Eye localization for face matching: is it always useful and under what conditions?
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Efficient Measurement of the Eye Blinking by Using Decision Function for Intelligent Vehicles
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
Efficient Facial Feature Detection Using Entropy and SVM
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Multimedia Tools and Applications
Robust Facial Feature Location on Gray Intensity Face
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Eye localization in low and standard definition content with application to face matching
Computer Vision and Image Understanding
Precise eye detection on frontal view face image
Proceedings of the First International Conference on Internet Multimedia Computing and Service
Adjusted pixel features for robust facial component classification
Image and Vision Computing
Proceedings of the 2007 conference on Human interface: Part I
Automatic eye detection using intensity filtering and K-means clustering
Pattern Recognition Letters
Rotation-Invariant facial feature detection using gabor wavelet and entropy
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
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The problem of eye detection in face images is very important for a large number of applications ranging from face recognition to gaze tracking. In this paper we propose a new algorithm for eyes detection that uses iris geometrical information for determining in the whole image the region candidate to contain an eye, and then the symmetry for selecting the couple of eyes. The novelty of this work is that the algorithm works on complex images without constraints on the background, skin color segmentation and so on. Different experiments, carried out on images of subjects with different eyes colors, some of them wearing glasses, demonstrate the effectiveness and robustness of the proposed algorithm.