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Xiaoyong Ye Franz Alexander Van Horenbeke David Abbott

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Presentation on theme: "Xiaoyong Ye Franz Alexander Van Horenbeke David Abbott"— Presentation transcript:

1 Xiaoyong Ye Franz Alexander Van Horenbeke David Abbott
Wearable Eye Tracker Xiaoyong Ye Franz  Alexander Van Horenbeke David Abbott

2 Index Introduction Background Hardware Software Experimental Results
System Design Algorithm Pupil Localization Ellipse Fitting Calibration Homographic Mapping Experimental Results Future Work

3 Introduction A complete system able to track the user’s eye and map the position of their pupil with the area at which they are looking at in the scene in front of them

4 Background Wearable Eye-Tracking information
Who has done previous work What they have used Recent Methods used with eye tracker

5 Objectives Hardware Software Wearable Real-Time Low-Cost Accurate
Light and Confortable Moveable eye-camera

6 Hardware Head-Mounted Gear Two Cameras: Scene Camera Eye Camera

7 Hardware Scene Camera Eye Camera
Captures the scene in front of the user Captures the eye With 5 DOF with respect to the head Fixed to the head

8 System Design Eye Image Scene Image Yes Calibration Done?
Pupil Localization No Ellipse Fitting Marker Detection Calculate Homography Ellipse Center Mapping

9 Pupil Localization Automatic Threshold (Modified Otsu’s Method)
Image Morphology(Dilation, Erosion) Connected Components Analysis(Find Pupil) Pupil Center Estimation

10 Histogram of an Eye Image
Background Pupil Graylevel Threshold

11 Pupil Localization Threshold Erosion Connect Components
Pupil Detection Dilation Fill holes

12 Ellipse Fitting 1. Updating the pupil Center
2. Need 5 points for Fitting Ellipse model 3. RANSAC to deal with noisy points

13 Ellipse Fitting RANSAC method Edge Image Starburst Algorithm
Feature Points RANSAC Ellipse Fitting

14 Calibration = * Relationship between Ellipse center to Scene Image
Homography Pupil Center Scene Position

15 Solving for homographies
X’ = Hx 8 degrees of freedom in 3 x 3 matrix H, so at least n = 8 pairs of points are sufficient to determine it Set up a system of linear equations: Ah = 0 where vector of unknowns h = [a,b,c,d,e,f,g,h]T Need at least 8 eqs, but the more the better… Solve for h. solve using least-squares

16 calibration method 1. Look at Scene Marker and Press corresponding number on keyboard, 2. Each marker press 2 to 3 times. 3. Randomly select 8 pairs of points to calculate Homography.(Repeatly) 3. Choose the best Homography matrix.

17 Mapping (x2, y2) (x1, y1)

18 Experimental Results Frame rate 25/second Accurate Pupil Ellipse
Mapping error is low( 13 pixels in 640*480 image)

19 Demo Link

20 Future Work Hardware Software Lighter cameras Scene camera position
Use corneal refletion Try different mapping techniques

21 Thank you!

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