Eye characteristic detection and gaze direction calculation in gaze tracking system
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1 24 9 Vol. 24 No. 9 Cont rol an d Decision Sep : (2009) ,,,, (, ) :., ;, ;., ;.. : ; ; ; : TP : A Eye characteristic detection and gaze direction calculation in gaze tracking system C H I J i an2nan, Z H A N G Chuang, H U T ao, YA N Yan2t ao, L I U Yang ( School of Information and Engineering, University of Science and Technology Beijing, Beijing , China. Correspondent : CHI Jian2nan, E2mail : com) Abstract : A gaze tracking method is proposed based on active inf rared source system. In the eye feature detection stage, p rojection method is applied to locate face. Symmetry axis of face is detected, potential region of pupil is found based on the knowledge about facial structure, and human eyes features can be precise segmented. In the eye2gaze modeling stage, a model with nonlinear polynomial to map the gaze parameters to gaze point under the circumstances of static head is set up. Then the deviation of gaze caused by different head position is compensated by GRNN neural network, so that nonlinear mapping f unction can be extended to any head position. So gaze can be estimated accurately under head movement. The experiment result s and the applications in interactive graphical system show the effectiveness of this method. Key words : Gaze tracking ; Gaze parameter ; Nonlinear polynomial ; Generalized regression neural network 1.. (VO G). VO G 2, ( )., ( IR),,., : ; : : ( ) ; 863 (2007AA01Z160) ; ( ). : (1967 ),,,,, ; (1982 ),,,,.
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3 9 : 1347,, [18 ],. Sobel,., A [col ], 0. IM G, : For each row For each pair of non2zero (pixels x1, y1 ) and ( x2, y2 ) in t he current row, Do { Distance = x1 - x2 ; Axis = ( x1, x2 ) / 2 ; if ( distance > low t hr and distance < up_t hr) A [axis ] = A [axis ] + 1. } A [col ], col. Step3.,. Step4.,.,,.,,.,.,. 4) Hough. Hough,,.,., Sobel, Hough ,, , :1),, ;2),, ;3), ;4),. [15 ], g = [ x y l p x p y ]. : ( x, y), ;, ; l, ; ( p x, p y ),. g
4 GRNN. GRNN, 3.,,, GRNN. 4. Q, R. 3, ;,,, GRNN ;, ,,, : X = a x + b y + c x y, (2) Y = d x + e y + f x 2. (3) : (2), (3) ; a, b, c, d, e, f ; x y 2., 2.,, GRNN GRNN GRNN,,,,. GRNN 4 :. 4 GRNN., 4 IW,, L W,..,,,,. ( min, max ),, 1,2,, 1,2,, E = 1 n n [ Y i ( X i) - Y i ] 2. (4) i = 1,. (4),.,., GRNN,..,,.,,.
5 9 : 1349, g 4 ( X, Y) = f ( g). (5),. 8,, 9,.., GRNN, 0. 8, GRNN,,., ( ),, ,, 45. 5,, x., , , 70, 20.,. 2,.,. 6 x x x y y x y
6 ,.,,,,., GRNN,,.. ( References) [ 1 ] Technologies L C. Eyegaze systems [ EB/ OL ]. http :/ / www. eyegaze. com, [ 2 ] Eyetech digital systems [ EB/ OL ]. http : / / www. eyetechds. com, [ 3 ] Tobii Technology, Danderyd, Sweden [ EB/ OL ]. http : / / www. tobii. se [ 4 ] Applied science laboratories[ Online ]. http :/ / www. a2s2 l. com, [ 5 ] Ebisawa Y, Satoh S. Effectiveness of pupil area detection technique using two light sources and image difference method[ C]. Proc of the 15th Annual Int Conf of the IEEE Engineer in Medicine and Biology Society. San Diego, 1993 : [ 6 ] Ebisawa Y. Improved video2based eye2gaze detection method[j ]. IEEE Trans on Instrument, 1998, 47 (2) : [ 7 ] Morimoto C H, Koons D, Amir A, et al. Pupil detection and tracking using multiple light sources [ J ]. Image Vision Computer, 2000, 18 (4) : [ 8 ] Morimoto C, Flickner M. Real2time multiple face detection using active illumination [ C ]. Proc 4th IEEE Int Conf on Automatic Face and Gesture Recognition. Grenoble, 2000 : [ 9 ] Haro A, Flickner M, Essa I. Detecting and tracking eyes by using their physiological properties, dynamics and appearance [ C ]. Proc IEEE CV PR South Carolina, 2000 : [ 10 ] Ji Q, Yang X. Real time visual cues extraction for monitoring driver vigilance[ C]. Proc Int Workshop on Computer Vision Systems. Vancouver, 2001 : [ 11 ] Zhu Z W, Fujjmura K, Qiang J. Real2time eye detection and tracking under various light conditions [ C ]. Proc of ACM SIGCH I Symposium on Eye Tracking Research and Applications. New Orleans, [12 ] Zhu Z W, Qiang J. Robust real2time eye detection and tracking under variable lighting conditions and various face orientations [ J ]. Computer Vision and Image Understanding, 2005, 38 (1) : [13 ] Qing J. Real2time eye, gaze and face pose tracking for monitoring driver vigilance [ J ]. Real2Time Imaging, 2002, 8 (5) : [ 14 ] Zhu Z, Ji Q. Eye and gaze tracking for interactive graphic display[j ]. Machine Vision Application, 2004, 15 (3) : [ 15 ] Kim S C. Non2intrusive eye gaze tracking under natural head movements[ C]. Proc of the 26th Annual Int Conf of the IEEE. San Francisco, 2004 : [ 16 ] Qing J, Zhu Z W. Real2time nonintrusive monitoring and prediction of driver fatigue [ J ]. IEEE Trans on Vehicular, 2004, 53 (4) : [17 ] Shih S W, Liu J. A novel approach to 3D gaze tracking using stereo cameras[j ]. IEEE Trans of Systems, Man and Cybernetics, 2004, 34 (1) : [ 18 ] Christian Hoff mann, Thao Dang, Christoph Stiller. Vehicle detection fusing 2D visual features [ C ]. IEEE Intelligent Vehicles Symposium University of Parma. Parma, 2004, 7 : ( 1344 ) [7 ]. Kalman [ M ]. :, ( Fu M Y. Kalman filtering theory and It s application on navigation system[ M ]. Beijing : Science Press, ) [ 8 ] J amshaid A, Fang J C. SINS/ ANS/ GPS integration using federated Kalman filter based on optimized information2sharing Coefficient s [ C ]. AIAA. New York : NASA, 2005 : [9 ],,. [J ]., 2006, 4 (8) : ( Sun L X, Mu R J, Cui N G. Theoretical and simulation study on general model of federated filtering with multi2sensor information f usion [ J ]. Aero Weaponry, 2006, 4 (8) : ) [10 ],. [J ]., 2007, 1 (1) : ( Mu R J, Cui N G. Hierarchical multistage and rescale information f usion method for multisensor integrated navigation[ J ]. Aerospace Shanghai, 2007, 1 ( 1) : )
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