Presents new image-based eye gaze tracking algorithms and applies them to biometric identification and activity recognition tasks.
An Improved Algorithm for Eye Corner Detection
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abstract
In this paper, a modified algorithm for the detection of nasal and temporal eye corners is presented. The algorithm is a modification of the Santos and Proenka Method. In the first step, we detect the face and the eyes using classifiers based on Haar-like features. We then segment out the sclera, from the detected eye region. From the segmented sclera, we segment out an approximate eyelid contour. Eye corner candidates are obtained using Harris and Stephens corner detector. We introduce a post-pruning of the Eye corner candidates to locate the eye corners, finally. The algorithm has been tested on Yale, JAFFE databases as well as our created database.
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Image based Eye Gaze Tracking and its Applications
Presents new image-based eye gaze tracking algorithms and applies them to biometric identification and activity recognition tasks.