Abstract Optical triangulation laser scanners produce errors at surface discontinuities and sharp features. These systematic errors are anisotropic. We examine the causes of these errors theoretically, and we study the correlation of systematic error with edge size and orientation experimentally. We then present a novel processing method for removing systematic errors, by combining scans taken at several different orientations. We apply an anisotropic filter to the separate scans, and use it to weight the data in a final combination step. Unlike previous approaches, our method does not require access to the scanner's internal data or firmware. We demonstrate the technique on data from laser range scanners by two different manufacturers.

We introduce the 3D warp brush, a method for interactive shape modeling in a immersive virtual reality environment. 3D warp brushes are implicitly-defined tools that operate on triangle meshes. We combine the efficiency of explicit mesh representations with implicit modeling operators. The area of influence of a 3D warp brush can be of arbitrary shape since it has an associated distance field. We define different warp functions including drag, explode, and whittle. A unique feature of our framework is the ability to convert meshes into 3D warp brushes at run time. The use of a Responsive Workbench and two-handed interaction allows the user to exploit the full potential of the modeling system by intuitive and easy modification of a base surface into a desired shape. We present models, which have been created and modified using 3D warp brushes, to demonstrate the usefulness of our framework.

The MLS surface [Levin 2003], used for modeling and rendering with point clouds, was originally defined algorithmically as the output of a particular meshless construction. We give a new explicit definition in terms of the critical points of an energy function on lines determined by a vector field. This definition reveals connections to research in computer vision and computational topology.Variants of the MLS surface can be created by varying the vector field and the energy function. As an example, we define a similar surface determined by a cloud of surfels (points equipped with normals), rather than points.We also observe that some procedures described in the literature to take points in space onto the MLS surface fail to do so, and we describe a simple iterative procedure which does.