Shape Modeling targets the description of the shape variation present in a population of scans with so called statistical shape models'. A major challenge in building shape models is finding correspondences between the scans. At the Vision Lab, two classes of correspondence methods are researched. On the one hand, group-wise correspondence methods based on surface parameterization, with a focus on elongated surfaces or surfaces of cylindrical topology, have been developed. On the other hand, research is done on the use of elastic surface registration to find pairwise correspondences. Next to the fundamental research, Vision Lab also focuses on applying shape models for improving fit and function of products that are worn close to or in the human body, e.g. protective gear, headsets, and implants.