Adaptive sampling and reconstruction for discontinuity preserving texture-mapped triangulation

The objective of this work is to use input data to construct a texture-mapped polyhedral representation of surfaces that can adapt to intrinsic surface properties, preserving their discontinuities, and might be used efficiently as an accurate 3D object model in graphical rendering. The authors present an adaptive sampling and reconstruction model for hierarchical triangulation of 3D objects. They have developed a parallel algorithm of adaptive mesh generation that recursively bisects mesh elements by increasing the number of mesh nodes according to local surface properties, such as surface orientation, curvature and color. The recursive subdivision based on such a viewpoint-invariant feature yields the hierarchical surface triangulation that is intrinsic to the surface, and satisfies the absolute accuracy criterion, because nodes are generated as many times as required until the entire surface has been approximated with a given threshold. The authors apply the algorithm to the adaptive sampling and reconstruction of range and color-texture images of human faces and fine antique dolls