Exemplar-based Age Progression Prediction in Children Faces

This work aims to develop a system for predicting age progression in children faces. Age progression prediction in children faces is critical to assist missing children searching. An integral module including feature extraction, distance measurement, and face synthesis is devised in this paper to predict faces at different ages. In the proposed method, a curvature-weighted plus bending-energy distance is employed for selecting similar facial components from an aging database. The growth curve of each facial component is used to predict the shape, size, and location of each component at a different age. Thin plate spline method is employed to synthesize a 3-D face model from the predicted components by minimizing the bending energy. Experiments are conducted to test the proposed method with various subjects and the results show that the proposed method is very promising.