Accurate Face Models from Uncalibrated and Ill-Lit Video Sequences

In this paper, we propose a face reconstruction technique that produces models that not only look good when texture mapped, but are also metrically accurate. Our method is designed to work with short uncalibrated video or movie sequences, even when the lighting is poor resulting in specularities and shadows that complicate the algorithm's task. Our approach relies on optimizing the shape parameters of a sophisticated PCA based model given pairwise image correspondences as input. All that is required is enough relative motion between camera and subject so that we can derive structure from motion. By matching the results against laser scanning data, we will show that its precision is excellent and can be predicted as a function of the number and quality of the correspondences. This is important if one wishes to obtain the appropriate compromise between processing speed and quality of the results. Furthermore, our method is in fact not specific to faces and could equally be applied to any shape for which a shape model controlled with relatively small number of parameters exists.

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