We present a novel approach on digitizing large scale unstructured environments like archaeological excavations using off-the-shelf digital still cameras. The cameras are calibrated with respect to few markers captured by a theodolite system. Having all cameras registered in the same coordinate system enables a volumetric approach. Our new algorithm has as input multiple calibrated images and outputs an occupancy voxel space where occupied pixels have a local orientation and a confidence value. Both, orientation and confidence facilitate an efficient rendering and texture mapping of the resulting point cloud. Our algorithm combines the following new features: Images are backprojected to hypothesized local patches in the world and correlated on these patches yielding the best orientation. Adjacent cameras build tuples which yield a product of pairwise correlations, called strength. Multiple camera tuples compete each other for the best strength for each voxel. A voxel is regarded as...