Nothing Special   »   [go: up one dir, main page]

CN103677270A - Human-computer interaction method based on eye movement tracking - Google Patents

Human-computer interaction method based on eye movement tracking Download PDF

Info

Publication number
CN103677270A
CN103677270A CN201310684342.5A CN201310684342A CN103677270A CN 103677270 A CN103677270 A CN 103677270A CN 201310684342 A CN201310684342 A CN 201310684342A CN 103677270 A CN103677270 A CN 103677270A
Authority
CN
China
Prior art keywords
time period
image
infrared light
frame
pupil
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201310684342.5A
Other languages
Chinese (zh)
Other versions
CN103677270B (en
Inventor
程洪
姬艳丽
刘雅齐
杨路
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
University of Electronic Science and Technology of China
Original Assignee
University of Electronic Science and Technology of China
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by University of Electronic Science and Technology of China filed Critical University of Electronic Science and Technology of China
Priority to CN201310684342.5A priority Critical patent/CN103677270B/en
Publication of CN103677270A publication Critical patent/CN103677270A/en
Application granted granted Critical
Publication of CN103677270B publication Critical patent/CN103677270B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Image Analysis (AREA)
  • Image Processing (AREA)

Abstract

一种基于眼动跟踪的人机交互方法,包括五组朝向计算机操作者的红外光源和一台内置红外滤光片的相机,其中四组红外光源设置在计算机显示屏的四个角落,另一组红外光源设置在相机镜头周围;相机设置在计算机显示屏下方并连接到计算机,相机镜头朝向操作者面部;包括标定的步骤,捕获和检测图像的步骤,判断眨眼的步骤,判断凝视点变化的步骤和输出交互指令的步骤。本发明的有益效果在于:1.标定简单,移植性好;2.通过对暗瞳进行检测,增加了适用用户;3.通过平滑处理,克服了人眼生理颤动带来的干扰;4.操作者头部在较大范围内移动系统精确度仍然较高;5.使用单个相机,成本相对较低;6.处理速度较快,能够满足实时的人机交互。

Figure 201310684342

A human-computer interaction method based on eye tracking, including five groups of infrared light sources facing the computer operator and a camera with built-in infrared filter, four groups of infrared light sources are set at the four corners of the computer display screen, and the other A group of infrared light sources is arranged around the camera lens; the camera is arranged under the computer display screen and connected to the computer, and the camera lens faces the operator's face; including the steps of calibration, the steps of capturing and detecting images, the steps of judging blinking, and judging the changes of gaze points steps and steps for outputting interactive instructions. The beneficial effects of the present invention are as follows: 1. Simple calibration and good transplantability; 2. Increase the number of applicable users by detecting the dark pupil; 3. Overcome the interference caused by the physiological vibration of human eyes through smoothing processing; 4. Operate The accuracy of the head moving system is still high in a large range; 5. Using a single camera, the cost is relatively low; 6. The processing speed is fast, which can meet the real-time human-computer interaction.

