3D scanners developed over the past several decades have facilitated the reconstruction of complicated engineering parts. Typically the boundary representation of a part is reconstructed from its scanned cloud of points. This approach, however, is still limited and cannot be applied to a family of objects such as thin parts. Recently, new 3D scanning devices have been developed. These devices capture additional information, such as normals and texture, as well as conventional information,

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... ing clouds of sampled points. This paper describes a new and fast reverse engineering method for creating a 3D computerized model from data captured by 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. Based on the proposed volumetric model, the surface reconstruction process becomes more robust and stable with respect to sampling noise. The hierarchical structure of the proposed volumetric model enables data reduction, while preserving sharp geometrical features and object topology. As a result of data reduction, 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. The proposed surface reconstruction approach is based on extracting a Connectivity Graph from the extended HSDM and reconstructing facets based on normals data. The feasibility of the method will be demonstrated on a number of complex objects, including thin parts.