Gaze Tracking for Multimodal Human-Computer Interaction
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 4 - Volume 4
A hybrid classifier for precise and robust eye detection
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
An Effective Method for Eye Detection Based on Texture Information
ICCIT '07 Proceedings of the 2007 International Conference on Convergence Information Technology
A Robust Eye Detection and Tracking Technique Using Gabor Filters
IIH-MSP '07 Proceedings of the Third International Conference on International Information Hiding and Multimedia Signal Processing (IIH-MSP 2007) - Volume 01
Robust depth camera based eye localization for human-machine interactions
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part I
A complete and fully automated face verification system on mobile devices
Pattern Recognition
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A novel fast eye localization algorithm based on pixel differences is presented, which is suitable for face recognition system on mobile device. It is based on the fact that eyeball is dark and round. A binary eye map is obtained by choosing those pixels darker than surrounding; then it is filtered by a rank order filter; connected regions in the eye map are then labeled by their geometric centers; best suitable eyeball pair is selected based on a set of geometric constraints. If no eyeball pair is detected, the algorithm is repeated iteratively until one pair is found. The algorithm is fast since it converts the gray level image to a binary eye map at the beginning. The algorithm is tested on our own face database, which consists of 4095 images of size 250×200. Detection rate is 93.04% when the tolerance is 0.7 times of eyeball width.