Figure 201310684342

Description

A kind of man-machine interaction method based on eye-tracking
Technical field
The present invention relates to computer vision control technology field, is specifically a kind of man-machine interaction method based on eye-tracking.
Background technology
In man-machine interaction, eye-tracking is being played the part of a very important role, and eye-tracking can be taken as the interface that connects people and computing equipment, and compared with mouse and keyboard, eye-tracking offers alternately a kind of more naturally mode of people and carries out man-machine interaction.The method that estimation eye movement realizes direction also has a variety of: reflection method, potential electronics skin, and contact lenses etc., these methods are classified as again the method for intrusive mood or non-intrusion type, the method of non-intrusion type more has superiority, more comfortable because the method for non-intrusion type uses.But in eye-tracking research, still also have many open questions.Its precision problem the most generally, the restriction of head movement, robustness, and the easness of demarcating.
Summary of the invention
The object of this invention is to provide a kind of man-machine interaction method based on eye-tracking, this method makes operator's head still can keep higher degree of accuracy when moving in a big way.
The technical scheme that realizes the object of the invention is as follows: a kind of man-machine interaction method based on eye-tracking, the camera that comprises five groups of infrared light supplies towards computer operation person and a built-in infrared optical filter, wherein four groups of infrared light supplies are arranged on four corners of computer display, and another group infrared light supply is arranged on around camera lens; Camera is arranged on computer display below and is connected to computing machine, and camera lens is towards operator's face; Comprise
The step of demarcating, comprises
101: face-image when computing machine is caught operator and watched attentively the infrared light supply in the arbitrary corner of display screen by camera, image is carried out to eye detection, spot detection and pupil detection, obtain pupil center, camera lens corresponding spot center and spot center corresponding to this group infrared light supply of infrared light supply around, calculate corresponding calibration coefficient;
102: according to aforesaid operations, corresponding calibration coefficient when calculating operation person watches the infrared light supply in other corner of display screen attentively respectively; Catch the step with detected image, comprise
201: computing machine continues to catch with frame frequency F the face-image that operator watches display screen by camera;
202: each two field picture is carried out to eye detection, spot detection, pupil detection and fixation point and estimate;
The step that judgement is blinked, comprises
301: the time period T that any time t is starting point is take in judgement lin the L frame consecutive image of catching, L=T l* F; If there is and only has a time period T in L two field picture kin the continuous image of K frame of catching hot spot do not detected, T k<T l, be set as operator and blink once; If there are two time period T in L two field picture k1and T k2in K1 and the continuous image of K2 frame of catching separately hot spot do not detected, T k1<T l, T k2<T land T k1+ T k2<T l, and other image detection between two time periods consecutive image of catching is separately to hot spot, is set as operator and blinks twice;
The step that judgement fixation point changes:
401: establish fixation point in that two field picture that any time t the catches horizontal ordinate g on screen xordinate g y;
402: the time period T that moment t is starting point is take in judgement rin R frame consecutive image, R=T r* F, if the fixation point in R two field picture all rests on horizontal ordinate g xordinate g yfor the center of circle, in the circle that radius is r, be set as fixation point and stop;
403: the time period T that moment t is starting point is take in judgement din D frame consecutive image, D=T d* F, if the horizontal ordinate of the fixation point in D two field picture and ordinate dullness reduce, and total decrease surpasses respectively horizontal ordinate variable quantity X and ordinate variable quantity Y, is set as fixation point and moves to upper left side;
404: the time period T that moment t is starting point is take in judgement uin U frame consecutive image, U=T u* F, if the horizontal ordinate of the fixation point in U two field picture and ordinate monotone increasing, and total recruitment surpasses respectively horizontal ordinate variable quantity X and ordinate variable quantity Y, is set as fixation point and moves to lower right;
The step of output interactive instruction, comprises
501: as operator blinks once, export the instruction that left mouse button is clicked;
502: as operator blinks twice, export the instruction that left mouse button is double-clicked;
503: as fixation point stops, export the instruction that right mouse button is clicked;
504: as fixation point moves to upper left side, export the instruction that mouse roller scrolls up;
505: as fixation point moves to lower right, export the instruction that mouse roller rolls downwards.
Further,
Described eye detection comprises: the face-image of catching is carried out to binaryzation, obtain black white image; Black white image is carried out to profile and search, determine that the minimum rectangle frame of the profile border parcel finding is human eye rectangle frame;
Described spot detection comprises: according to human eye rectangle frame intercepting face-image, obtain human eye rectangle frame image; Human eye rectangle frame image is carried out to binaryzation, obtain binary image; Binary image is removed to noise; Search five white portions of area maximum in the binary image of removing after noise as five groups of hot spots that infrared light supply is corresponding; The barycenter of determining five hot spots is spot center; Determine the one-to-one relationship of five hot spots and five groups of infrared light supplies;
Described pupil detection comprises: take respectively the mean value of horizontal ordinate of five spot center and initialization abscissa value and the initialization ordinate value that the mean value of ordinate is pupil center; Set pupil rectangle frame, take the initialization abscissa value of pupil center and the center that initialization ordinate value is pupil rectangle frame; Pupil rectangle frame is carried out to vertical and horizontal projecting integral, obtain only comprising in pupil rectangle frame the little rectangle frame of pupil; From little rectangle frame, search pupil boundary and center thereof;
Described fixation point is estimated to comprise: according to five spot center and calibration coefficient, calculate respectively spot center that the infrared light supply in four corners of display screen is corresponding four virtual projection points on eyes cornea; According to pupil center and four virtual projection points, and the length of display screen and width, estimate fixation point.
Further, described time period T l, time period T r, time period T dwith time period T ube at the same time section.
Further, described frame frequency F was 15 frame/seconds; Described time period T l, time period T r, time period T dwith time period T uduration be 2 seconds; Described time period T k, time period T k1with time period T k2all be greater than 0.5 second; Described radius r is
Figure BDA0000437760480000031
described horizontal ordinate variable quantity X and ordinate variable quantity Y are respectively
Figure BDA0000437760480000032
with
Figure BDA0000437760480000033
wherein w is display screen width, and h is display screen height.
Beneficial effect of the present invention is, 1, demarcate simply, and transplantability is good; 2, by dark pupil is detected, avoided different human eyes, the bad user of bright pupil effect, has increased applicable user; 3,, by smoothing processing, overcome the interference that the vibration of people's physiology of eye brings; 4, operator's head mobile system degree of accuracy in is in a big way still higher; 5, use single camera, compare with using a plurality of cameras, cost is relatively low; 6, processing speed is very fast, and system responses is quicker, in time, can meet real-time man-machine interaction.
Accompanying drawing explanation
Fig. 1 is the schematic diagram of infrared light supply, camera and the face-image of catching, human eye rectangle frame, human eye rectangle frame image;
