Catherine M. Scandrett

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We present a statistically rigorous approach to the aging of digitised images of the human face. Our methodology is based on the calculation of optimised aging trajectories in a model space and aged images can be obtained through a fast, semi-automatic procedure. In addition, person-specific information about the subject at previous ages is included,(More)
In this paper the age group estimation is presented based on combination of texture and fractal dimension features. The age of the human is used as one of the important key parameter for computer vision applications. The fractal dimension of the face image and the texture analysis is used to classify the age of the person into the three different groups(More)
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