We present a novel method to synthesize images of a 3D object in arbitrary poses illuminated from arbitrary directions, given a few images of the object in unknown motion under static lighting. Our scheme is underpinned by the notion of illumination image basis which spans an image space of arbitrary lighting, and we propose to generate it by a recursive search for the correspondence between input images and by subsequent realignment of their pixels. Using the 3D surface of the object that also becomes available in this procedure, we synthesize images of the object in arbitrary poses while arbitrarily varying the direction of lighting by combination of the illumination basis images. The effectiveness of the entire algorithm is shown through experiments.

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.