Fig. 2 is the schematic diagram that in human eye rectangle frame image, hot spot distributes;
Fig. 3, Fig. 4 and Fig. 5 are the principle schematic that fixation point is estimated;
Fig. 6 is the schematic diagram that fixation point stops;
Fig. 7 is the schematic diagram that fixation point moves to upper left side;
Fig. 8 is the schematic diagram that fixation point moves to lower right.
Embodiment
As shown in Figure 1, a kind of man-machine interaction method based on eye-tracking, the camera that comprises five groups of infrared light supplies towards computer operation person and a built-in infrared optical filter, wherein four groups of infrared light supply LED1, LED2, LED3 and LED4 are arranged on four corners of computer display, and another group infrared light supply LED5 is arranged on around camera lens 3; Camera is arranged on computer display below and is connected to computing machine, and camera lens 3 is towards operator's face.
The method of eye detection is: infrared light supply reflects and produces the pul speck of admiring in human eye, in the grey face-image 1 of catching with the camera of optical filter, the pul being positioned on eye cornea is admired speck for the brightest, the position of searching human eye can change into searches the admire position of speck of the brightest pul, the position of searching left eye or right eye can change into search abscissa value minimum or the admire position of speck of maximum pul.Pass through binaryzation, obtain pul and admire speck region for white, all the other positions are the black white image of black, this black white image is carried out to profile and search (border of searching monochrome pixels), and the minimum rectangle frame of definite profile border parcel finding is human eye rectangle frame 2 as the region at human eye place.
The method of spot detection is:
Step1: use human eye rectangle frame 2 intercepting face-images, obtain human eye rectangle frame image 2 ';
Step2: human eye rectangle frame image is cut apart by setting threshold, obtained a binary image;
Step3: process binary image and morphological operation to remove noise;
In binary image, infrared lamp reflection produces the hot spot that five brightness values are 1 (pul admire speck), and different hot spots forms different white portions.But, due to the existence of noise, and the external environment illumination condition of different brightness, also may produce brightness value and be 1 other white portion.In addition, improper due to selected threshold, the single hot spot that infrared lamp reflection produces also may be divided into a plurality of fritters, form polylith white portion, by first corroding again expansion form, learn operation (< < study Opencv (Chinese edition) > >) and eliminate the interference that noise that part area is less brings here.
Step4: group areas;
After morphological operation, now in binary image, be only left the relatively large white portion of some areas.We find, noise place white portion area is less than the white portion area at hot spot place, therefore only need in binary image, find out five white portions that white portion is hot spot place of area maximum.By the cvFindContours function of increasing income in the Opencv of computer vision storehouse, search the profile of every white portion in binary image, recycling cvContourArea function calculates respectively the area that every white portion comprises (pixel and).Each region area is sorted according to descending, and the region of choosing five area maximums after sequence is spot area.
Step5: the center of calculating every spot area;
By calculating above, five hot spots have all been detected, and obtain the barycenter of each spot area as spot center.
Step6: the one-to-one relationship of determining five hot spots and five groups of infrared light supplies;
Relative position relation by five groups of infrared light supplies can be known, ordinate value maximum be LED5, abscissa value minimum be LED1 and LED3, abscissa value maximum be LED2 and LED4, and the ordinate value of LED1 is less than the ordinate value of LED3, the ordinate value of LED2 is less than the ordinate value of LED4.According to this relation, compare the coordinate figure of the spot center of five hot spots, can determine the one-to-one relationship of five hot spots and five groups of infrared light supplies.As Fig. 2, in human eye rectangle frame image, hot spot LED1 ', LED2 ', LED3 ', LED4 ' and LED5 ' are corresponding one by one with infrared light supply LED1, LED2, LED3, LED4 and LED5.
The method of pupil detection is:
Step1: initialization pupil region center;
Before obtained the center of five hot spots.In fact, the position of five hot spots and pupil is separated by very near, therefore we use respectively the horizontal ordinate of five spot center and ordinate mean value as the initialization coordinate figure of pupil center, using this centre coordinate as the center of pupil rectangle frame, and the large I of this rectangle frame is set (general length and width are 160*120 pixel) according to actual conditions.
Step2: iterative projection integration
Above-mentioned pupil rectangle frame is carried out to vertical and horizontal projecting integral, because it is dark that want in other regions of the relative around eyes of pupil, by vertical and horizontal projection integration, each row pixel value of every a line and minimum coordinate are all found out, by the projecting integral of iteration, we can access the little rectangle frame (length and width are 80*60 pixel) that only comprises pupil in pupil rectangle frame.By Opencv binaryzation function cvThreshold, profile is searched function cvFindContours again, and Hough transformation is searched circular function cvHoughCircles, can find pupil boundary and center thereof.
The method of demarcating is:
Face-image when computing machine is caught operator and watched attentively the infrared light supply in the arbitrary corner of display screen by camera, image is carried out to eye detection, spot detection and pupil detection, obtain pupil center, camera lens corresponding spot center and spot center corresponding to this group infrared light supply of infrared light supply LED5 around, calculate corresponding calibration coefficient.
Suppose that operator watches LED1 attentively, computing machine is caught its face-image by camera.By eye detection, spot detection and pupil detection, obtain the u of pupil center p, camera lens spot center u corresponding to infrared light supply LED5 around cthe spot center u corresponding with infrared light supply LED1 r1.Because that operator watches attentively is LED1, the corresponding virtual projection point of hot spot that LED1 produces should with the center superposition of pupil, by this constraint, we can calculate this coefficient in order to lower equation:
&alpha; 1 = d ( u p , u c ) d ( u r 1 , u c )
In above formula, α 1the calibration coefficient of operator while watching LED1 attentively, d (x 1, x 2) be an x 1, x 2between Euclidean distance.When user watches respectively LED2, LED3 and LED4 attentively, according to said method, can calculate corresponding calibration coefficient α 2, α 3and α 4.
The method that fixation point is estimated is:
By the unchangeability of double ratio in projection process, estimate the position of eye gaze point.In Fig. 3, supposing has a tangent virtual section X with it at anterior corneal surface, some v 1, v 2, v 3, v 4on this virtual section, be four groups of infrared light supply LED1 of corner screen, LED2, LED3 and LED4 are at the subpoint in this virtual section, and we are referred to as virtual projection point these four points, and their projection centre is cornea ball centre J.Suppose that these virtual projection points are roughly coplanar, the quadrilateral that these four virtual point are linked to be is so exactly the projection of screen display, and these virtual projections Dian He P of pupil center is projected into five some u on camera image plane T v1, u v2, u v3, u v4and u p, Z is camera optical axis center.Thereby, from screen display to the plane of delineation, there are two projection conversions here, if this virtual projection point is roughly coplanar, fixation point g point coordinate just can be estimated to obtain by calculating with Projective invariance.
Specific as follows: as shown in Figure 4, u v1, u v2, u v3, u v4the virtual projection point on cornea, u pbe pupil center in image, c is u v1, u v2, u v3, u v4the point of crossing of the quadrilateral summit line forming.Wherein, u v1=u c+ α 1(u r1-u c), u v2=u c+ α 2(u r2-u c), u v3=u c+ α 3(u r3-u c), u v4=u c+ α 4(u r4-u c), u in formula ccamera lens spot center corresponding to infrared light supply LED5 around, u r1the spot center that infrared light supply LED1 is corresponding, u r2the spot center that infrared light supply LED2 is corresponding, u r3the spot center that infrared light supply LED3 is corresponding, u r4it is the spot center that infrared light supply LED4 is corresponding.
