Recently developed 3D scanning devices are capable of capturing point clouds, as well as additional information, such as normals and texture. This paper describes a new and fast reverse engineering method for creating a 3D computerized model from data captured by such contemporary 3D scanning devices. The proposed method aggregates large-scale 3D scanned data into an extended Hierarchical Space Decomposition Model (HSDM) based on Octree data structure. This model can represent both an object’s boundary surface and its interior volume. The HSDM enables data reduction, while preserving sharp geometrical features and object topology. As a result the execution time of the reconstruction process is significantly reduced. Moreover, the proposed model naturally allows multiresolution surface reconstruction, represented by a mesh with regular properties. Based on the proposed volumetric model, the surface reconstruction process becomes more robust and stable with respect to sampling noise.