Harshita Karamchandani Placement, Masters Project and Travels…..

Outline  Placement Project Work  Background  Deliverables  Program outline  Masters  Usability requirements  Current Issues  Plan  Literature  A little more about my placement  Workplace  Pictures!

Background  WIL placement at BRI in Toronto  Development of an eye tracking system for an iPad  Uses for eye tracking Hands-free use of technology Access pathway for individuals with disabilities Augmentative and Alternative Communication (AAC) apps for tablets  Commercial Systems Tobii, Dynavox $ $40,000  Currently no system available for tablets  Advantages of an eye tracking system on a tablet Low cost Portable Accessible

Deliverables  Programmed in C using the OpenCV library  PC version  Uses various image processing functions  Erosion  Canny edge detection  Hough circle transformation  Template Matching  Simple Logitech Quickcam  iPad version

Program Outline  Face tracking  User selects eye region  User selects iris template  Tracking begins  Calibration process – 4 points  Kalman filtering  Choice selection

Usability Requirements  tracking accuracy and reliability……………..  robustness to light conditions and head movements…………………………………….  non-intrusiveness……………………………..  real-time implementation……………………...  fast calibration…………………………………  cost-effectiveness…………………………….. (Toricelli et al 2008)

Current Issues  Only works with 2x2 grid  Need to improve accuracy (at least 4x4 grid)  Account for head tilt  Added functionality  e.g. detect blinking

Plan  Develop eye tracking program  Windows 7 Acer Tablet PC  VGA video recording – 640x480  C++ programming  Windows 7 SDK  Image processing beyond OpenCV  Enhance eye tracking  Obtain SBREC Ethics approval  User evaluation

Ideas and Literature  Artificial Neural Networks (ANN) –  Images of eyes are captured for every gaze position for training  2000 images/position (Baluja and Pomerleau 1994)  Large data  Computationally expensive  User specific  Eye tracking with large head motion  Requires external hardware,  IR light, multiple cameras (Yoo and Chung 2004)  Stereo Cameras (Matsumoto 1999)  Ultrasonic sensors (Sugioka et al 1996)

Continued..  OpenGazer (Nel 2009)  Uses optical flow  Trained Gaussian process  Source code available  Different morphological operators (Wang et al 2004)  Thresholding  Opening  Canny edge detection  Edge selection criteria – longest vertical edges  Ellipse fitting  More calibration points

Workplace  Holland Bloorview Kids Rehabilitation Hospital  Prism Lab  Infinity Lab  Supervisors – Tom Chau, Leslie Mumford, David Hobbs  Colleagues

My trip in pictures

References  Novita 2013, Augmentative and Alternative Communication (AAC), viewed on 16 April 2013  Tobii 2013, What is eye tracking?, viewed on 16 April 2013  Tobii 2013, Tobii C12 - AAC device for independence, viewed on 16 April 2013  Dynavox 2013, Dynavox EyeMax, viewed on 16 April 2013  Kumar, N. 2006, Reducing the Cost of Eye Tracking Systems, viewed on 16 April 2013  Holland, C. et al 2012, Eye tracking on un-modified common tablets: challenges and solutions, Texas State University, viewed on 16 April 2013  Ciesla, M et al 2012, Eye pupil location using webcam, Jagiellonian University, viewed on 16 April 2013

Thank You. Questions?