124(3):372–422
5. Xu S, Zhang S, Geng HY (2011) Gaze-induced joint attention persists under high perceptual load and does not depend on awareness. Vis Res 51:2048–2056
6. Chen LY, Sun FC (1997) A cascade neural network for identifying fixation parameters of reading eye-movements. Acta Automat Sinica 123(14):489–495
7. Hutchinson TE, Jr White KP, Martin WN, Reichert KC, Frey LA (1989) Human–computer interaction using eye-gaze input. IEEE Trans Syst Man Cybern 19(6):1527–1534
8. Hansen DW, Qiang J (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
9. Jacob RJK (1991) The use of eye movements in human–computer interaction techniques: what you look at is what you get. ACM Trans Inform Syst 9(3):152–169
10. Zhai S (2003) What’s in the eyes for attentive input. Commun ACM 46(3):34–39
11. Li L, Pan G, Li SJ (2011) Eye-controlled painting system for disabled. J Electron 39(3A):163–167
12. Lee JY, Park HM, Lee SH, Kim TE, Choi JS (2011) Design and Implementation of an augmented reality system using gaze interaction. In: 2011 Proceedings of the IEEE international conference information science and applications, pp 1–8
13. Park KS, Lee KT (1996) Eye-controlled human/computer interface using the line-of-sight and the intentional blink. Comput Ind Eng 30(3):463–473
14. MacKenzie IS, Ashtiani B (2011) BlinkWrite: efficient text entry using eye blinks. Univ Access Inf Soc 10:69–80
15. Grauman K, Betke M, Gips J, Bradski GR (2001) Communication via eye blinks-detection and duration analysis in real time. In: 2001 Proceedings of IEEE Computer Society Conference computer vision and pattern recognition, vol 1, pp I-1010–I-1017
16. Lee WO, Lee EC, Park KR (2010) Blink detection robust to various facial poses. J Neurosci Methods 193:356–372
17. Bulling A, Ward JA, Gellersen H, Troster G (2011) Eye movement analysis for activity recognition using electrooculography. IEEE Trans Pattern Anal Mach Intell 33(4):741–753
18. Krupinski R, Mazurek P (2010) Sensitivity analysis of eye blinking detection using evolutionary approach. In: Proceedings of the international conference on signals and electronics systems, Gliwice, Poland, pp 81–84
19. Bulling A, Gellersen H (2010) Toward mobile eye-based human–computer interaction. IEEE Perv Comput 9(4):8–12
20. Noureddin B, Lawrence PD, Birch GE (2012) Online removal of eye movement and blink EEG artifacts using a high-speed eye tracker. IEEE Trans Biomed Eng 59(8):2103–2110
21. Reale MJ, Canavan S, Yin L-J (2011) A multi-gesture interaction system using a 3-D iris disk model for gaze estimation and an active appearance model for 3-D hand pointing. EEE Trans Multimed 13(3):474–486
22. Kurylyak Y, Lamonaca F, Mirabelli G, Boumbarov O, Panev S (2011) The infrared camera-based system to evaluate the human sleepiness. IEEE international workshop for medical measurements and applications (MeMeA), pp 253–256, May 2011
23. Komogortsev OV, Ryu YS, Koh DH, Gowda SM (2009) Instantaneous saccade driven eye gaze interaction. In: Proceedings of the international conference on advanced in computer entertainment technology. ACM, New York, pp 140–147
24. Nystrom M, Holmqvist K (2010) An adaptive algorithm for fixation, saccade, and glissade detection in eye tracking data. Behav Res Methods 42(1):188–204
25. Salvucci DD, Goldberg JH (2000) Identifying fixations and saccades in eye-tracking protocols. In: Proceedings of eye-tracking research and applications symposium, New York, pp 71–78
26. Komogortsev OV, Gobert DV, Jayarathna S, Koh DH, Gowda SM (2010) Standardization of automated analyses of oculomotor fixation and saccadic behaviors. IEEE Trans BME 57(11):2635–2645
27. Komogortsev OV, Karpov A (2013) Automated classification and scoring of smooth pursuit eye movements in the presence of fixations and saccades. Behav Res Methods 45(1):203–215
28. Panning A, Al-Hamadi A, Michaelis B (2011) A color based approach for eye blink detection in image sequences. IEEE international conference on signal and image processing applications, Kuala Lumpur, pp 40–45
29. Bacivarov I, Ionita M, Corcoran P (2008) Statistical models of appearance for eye tracking and eye-blink detection and measurement. IEEE Trans Consum Electron 54(3):1312–1320
30. Tan HC, Zhang Y-J (2006) Detecting eye blink states by tracking iris and eyelids. Pattern Recognit Lett 27(6):667–675
31. Zhao QJ, Tu DW, Huang ZH (2007) Image-processing based adaptive human–computer interaction system. Int J Assist Robot Mech 8(3):35–45
32. Zhao QJ, Yuan XM, Tu DW, Lu JX (2012) Multi-initialized states referred work parameters calibration for gaze tracking human robot interaction. Int J Adv Robot Syst 9(75):1–7
33. Lee J-Y, Park H-M, Lee S-H, Shin S-H, Kim T-E, Choi J-S (2014) Design and implementation of an augmented reality system using gaze interaction. Multimed Tools Appl. 68(2):265–280
34. Lin Y-T, Lin R-Y, Lin Y-C, Lee GC (2013) Real-time eye-gaze estimation using a low-resolution webcam. Multimed Tools Appl 65(3):543–568
35. Wu Y-L, Yeh C-T, Hung W-C, Tang C-Y (2014) Gaze direction estimation using support vector machine with active appearance model. Multimed Tools Appl 70(3):2037–2062
36. Valenti R, Sebe N, Gevers T (2012) Combining head pose and eye location information for gaze estimation. IEEE Trans Image Process 21(2):802–815
37. Larsson L, Nyström M, Stridh M (2013) Detection of saccades and post-saccadic oscillations in the presence of smooth pursuit. IEEE Trans Biomed Eng 60(9):2484–2493
38. Niemenlehto P-H, Juhola M (2007) Application of the cell averaging constant false alarm rate technique to saccade detection in electro-oculography. in: Proceedings of the 29th annual international conference of the IEEE EMBS Cité internationale, Lyon, France, August 23–26, pp 586–589
39. Keegan J, Burke E, Condron J (2009) An electrooculogram-based binary saccade sequence classification (BSSC) technique for augmentative communication and control. In: 31st Annual international conference of the IEEE EMBS Minneapolis, Minnesota, USA, September 2–6, pp 2604–2607
40. Koh DH, Gowda SM, Komogortsev OV (2009) Input Evaluation of an eye-gaze-guided interface: Kalman filter vs. velocity threshold eye movement identification. In: Proceedings of ACM EICS’09, Pittsburgh, Pennsylvania, USA, July 15–17, pp 197–202
41. Komogortsev OV, Khan J (2007) Kalman filtering in the design of eye-gaze-guided computer interfaces. Human–computer interaction, part III, HCII 2007. LNCS 4552, pp 679–689