From regular images to animated heads: a least squares approach

We show that we can effectively fit arbitrarily complex animation models to noisy image data. 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