U m1straight line and u for end point a and c place v1, u v2the intersection point of place straight line, u m2for end point a and u pthe straight line at place and u v1, u v2the intersection point of place straight line, u m3for end point b and u pthe straight line at place and u v2, u v4the intersection point of place straight line, u m4straight line and u for end point b and c point place v2, u v4the intersection point of place straight line.
Suppose u vi = ( x i v , y i v ) ( i = 1,2,3,4 ) , u mi = ( x i m , y i m ) ( i = 1,2,3,4 ) , Straight line
Figure BDA0000437760480000062
the double ratio of upper four points is:
CR image x = ( x 1 v y 1 m - x 1 m y 1 v ) ( x 2 m y 2 v - x 2 v y 2 m ) ( x 1 v y 2 m - x 2 m y 1 v ) ( x 2 m y 2 v - x 2 v y 1 m )
Same, the double ratio of screen display, as shown in Figure 5, adopts following equation to calculate:
CR image x = ( w - w 2 ) x ^ g ( w - x ^ g ) w 2 = x ^ g w - x ^ g
W is the width of screen display,
Figure BDA0000437760480000065
it is the x coordinate of estimation point g.
According to the cross ratio invariability character of projector space, those double ratios equate.So
x ^ g = w &CenterDot; CR image x 1 + CR image x
The y coordinate that g is ordered can be estimated equally in this way, and image double ratio is:
CR image y = ( x 2 v y 3 m - x 3 m y 2 v ) ( x 4 m y 3 v - x 3 v y 4 m ) ( x 2 v y 4 m - x 4 m y 2 v ) ( x 3 m y 3 v - x 3 v y 3 m )
The double ratio of screen display is:
CR image y = ( h - h 2 ) y ^ g ( h - y ^ g ) h 2 = y ^ g h - y ^ g
H is the height of screen display,
Figure BDA0000437760480000069
it is the y coordinate of estimation point g.And
y ^ g = h &CenterDot; CR image y 1 + CR image y
The implementing procedure of the man-machine interaction method based on eye-tracking is: the step of first carry out demarcating, and by human eye detection, spot detection, pupil detection, and user watches respectively four corners of screen attentively and demarcates, and obtains calibration coefficient α 1, α 2, α 3, α 4.After demarcation completes, carry out and catch and detect, be specially: computing machine continues to catch with frame frequency F the face-image that operator watches display screen by camera; Each two field picture is carried out to eye detection, spot detection, pupil detection and fixation point to be estimated.The method that eye detection, spot detection, pupil detection and fixation point are estimated is as aforementioned.According to the result detecting and fixation point is estimated, the judgement that blink judgement and fixation point change.
The method of judgement nictation is: the time period T that any time t is starting point is take in judgement lin the L frame consecutive image of catching, L=T l* F; If there is and only has a time period T in L two field picture kin the continuous image of K frame of catching hot spot do not detected, T k<T l, be set as operator and blink once; If there are two time period T in L two field picture k1and T k2in K1 and the continuous image of K2 frame of catching separately hot spot do not detected, T k1<T l, T k2<T land T k1+ T k2<T l, and other image detection between two time periods consecutive image of catching is separately to hot spot, is set as operator and blinks twice.
The method that judgement fixation point changes is: as shown in Figure 6, establish fixation point in that two field picture that any time t the catches horizontal ordinate g on screen xordinate g y; The time period T that moment t is starting point is take in judgement rin R frame consecutive image, R=T r* F, if the fixation point in R two field picture all rests on horizontal ordinate g xordinate g yfor the center of circle, in the circle that radius is r, be set as fixation point and stop.As shown in Figure 7, the time period T that moment t is starting point is take in judgement din D frame consecutive image, D=T d* F, if the horizontal ordinate of the fixation point in D two field picture and ordinate dullness reduce, and total decrease surpasses respectively horizontal ordinate variable quantity X and ordinate variable quantity Y, is set as fixation point and moves to upper left side.As shown in Figure 8, the time period T that moment t is starting point is take in judgement uin U frame consecutive image, U=T u* F, if the horizontal ordinate of the fixation point in U two field picture and ordinate monotone increasing, and total recruitment surpasses respectively horizontal ordinate variable quantity X and ordinate variable quantity Y, is set as fixation point and moves to lower right.
The method of output interactive instruction is: according to judged result, as operator blinks once, export the instruction that left mouse button is clicked; As operator blinks twice, export the instruction that left mouse button is double-clicked; As fixation point stops, export the instruction that right mouse button is clicked; As fixation point moves to upper left side, export the instruction that mouse roller scrolls up; As fixation point moves to lower right, export the instruction that mouse roller rolls downwards.
In actual judgement, for simplifying the operation, can take out one group of continuous image since any time, this group image is blinked successively and judged and fixation point variation judgement.That is to say, the frame number of the consecutive image that blink judgement and fixation point change to judge is identical, i.e. L=R=D=U, and the time period of catching this framing is also identical, i.e. time period T l, time period T r, time period T dwith time period T ube at the same time section.If meet nictation or fixation point in this group image, change one of five kinds of situations of judgement, operational order corresponding to instant output just, usings the next frame image of current frame image simultaneously as the start frame of next group consecutive image; If all do not met, do not export any instruction, again get one group of continuous image and judge next time, the start frame that the second frame of above one group of consecutive image is this group consecutive image.
For example, computing machine is caught after operator's face-image with the frame frequency of 15 frame/seconds continuously by camera, carry out eye detection, spot detection, pupil detection and fixation point and estimate, from any frame, start to get one group of 30 continuous two field picture afterwards, the duration of this 30 two field picture is 2 seconds.Suppose in this 30 two field picture, the 3rd frame to the 10 frames all do not detect hot spot, and the time that respective operations person closes one's eyes is greater than 0.5 second, and other image all detects hot spot, can regard as operator and blink once, correspondingly export the instruction that left mouse button is clicked.Suppose in this 30 two field picture, the 3rd frame to the 10 frames and the 20th frame to the 27 frames all do not detect hot spot, and other image all detects hot spot, can regard as operator and blink twice, correspondingly export the instruction that left mouse button is double-clicked.Suppose that, in this 30 two field picture, the fixation point of the first frame is horizontal ordinate g xordinate g y, the fixation point of other all frames is with horizontal ordinate g xordinate g yfor the center of circle, within the circle that radius is r, can regard as fixation point and stop, correspondingly export the instruction that right mouse button is clicked.Radius r can be set as 1/20th of display screen width w.Suppose that, in this 30 two field picture, the horizontal ordinate of fixation point and ordinate dullness reduce, and the total decrease of horizontal ordinate surpasses
Figure BDA0000437760480000081
the total decrease of ordinate surpasses
Figure BDA0000437760480000082
can regard as fixation point and move to upper left side, correspondingly export the instruction that mouse roller scrolls up.Suppose in this 30 two field picture, the horizontal ordinate of fixation point and ordinate are dull to be increased, and the total increase of horizontal ordinate surpasses the total increase of ordinate surpasses
Figure BDA0000437760480000084
can regard as fixation point and move to lower right, correspondingly export the instruction that mouse roller rolls downwards.Here h is the height of display screen.According to the instruction of output, just can carry out some shirtsleeve operations, such as controlling ppt, webpage rolling etc., thereby reach the object of man-machine interaction.

