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!