Surface reconstruction of scanned human body using radial basis functions and adaptive partition of unity

It is important to reconstruct a continuous surface representation of the point cloud scanned from a human body. In this paper a new implicit surface method is proposed to reconstruct the human body surface from the points based on the combination of radial basis functions (RBFs) and adaptive partition of unity (PoU). The whole 3D domain of the scanned human body is firstly subdivided into a set of overlapping subdomains based on the improved octrees. The smooth local surfaces are then computed in the subdomains based on RBFs. And finally the global human body surface is reconstructed by blending the local surfaces with the adaptive PoU functions. This method is robust for the surface reconstruction of the scanned human body even with large or non-uniform point cloud which has a sharp density variation. Foundation item: the National Natural Science Foundation of China (No. 50575139) and the Shanghai Special Fund of Informatization (No. 088)