Multi-hypothesis, volumetric reconstruction of 3-D objects from multiple calibrated camera views

In this paper we present a volumetric method for the 3-D reconstruction of real world objects from multiple calibrated camera views. The representation of the objects is fully volume-based and no explicit surface description is needed. The approach is based on multi-hypothesis tests of the voxel model back-projected into the image planes. All camera views are incorporated in the reconstruction process simultaneously and no explicit data fusion is needed. In a first step each voxel of the viewing volume is filled with several color hypotheses originating from different camera views. This leads to an overcomplete representation of the 3-D object and each voxel typically contains multiple hypotheses. In a second step only those hypotheses remain in the voxels which are consistent with all camera views where the voxel is visible. Voxels without a valid hypothesis are considered to be transparent. The methodology of our approach combines the advantages of silhouette-based and image feature-based methods. Experimental results on real and synthetic image data show the excellent visual quality of the voxel-based 3-D reconstruction.