Animated Heads from Ordinary Images: A Least-Squares Approach

摘要

We show that we can effectively fit arbitrarily complex animation models to noisy data extracted from ordinary face images. Our approach is based on least-squares adjustment, using of a set of progressively finer control triangulations and takes advantage of three complementary sources of information: stereo data, silhouette edges, and 2D feature points. In this way, complete head models—including ears and hair—can be acquired with a cheap and entirely passive sensor, such as an ordinary video camera. They can then be fed to existing animation software to produce synthetic sequences.