document: Automatic extraction of eye and mouth fields from a face image using eigenfeatures and ensemble networks This paper presents a novel algorithm for the extraction of the eye and mouth -LRB- facial features -RRB- fields from 2D gray level images . Eigenfeatures are derived from the eigenvalues and eigenvectors of the binary edge data set constructed from eye and mouth fields . Such eigenfeatures are ideal features for finely locating fields efficiently . The eigenfeatures are extracted from a set of the positive and negative training samples for facial features and are used to train a multilayer perceptron -LRB- MLP -RRB- whose output indicates the degree to which a particular image window contains the eyes or the mouth within itself . An ensemble network consisting of a multitude of independent MLPs was used to enhance the generalization performance of a single MLP . It was experimentally verified that the proposed algorithm is robust against facial size and even slight variations of the pose
doc_bio_tags: O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B I I I O B O O O O B O B O O B I I I O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O B I O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O