3D Morphable Model Fittingto Image Sequences

This paper outlines a new method to fit 3D Morphable Models (3DMM’s) from sets of 2D image features. It is the extension of a popular correspondence 3D shape fitting from 2D feature point method which allows it to be applied to video sequences. For shape estimation this paper focuses on strictly linear solutions to the problem of shape fitting to image sequences. In doing so we introduce a Shape- Update algorithm which integrates the data present in the video sequence using only a small amount of computation. This paper also presents the relationship between our Shape-Update algorithm and our previous Kalman filter approach. We also describe a pose estimation algorithm that uses an Extended Kalman filter and a linearly estimated prior.