Prediction of Individual Non-Linear Aging Trajectories of Faces

Represented in a Morphable Model, 3D faces follow curved trajectories in face space as they age. We present a novel algorithm that computes the individual aging trajectories for given faces, based on a non-linear function that assigns an age to each face vector. This function is learned from a database of 3D scans of teenagers and adults using support vector regression. To apply the aging prediction to images of faces, we reconstruct a 3D model from the input image, apply the aging transformation on both shape and texture, and then render the face back into the same image or into images of other individuals at the appropriate ages, for example images of older children. Among other applications, our system can help to find missing children. Categories and Subject Descriptors (according to ACM CCS): I.3.6 [Computer Graphics]: Methodology and Techniques–Interaction techniques I.4.10 [Image Processing and Computer Vision]: Image Representation– Hierarchical, Multidimensional, Statist...

• Type: Journal
• Year: 2007
• Where: CGF
• Authors: Kristina Scherbaum, Martin Sunkel, Hans-Peter Seidel, Volker Blanz
• Keywords: CGF 2007, Image, Individual Aging Trajectories, Support Vector Regression