A face location and recognition system based on tangent distance
Multimodal interface for human-machine communication
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Attentiveness assessment in learning based on fuzzy logic analysis
Expert Systems with Applications: An International Journal
Robust real time eye tracking for computer interface for disabled people
Computer Methods and Programs in Biomedicine
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Algorithm optimizations for low-complexity eye tracking
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Eye-verifier using ternary template for reliable eye detection in facial color images
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Robust precise eye location by adaboost and SVM techniques
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
A robust and efficient algorithm for eye detection on gray intensity face
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
A hierarchical floatboost and MLP classifier for mobile phone embedded eye location system
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Detection of facial features on color face images
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part I
Evaluating the robustness of an appearance-based gaze estimation method for multimodal interfaces
Proceedings of the 15th ACM on International conference on multimodal interaction
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This paper presents a robust and precise scheme for face detection and precise facial feature location. Multiscale filters are use d to obtain the pre-attentive features of objects, based on which different models are investigated to locate the face and facial features such as eyes, nose and mouth. The structural model is used to characterize the geometric pattern of facial components. The texture and feature models are used to verify the face candidates detected before. Since the eyeballs are the only features that are salient and have strong invariant property, the distance between them will be used to normalize faces for recognition. Motivated from this, with the face detected and the structural information extracted, a precise eyes location algorithm is applied using contour and region information. It detects, with a sub-pixellic precision, the center and the radius of the eyeballs of a person's eyes. The detected result can be used as an accurate normalization of images, which reduces greatly the number of possible scales used during the face recognition process.