Eigenface based facial recognition
13 Feb These characteristic features are called eigenfaces in the facial recognition domain (or principal components generally). They can be extracted.
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Eigenface-based facial recognition
Eigenfaces is the name given to a set of eigenvectors when they are used in the computer vision problem of human face recognition. The approach of using eigenfaces for recognition was developed by Sirovich Informally, eigenfaces can be considered a set of "standardized face ..
Eigenface-based facial recognition.
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Description:The task of facial recogniton is discriminating input signals image data into several classes persons. The input signals are highly noisy e. Such patterns, which can be observed in all signals could be - in the domain of facial recognition - the presence of some objects eyes, nose, mouth in any face as well as relative distances between these objects. These characteristic features are called eigenfaces in the facial recognition domain or principal components generally. They can be extracted out of original image data by means of a mathematical tool called Principal Component Analysis PCA. By means of PCA one can transform each original image of the training set into a corresponding eigenface.
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