Download presentation

Presentation is loading. Please wait.

Published byHoward Burnett Modified about 1 year ago

1
Xiaoyong Ye Franz Alexander Van Horenbeke David Abbott

2
Index Introduction Background Hardware Software 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 Wearable Low-Cost Light and Confortable Moveable eye-camera Software Real-Time Accurate

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

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

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

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 Graylevel Pupil Background 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 * = Scene Position HomographyPupil Center

15
Solving for homographies 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 X’ = Hx

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 (x1, y1) (x2, y2)

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

19
Demo Link ntext=C25ea4ADOEgsToPDskIo6A6rLXR8eySvaEf82q 6h ntext=C25ea4ADOEgsToPDskIo6A6rLXR8eySvaEf82q 6h

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

21
Thank you!

Similar presentations

© 2016 SlidePlayer.com Inc.

All rights reserved.

Ads by Google