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The morphable modeling method of reconstructing 3D human face is based on a single given image, and the model fitting is ambiguous owing to the lack of depth information and geometry constraints between images. In this paper, we introduce a new face reconstruction method from multiple views based on the morphable model. The morphable face model is matched with multiple face images from different views. Using the multi-view geometry constraints, the ambiguity is efficiently eliminated and more realistic results are provided. We test our algorithm on the MPI face database and real images from our multi-camera system. The experimental results show the efficiency of the proposed method.

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In this paper, we investigate the problem of determining regions in 3D scene visible to some given viewpoints when obstacles are present in the scene. We assume that the obstacles are composed of some opaque objects with closed surfaces. The problem is formulated in an implicit framework where the obstacles are represented by a level set function. The visible and invisible regions of the given viewpoints are determined through an efficient implicit ray tracing technique. As an extension of our approach, we apply the multiview visibility estimation to an image-based modeling technique. The unknown scene geometry and multiview visibility information are incorporated into a variational energy functional. By minimizing the energy functional, the true scene geometry as well as the accurate visibility information of the multiple views can be recovered from a number of scene images. This makes it feasible to handle the visibility problem of multiple views by our approach when the true scene geometry is unknown.