Claims (5)

1.一种基于眼动跟踪的人机交互方法,包括五组朝向计算机操作者的红外光源和一台内置红外滤光片的相机,其中四组红外光源(LED1、LED2、LED3、LED4)设置在计算机显示屏的四个角落,另一组红外光源(LED5)设置在相机镜头周围;相机设置在计算机显示屏下方并连接到计算机,相机镜头朝向操作者面部;其特征在于,包括1. A human-computer interaction method based on eye tracking, including five groups of infrared light sources facing the computer operator and a camera with a built-in infrared filter, of which four groups of infrared light sources (LED1, LED2, LED3, LED4) are set At the four corners of the computer display screen, another group of infrared light sources (LED5) are arranged around the camera lens; the camera is arranged under the computer display screen and connected to the computer, and the camera lens faces the operator's face; it is characterized in that, including 标定的步骤,包括Calibration steps, including 101:计算机通过相机捕获操作者注视显示屏任一角落的红外光源时的面部图像,对图像进行眼睛检测、光斑检测和瞳孔检测,得到瞳孔中心、相机镜头周围的红外光源(LED5)对应的光斑中心和该组红外光源对应的光斑中心,计算对应的标定系数;101: The computer uses the camera to capture the face image of the operator looking at the infrared light source at any corner of the display screen, and performs eye detection, spot detection and pupil detection on the image to obtain the pupil center and the corresponding light spot of the infrared light source (LED5) around the camera lens Center and the spot center corresponding to the group of infrared light sources, and calculate the corresponding calibration coefficient; 102:依照上述操作,分别计算操作者注视显示屏其它角落的红外光源时对应的标定系数;102: According to the above operations, respectively calculate the corresponding calibration coefficients when the operator looks at the infrared light sources in other corners of the display screen; 捕获和检测图像的步骤,包括Steps to capture and detect images, including 201:计算机通过相机以帧频F持续捕获操作者观看显示屏的面部图像;201: The computer continuously captures the facial image of the operator watching the display screen with the frame rate F through the camera; 202:对每一帧图像进行眼睛检测、光斑检测、瞳孔检测和凝视点估计;202: Perform eye detection, spot detection, pupil detection, and gaze point estimation on each frame of image; 判断眨眼的步骤,包括Steps for judging blinking, including 301:判断以任意时刻t为起始点的时间段TL中捕获的L帧连续图像,L=TL*F;如果L帧图像中有且仅有一个时间段TK中捕获的K帧连续的图像未检测到光斑,TK<TL,设定为操作者眨眼一次;如果L帧图像中有两个时间段TK1和TK2中各自捕获的K1和K2帧连续的图像未检测到光斑,TK1<TL、TK2<TL且TK1+TK2<TL,并且两个时间段各自捕获的连续图像之间的其它图像检测到光斑,设定为操作者眨眼两次;301: Determine the L frames of continuous images captured in the time period T L starting at any time t, L=T L *F; if there is and only one K frame captured in the time period T K in the L frame images is continuous No light spot is detected in the image of T K < T L , it is set that the operator blinks once; if there are two consecutive images of K1 and K2 captured in two time periods T K1 and T K2 respectively in the L frame image, no light spot is detected The light spot, T K1 <T L , T K2 <T L and T K1 +T K2 <T L , and the light spot is detected in other images between the consecutive images captured in the two time periods respectively, is set so that the operator blinks twice ; 判断凝视点变化的步骤:Steps to judge gaze point change: 401:设任意时刻t捕获的那一帧图像中的凝视点在屏幕上的横坐标gx纵坐标gy401: Set the abscissa g x ordinate g y of the gaze point on the screen in the frame of image captured at any time t; 402:判断以时刻t为起始点的时间段TR中的R帧连续图像,R=TR*F,如果R帧图像中的凝视点均停留在以横坐标gx纵坐标gy为圆心,半径为r的圆内,设定为凝视点停留;402: Judging the R frame continuous images in the time period T R starting from time t, R=T R *F, if the gaze points in the R frame images all stay at the abscissa g x ordinate g y as the center of the circle , in a circle with a radius of r, set to stay at the gaze point; 403:判断以时刻t为起始点的时间段TD中的D帧连续图像,D=TD*F,如果D帧图像中的凝视点的横坐标和纵坐标单调减小,且总的减小量分别超过横坐标变化量X和纵坐标变化量Y,设定为凝视点向左上方移动;403: Determine the continuous images of D frames in the time period T D with time t as the starting point, D=T D *F, if the abscissa and ordinate of the gaze point in the D frame image decrease monotonously, and the total decrease A small amount exceeds the change amount X of the abscissa and the change amount Y of the ordinate respectively, and the gaze point is set to move to the upper left; 404:判断以时刻t为起始点的时间段TU中的U帧连续图像,U=TU*F,如果U帧图像中的凝视点的横坐标和纵坐标单调增加,且总的增加量分别超过横坐标变化量X和纵坐标变化量Y,设定为凝视点向右下方移动;404: Judging the U frame continuous images in the time period T U with time t as the starting point, U=T U *F, if the abscissa and ordinate of the gaze point in the U frame image increase monotonously, and the total increase If the amount of change X on the abscissa and the amount Y on the ordinate are respectively exceeded, the gaze point is set to move to the lower right; 输出交互指令的步骤,包括Steps for outputting interactive commands, including 501:如操作者眨眼一次,则输出鼠标左键单击的指令;501: If the operator blinks once, then output an instruction to click the left button of the mouse; 502:如操作者眨眼两次,则输出鼠标左键双击的指令;502: If the operator blinks twice, then output the instruction of double-clicking the left mouse button; 503:如凝视点停留,则输出鼠标右键单击的指令;503: If the gaze point stays, then output the command of the right mouse click; 504:如凝视点向左上方移动,则输出鼠标滚轮向上滚动的指令;504: If the gaze point moves to the upper left, output an instruction to scroll up the mouse wheel; 505:如凝视点向右下方移动,则输出鼠标滚轮向下滚动的指令。