Online geometric reconstruction

Abstract

We investigate a new class of geometric problems based on the idea of online error correction. Suppose one is given access to a large geometric dataset though a query mechanism; for example, the dataset could be a terrain and a query might ask for the coordinates of a particular vertex or for the edges incident to it. Suppose, in addition, that the dataset satisfies some known structural property P (for example, monotonicity or convexity) but that, because of errors and noise, the queries occasionally provide answers that violate P . Can one design a filter that modifies the query's answers so that (i) the output satisfies P ; (ii) the amount of data modification is minimized? We provide upper and lower bounds on the complexity of online reconstruction for convexity in 2D and 3D.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 01, 2011
Source ID
10.1145/1989727.1989728

Entities

People

  • Bernard Chazelle
  • C. Seshadhri

Organizations

  • Army Research Office
  • National Science Foundation
  • Princeton University
  • Sandia National Laboratories

Tags

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Graph Algorithms and Convex Optimization.
  • Regression Analysis.