As developing finite element (FE) human body models for automotive impact is a time-consuming process, morphing using interpolation methods such as kriging has often been used to rapidly generate models of different shapes and sizes. Kriging can be computationally expensive when many control points (CPs) are used, i.e., for very detailed target geometry (e.g., shape of bones and skin). It can also lead to element quality issues (up to inverted elements) preventing the use of the morphed models for finite element simulation. This paper presents a workflow combining iterative subsampling and spatial subdivision methodology that effectively reduces the computational costs and allows for the generation of usable models through kriging with hundreds of thousands of control points. As subdivision introduces discontinuities in the interpolation function that can cause distortion of elements on the boundaries of individual subdivision areas, algorithms for smoothing the interpolation over those boundaries are proposed and compared. Those techniques and their combinations were tested and evaluated in a scenario of mass change on the detailed 50th percentile male model of the global human body models consortium (GHBMC): the model, which has body mass index (BMI) 25.34, was morphed toward a statistical surface model of a person with body mass index 20, 22.7 and 35. 234 777 control points were used to successfully morph the model in less than 15 min on an office PC. Open source implementation is provided.