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Face image synthesis with weight and age progression using conditional adversarial autoencoder
(PDF) MORPH: A longitudinal image database of normal adult age-progression
Modelling of the development of facial morphology during childhood and adolescence is highly useful in forensic and biomedical practice. However, most studies in this area fail to capture the essence of the face as a three-dimensional structure. The main aims of our present study were 1 to construct ageing trajectories for the female and male face between 7 and 17 years of age and 2 to propose a three-dimensional age progression age -regression system focused on real growth-related facial changes. Our approach was based on an assessment of a total of three-dimensional 3D facial scans of Czech children 39 boys, 48 girls that were longitudinally studied between the ages of 7 to 12 and 12 to 17 years. We observed very similar growth rates between 7 and 10 years in both sexes, followed by an increase in growth velocity in both sexes, with maxima between 11 and 12 years in girls and 11 to 13 years in boys, which are connected with the different timing of the onset of puberty.
MORPH: A longitudinal image database of normal adult age-progression
Neural Computing and Applications. The appearance of a human face changes with the change in body weight and age. With varying lifestyle choices, it is hard to imagine the appearance of a given human face in years to come.
Modelling of the development of facial morphology during childhood and adolescence is highly useful in forensic and biomedical practice. However, most studies in this area fail to capture the essence of the face as a three-dimensional structure. The main aims of our present study were 1 to construct ageing trajectories for the female and male face between 7 and 17 years of age and 2 to propose a three-dimensional age progression age -regression system focused on real growth-related facial changes.