Fitting cylinders to data

Fitting enclosing cylinders to data in R

A simple iterative algorithm is given for finding a stationary point of the (non-convex) problem of finding the smallest enclosing (n− d)cylinder to discrete data in Rn, that is a cylinder whose axis is a ddimensional linear manifold. An important special case is the problem of finding the smallest enclosing (usual) cylinder, when n = 3 and d = 1. The method is based on the solution of a sequen...

A RANSAC-Based Approach to Model Fitting and Its Application to Finding Cylinders in Range Data

General principles for fitting models to data containing "gross" errors in addition to "measurement" errors are presented A fitting technique is described and illustrated by its application to the problem of locating cylinders in range data, two key steps in this process arc fitting ellipses to partial data and fitting lines to sets of three-dimensional points The technique is specifically desi...

Geometric least-squares fitting of spheres, cylinders, cones and tori

This paper considers a problem arising in the reverse engineering of boundary representation solid models from three-dimensional depth maps of scanned objects. In particular, we wish to identify and fit surfaces of known type wherever these are a good fit, and we briefly outline a segmentation strategy for deciding to which surface type the depth points should be assigned. The particular contri...

Superellipse fitting to partial data

Superellipses can be used to represent in a compact form a large variety of shapes, and are useful for modelling in the fields of computer graphics and computer vision. However, fitting them to data is difficult and computationally expensive. Moreover, when only partial data is available the parameter estimates become unreliable. This paper attempts to improve the process of fitting to partial ...

Fitting Models to Grouped Data