This paper presents a new automatic scheme for tracking a 3D non-rigid object surface such as a human face in a real-time video sequence. We introduce a coordinate-oriented error minimization method for estimating the tracking parameters, whereas we base our algorithm on a morphable 3D model consisting of a combination of 3D linear bases, and show that it is extremely well suited to the task of fitting the 3D model to the target object in real time. The algorithm is straightforward, allowing the parameters of an object's pose and non-rigid motion to be computed in an integrated manner. Also, it is found that the illumination variability on the object surface, for instance due to the target motion, can be handled easily. Through the experiments we not only show that on-line tracking is indeed possible, but also demonstrate the effect of our technique of video mimicking.
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