eye-tracking

How can I detect irises in a face with opencv? mpenkov Have a look at this forum thread . There's some source code there to get you started, but be careful about using it directly -- the original author seemed to have problems compiling it. Start with detecting circles - see cvHoughCircles - hint, eyes have a series of concentric circles. OpenCV has Face Detection module which uses Haar Cascade. You can use the same method to detect Iris. You collect some iris images and make it as positive set and non iris images as negative set. The use the Haar Training module to train it. Quick and dirty

The requirement is to define a rectangle around each eye in 3D space. There should be a way to track eyes using the Microsoft Kinect SDK. According to this The Face Tracking SDK uses the Kinect coordinate system to output its 3D tracking results. The origin is located at the camera’s optical center (sensor), Z axis is pointing towards a user, Y axis is pointing up. The measurement units are meters for translation and degrees for rotation angles. Adding ... Debug3DShape("OuterCornerOfRightEye", faceTrackFrame.Get3DShape() [FeaturePoint.OuterCornerOfRightEye]); Debug3DShape("InnerCornerRightEye"

I am now working on an eye tracking project. In this project I am tracking eyes in a webcam video (resolution if 640X480). I can locate and track the eye in every frame, but I need to locate the pupil. I read a lot of papers and most of them refer to Alan Yuille's deformable template method to extract and track the eye features. Can anyone help me with the code of this method in any languages (matlab/OpenCV)? I have tried with different thresholds, but due to the low resolution in the eye regions, it does not work very well. I will really appreciate any kind of help regarding finding pupil or

In my eye tracking project, the pupil center is jumping a lot and I don't see it as a fixed point. What should I do? My idea is comparing the pupil center and pupil in 2 frames with a threshold but it doesn't help the problem. Another point is camera noise. What should I do to reduce the noises? I used the starburst algorithm . Starburst : A hybrid algorithm for video-based eye tracking combining feature-based and model-based approaches. Eye trackers come with 2 types of noise/errors: variable and systematic error. Variable noise is basically the dispersion around the gazed target and the

I've been able to detect pupil and the eye corners accurately so far. You can see a few snaps i uploaded in my answer to my own question here: Performing stable eye corner detection Here's what i've done so far. I calibrated the gaze of the user by looking at TLCP, TRCP and BLCP where CP = calibration point; a screen point used for calibration B = bottom T = top L= left R = right gaze_width = TRCP.x - TLCP.x gaze_height = BLCP.y- TLCP.y And the corresponding gaze points i get by looking at those CPs are called GPs calculation of a gaze point GP: I subtract the TLGP's ordinates' values from the