505: If the gaze point moves to the lower right, then output an instruction to scroll down with the mouse wheel. 2.如权利要求1所述的人机交互方法,其特征在于,2. the human-computer interaction method as claimed in claim 1, is characterized in that, 所述眼睛检测包括:对捕获的面部图像进行二值化,得到黑白图像;对黑白图像进行轮廓查找,确定查找到的轮廓边界包裹的最小矩形框为人眼矩形框;The eye detection includes: binarizing the captured facial image to obtain a black-and-white image; performing contour search on the black-and-white image, and determining that the smallest rectangular frame wrapped by the contour boundary found is the human eye rectangular frame; 所述光斑检测包括:根据人眼矩形框截取面部图像,得到人眼矩形框图像;对人眼矩形框图像进行二值化,得到二值化图像;对二值化图像去除噪声;查找去除噪声后的二值化图像中面积最大的五块白色区域作为五组红外光源对应的光斑;确定五个光斑的质心为光斑中心;确定五个光斑与五组红外光源的一一对应关系;The spot detection includes: intercepting the facial image according to the rectangular frame of human eyes to obtain a rectangular frame image of human eyes; binarizing the rectangular frame image of human eyes to obtain a binarized image; removing noise from the binarized image; searching and removing noise The five white areas with the largest area in the final binary image are used as the corresponding light spots of five groups of infrared light sources; the centroids of five light spots are determined to be the center of light spots; the one-to-one correspondence between five light spots and five groups of infrared light sources is determined; 所述瞳孔检测包括:分别以五个光斑中心的横坐标的平均值和纵坐标的平均值为瞳孔中心的初始化横坐标值和初始化纵坐标值;设定瞳孔矩形框,以瞳孔中心的初始化横坐标值和初始化纵坐标值为瞳孔矩形框的中心;对瞳孔矩形框进行垂直与水平投影积分,得到瞳孔矩形框中只包含瞳孔的小矩形框;从小矩形框中查找瞳孔边界及其中心;The pupil detection includes: taking the average value of the abscissa and the average value of the ordinate of the five spot centers as the initial abscissa value and the initialization ordinate value of the pupil center respectively; The coordinate value and the initial ordinate value are the center of the pupil rectangle; vertical and horizontal projection integrals are carried out to the pupil rectangle to obtain a small rectangle that only contains the pupil in the pupil rectangle; find the pupil boundary and its center from the small rectangle; 所述凝视点估计包括:根据五个光斑中心以及标定系数,分别计算显示屏四个角落的红外光源对应的光斑中心在眼睛角膜上的四个虚拟投影点;根据瞳孔中心和四个虚拟投影点,以及显示屏的长度和宽度,估计凝视点。The gaze point estimation includes: according to the five facula centers and the calibration coefficients, respectively calculating four virtual projection points of the corresponding facula centers of the infrared light sources at the four corners of the display screen on the cornea of the eye; according to the center of the pupil and the four virtual projection points , and the length and width of the display to estimate the gaze point. 3.如权利要求1所述的人机交互方法,其特征在于,所述时间段TL,时间段TR,时间段TD和时间段TU是同一个时间段。3. The human-computer interaction method according to claim 1, wherein the time period T L , time period T R , time period T D and time period T U are the same time period. 4.如权利要求2所述的人机交互方法,其特征在于,所述时间段TL,时间段TR,时间段TD和时间段TU是同一个时间段。4. The human-computer interaction method according to claim 2, wherein the time period T L , the time period TR , the time period T D and the time period T U are the same time period. 5.如权利要求1至4所述的任意一种人机交互方法,其特征在于,所述帧频F为15帧/秒;所述时间段TL,时间段TR,时间段TD和时间段TU的时长均为2秒;所述时间段TK,时间段TK1和时间段TK2均大于0.5秒;所述半径r为
Figure FDA0000437760470000021
所述横坐标变化量X和纵坐标变化量Y分别为
Figure FDA0000437760470000022
Figure FDA0000437760470000023
其中w为显示屏宽度,h为显示屏高度。
5. The human-computer interaction method according to any one of claims 1 to 4, wherein the frame frequency F is 15 frames/second; the time period T L , time period T R , and time period T D and the duration of the time period T U are both 2 seconds; the time period T K , the time period T K1 and the time period T K2 are all greater than 0.5 seconds; the radius r is
Figure FDA0000437760470000021
The abscissa variation X and the ordinate variation Y are respectively
Figure FDA0000437760470000022
and
Figure FDA0000437760470000023
Where w is the width of the display screen and h is the height of the display screen.
CN201310684342.5A 2013-12-13 2013-12-13 A kind of man-machine interaction method based on eye-tracking Active CN103677270B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201310684342.5A CN103677270B (en) 2013-12-13 2013-12-13 A kind of man-machine interaction method based on eye-tracking

