Localization of a robotic system within previously mapped environment is important for reducing estimation drift and reusing built maps. Existing techniques geometry-based localization have focused on the description local surface geometry, usually using pointclouds as underlying representation. We propose geometrybased that extracts features directly from an implicit representation: Signed Dis...

We propose displaced signed distance fields, an implicit shape representation to accurately, efficiently and robustly 3D-print finely detailed smoothly curved surfaces at native device resolution. As the resolution accuracy of 3D printers increase, accurate reproduction such becomes increasingly realizable from a hardware perspective. However, representing with polygonal meshes requires high po...

We study the String Reversal Distance problem, an extension of the well-known Sorting by Reversals problem. String Reversal Distance takes two strings S and T as input, and asks for a minimum number of reversals to obtain T from S. We consider four variants: String Reversal Distance, String Prefix Reversal Distance (in which any reversal must include the first letter of the string), and the sig...

Signed distance functions computed in discrete form from given RGB-D data as regular voxel grids can represent manifold shapes the zero crossing of a trivariate function; corresponding meshes be derived by Marching Cubes algorithm. However, 3D models automatically reconstructed this way often contain irrelevant objects or artifacts, such holes noise, due to erroneous scan and error-prone recons...