Projection based method for segmentation of human face and its evaluation
Pattern Recognition Letters
Computer Vision and Image Understanding - Special issue on eye detection and tracking
A fast and robust method for the identification of face landmarks in profile images
WSEAS Transactions on Computers
Robust identification of face landmarks in profile images
ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
A novel approach to classification of facial expressions from 3D-mesh datasets using modified PCA
Pattern Recognition Letters
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Facial landmark detection system using interest-region model and edge energy function
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Algorithm optimizations for low-complexity eye tracking
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Facial feature point extraction using the adaptive mean shape in active shape model
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
Facial expression recognition using AAMICPF
HCII'11 Proceedings of the 14th international conference on Human-computer interaction: interaction techniques and environments - Volume Part II
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This paper describes a method for the automatic location of facial features, such as eyes, nose and mouth, in image sequences using a neural network approach. It is shown that by modeling the feature sought as a structural assembly of micro-features, and by using a probabilistic interpretation of neural network outputs, it is possible to construct a location system that is more robust than a location system which uses the feature as a single entity. With this micro-feature approach, not only the position of the features can be found, but also the shape of the features.