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201310684342.5A CN103677270B (en) 2013-12-13 2013-12-13 A kind of man-machine interaction method based on eye-tracking

Publications (2)

Publication Number Publication Date
CN103677270A true CN103677270A (en) 2014-03-26
CN103677270B CN103677270B (en) 2016-08-17

Family

ID=50315078

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201310684342.5A Active CN103677270B (en) 2013-12-13 2013-12-13 A kind of man-machine interaction method based on eye-tracking

Country Status (1)

Country Link
CN (1) CN103677270B (en)

Cited By (19)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104751467A (en) * 2015-04-01 2015-07-01 电子科技大学 Gaze point estimation method based on dynamic cross ratio and system thereof
CN105078404A (en) * 2015-09-02 2015-11-25 北京津发科技股份有限公司 Fully automatic eye movement tracking distance measuring calibration instrument based on laser algorithm and use method of calibration instrument
CN105260027A (en) * 2015-11-04 2016-01-20 上海斐讯数据通信技术有限公司 Man-machine interactive system and method
CN106200961A (en) * 2016-07-10 2016-12-07 上海青橙实业有限公司 Mobile terminal, wearable device and input method
CN106265006A (en) * 2016-07-29 2017-01-04 维沃移动通信有限公司 The antidote of a kind of dominant eye and mobile terminal
CN106662911A (en) * 2014-04-29 2017-05-10 惠普发展公司,有限责任合伙企业 Gaze detector using reference frames in media
CN107024991A (en) * 2017-04-13 2017-08-08 长沙职业技术学院 A kind of glasses system based on Internet of Things
WO2017152679A1 (en) * 2016-03-09 2017-09-14 北京七鑫易维信息技术有限公司 Eyeball tracking device matchable for intelligent terminal
CN107450729A (en) * 2017-08-10 2017-12-08 上海木爷机器人技术有限公司 Robot interactive method and device
CN107818310A (en) * 2017-11-03 2018-03-20 电子科技大学 A kind of driver attention's detection method based on sight
CN107992196A (en) * 2017-12-08 2018-05-04 天津大学 A kind of man-machine interactive system of blink
CN108139663A (en) * 2016-03-03 2018-06-08 萨利赫·伯克·伊尔汉 smile mirror
CN108596106A (en) * 2018-04-26 2018-09-28 京东方科技集团股份有限公司 Visual fatigue recognition methods and its device, VR equipment based on VR equipment
WO2018184246A1 (en) * 2017-04-08 2018-10-11 闲客智能(深圳)科技有限公司 Eye movement identification method and device
CN109146851A (en) * 2018-07-30 2019-01-04 南京慧视医疗科技有限公司 A kind of nystagmus signal characteristic abstraction and tracing algorithm diagnosing vestibular system disease
CN110115026A (en) * 2016-12-19 2019-08-09 三星电子株式会社 The method and system of 360 degree of contents is generated on rectangular projection in an electronic
CN111399627A (en) * 2020-03-09 2020-07-10 宁波视睿迪光电有限公司 Energy-saving method and system for 3D display device
CN112099615A (en) * 2019-06-17 2020-12-18 北京七鑫易维科技有限公司 Gaze information determination method and device, eyeball tracking equipment and storage medium
WO2024041488A1 (en) * 2022-08-22 2024-02-29 北京七鑫易维信息技术有限公司 Electronic device

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101866215A (en) * 2010-04-20 2010-10-20 复旦大学 Human-computer interaction device and method using gaze tracking in video surveillance
CN102043952A (en) * 2010-12-31 2011-05-04 山东大学 Eye-gaze tracking method based on double light sources
US20110182472A1 (en) * 2008-07-08 2011-07-28 Dan Witzner Hansen Eye gaze tracking
CN102193621A (en) * 2010-03-17 2011-09-21 三星电子(中国)研发中心 Vision-based interactive electronic equipment control system and control method thereof
US20130332160A1 (en) * 2012-06-12 2013-12-12 John G. Posa Smart phone with self-training, lip-reading and eye-tracking capabilities

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110182472A1 (en) * 2008-07-08 2011-07-28 Dan Witzner Hansen Eye gaze tracking
CN102193621A (en) * 2010-03-17 2011-09-21 三星电子(中国)研发中心 Vision-based interactive electronic equipment control system and control method thereof
CN101866215A (en) * 2010-04-20 2010-10-20 复旦大学 Human-computer interaction device and method using gaze tracking in video surveillance
CN102043952A (en) * 2010-12-31 2011-05-04 山东大学 Eye-gaze tracking method based on double light sources
US20130332160A1 (en) * 2012-06-12 2013-12-12 John G. Posa Smart phone with self-training, lip-reading and eye-tracking capabilities

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
Z ZHU: "eye and gaze tracking for interactive graphic display", 《MACHINE VISION & APPLICATIONS》, vol. 15, no. 3, 31 December 2002 (2002-12-31), pages 139 - 148, XP002719847, DOI: doi:10.1007/s00138-004-0139-4 *
王文成 等: "一种基于区域投影的人眼精确定位方法", 《光电子.激光》, vol. 22, no. 4, 30 April 2011 (2011-04-30), pages 618 - 622 *

