V.: Regularized 3d morphable models

Three-dimensional morphable models of object classes are a powerful tool in modeling, animation and recognition. We introduce here the new concept of regularized 3D mor-phable models, along with an iterative learning algorithm, by adding in the statistical model a noise/regularization term which is estimated from the examples set. With regu-larized 3D morphable models we are able to handle miss-ing information, as it often occurs with data obtained by 3D acquisition systems; additionally, the new models are less complex than, but as powerful as the non-regularized ones. We present the results obtained for a set of 3D face models and a comparison with the ones obtained by a tra-ditional morphable model on the same data set. 1