Focused Volumetric Visual Hull with Color Extraction

This paper introduces a new approach for volumetric visual hull reconstruction, using a voxel grid that focuses on the moving target object. This grid is continuously updated as a function of object location, orientation, and size. The benefit is a reduced amount of voxels that have to be evaluated or allocated towards capturing the target at higher resolution. This technique particularly improves reconstructions where the total reconstruction space is larger than the moving reconstruction target. The higher resolution of the voxel grid also reduces the computational cost per voxel reprojection since a one voxel to one input pixel reprojection ratio is approximated. In addition, the appropriate view independent color of the surface voxels is computed allowing for realistic visual hull texturing. All color calculations are performed locally, based on approximated surface voxel normals and the input images. A color outlier detection approach is introduced, which reduces the influence of occlusions in the color evaluation. The parallel nature of the presented focused visual hull reconstruction technique, lends itself to hardware acceleration, allowing interactive rates to be achieved by performing most computations on the GPU. A set of case studies is provided for well-defined static and dynamic data sets.