Cited By (26)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106662911A (en) * 2014-04-29 2017-05-10 惠普发展公司,有限责任合伙企业 Gaze detector using reference frames in media
CN106662911B (en) * 2014-04-29 2020-08-11 惠普发展公司,有限责任合伙企业 Gaze detector using reference frames in media
CN104751467A (en) * 2015-04-01 2015-07-01 电子科技大学 Gaze point estimation method based on dynamic cross ratio and system thereof
CN104751467B (en) * 2015-04-01 2017-11-24 电子科技大学 It is a kind of that the point estimation method and its system are stared based on dynamic double ratio
CN105078404A (en) * 2015-09-02 2015-11-25 北京津发科技股份有限公司 Fully automatic eye movement tracking distance measuring calibration instrument based on laser algorithm and use method of calibration instrument
CN105260027A (en) * 2015-11-04 2016-01-20 上海斐讯数据通信技术有限公司 Man-machine interactive system and method
CN108139663A (en) * 2016-03-03 2018-06-08 萨利赫·伯克·伊尔汉 smile mirror
WO2017152679A1 (en) * 2016-03-09 2017-09-14 北京七鑫易维信息技术有限公司 Eyeball tracking device matchable for intelligent terminal
CN106200961A (en) * 2016-07-10 2016-12-07 上海青橙实业有限公司 Mobile terminal, wearable device and input method
CN106265006A (en) * 2016-07-29 2017-01-04 维沃移动通信有限公司 The antidote of a kind of dominant eye and mobile terminal
CN106265006B (en) * 2016-07-29 2019-05-17 维沃移动通信有限公司 A kind of control method and mobile terminal of the apparatus for correcting of dominant eye
CN110115026A (en) * 2016-12-19 2019-08-09 三星电子株式会社 The method and system of 360 degree of contents is generated on rectangular projection in an electronic
WO2018184246A1 (en) * 2017-04-08 2018-10-11 闲客智能(深圳)科技有限公司 Eye movement identification method and device
CN107024991A (en) * 2017-04-13 2017-08-08 长沙职业技术学院 A kind of glasses system based on Internet of Things
CN107450729B (en) * 2017-08-10 2019-09-10 上海木木机器人技术有限公司 Robot interactive method and device
CN107450729A (en) * 2017-08-10 2017-12-08 上海木爷机器人技术有限公司 Robot interactive method and device
CN107818310A (en) * 2017-11-03 2018-03-20 电子科技大学 A kind of driver attention's detection method based on sight
CN107818310B (en) * 2017-11-03 2021-08-06 电子科技大学 A line-of-sight-based driver's attention detection method
CN107992196A (en) * 2017-12-08 2018-05-04 天津大学 A kind of man-machine interactive system of blink
CN108596106A (en) * 2018-04-26 2018-09-28 京东方科技集团股份有限公司 Visual fatigue recognition methods and its device, VR equipment based on VR equipment
CN108596106B (en) * 2018-04-26 2023-12-05 京东方科技集团股份有限公司 Visual fatigue recognition method and device based on VR equipment and VR equipment
CN109146851A (en) * 2018-07-30 2019-01-04 南京慧视医疗科技有限公司 A kind of nystagmus signal characteristic abstraction and tracing algorithm diagnosing vestibular system disease
CN112099615A (en) * 2019-06-17 2020-12-18 北京七鑫易维科技有限公司 Gaze information determination method and device, eyeball tracking equipment and storage medium
CN112099615B (en) * 2019-06-17 2024-02-09 北京七鑫易维科技有限公司 Gaze information determination method, gaze information determination device, eyeball tracking device, and storage medium
CN111399627A (en) * 2020-03-09 2020-07-10 宁波视睿迪光电有限公司 Energy-saving method and system for 3D display device
WO2024041488A1 (en) * 2022-08-22 2024-02-29 北京七鑫易维信息技术有限公司 Electronic device

Also Published As

Publication number Publication date
CN103677270B (en) 2016-08-17

Similar Documents

Publication Publication Date Title
CN103677270A (en) Human-computer interaction method based on eye movement tracking
TWI489317B (en) Method and system for operating electric apparatus
Jain et al. Real-time upper-body human pose estimation using a depth camera
TWI479430B (en) Gesture identification with natural images
Cho et al. Gaze Detection by Wearable Eye‐Tracking and NIR LED‐Based Head‐Tracking Device Based on SVR
CN103353935A (en) 3D dynamic gesture identification method for intelligent home system
CN102831404A (en) Method and system for detecting gestures
CN108197534A (en) A kind of head part&#39;s attitude detecting method, electronic equipment and storage medium
CN105138965A (en) Near-to-eye sight tracking method and system thereof
CN107687818B (en) Three-dimensional measurement method and three-dimensional measurement device
CN105912126B (en) A kind of gesture motion is mapped to the adaptive adjusting gain method at interface
Song et al. Detection of movements of head and mouth to provide computer access for disabled
Utaminingrum et al. Eye movement and blink detection for selecting menu on-screen display using probability analysis based on facial landmark
CN108551699A (en) Eye control intelligent lamp and control method thereof
CN113160260B (en) Head-eye double-channel intelligent man-machine interaction system and operation method
Galab et al. Adaptive real time eye-blink detection system
Yamamoto et al. Algorithm optimizations for low-complexity eye tracking
Xu et al. Real time detection of eye corners and iris center from images acquired by usual camera
Taaban et al. Eye tracking based mobile application
Lin et al. Identification of eye movements from non-frontal face images for eye-controlled systems
Khilari Iris tracking and blink detection for human-computer interaction using a low resolution webcam
Hao et al. Vision-based interface: Using face and eye blinking tracking with camera
CN107256089B (en) Gesture recognition method by natural image
Lemahieu et al. Low cost eye tracking for human-machine interfacing
Mohammadi et al. Robust pose-invariant eye gaze estimation using geometrical features of iris and pupil images

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant