Efficient Point-Cloud Processing with Primitive Shapes

Dissertation, Universität Bonn, Dez. 2010
 

Abstract

This thesis presents methods for efficient processing of point-clouds based on primitive shapes. The set of considered simple parametric shapes consists of planes, spheres, cylinders, cones and tori. The algorithms developed in this work are targeted at scenarios in which the occurring surfaces can be well represented by this set of shape primitives which is the case in many man-made environments such as e.g.\ industrial compounds, cities or building interiors. A primitive subsumes a set of corresponding points in the point-cloud and serves as a proxy for them. Therefore primitives are well suited to directly address the unavoidable oversampling of large point-clouds and lay the foundation for efficient point-cloud processing algorithms.

The first contribution of this thesis is a novel shape primitive detection method that is efficient even on very large and noisy point-clouds. Several applications for the detected primitives are subsequently explored, resulting in a set of novel algorithms for primitive-based point-cloud processing in the areas of compression, recognition and completion. Each of these application directly exploits and benefits from one or more of the detected primitives' properties such as approximation, abstraction, segmentation and continuability.

(Thesis submission date: Dec. 2009)

Download: http://nbn-resolving.de/urn:nbn:de:hbz:5N-23194

Bibtex

@PHDTHESIS{schnabel-2010-dissertation,
    author = {Schnabel, Ruwen},
     title = {Efficient Point-Cloud Processing with Primitive Shapes},
      type = {Dissertation},
      year = {2010},
     month = dec,
    school = {Universit{\"a}t Bonn},
  abstract = {This thesis presents methods for efficient processing of point-clouds based on primitive shapes. The
              set of considered simple parametric shapes consists of planes, spheres, cylinders, cones and tori.
              The algorithms developed in this work are targeted at scenarios in which the occurring surfaces can
              be well represented by this set of shape primitives which is the case in many man-made environments
              such as e.g.\ industrial compounds, cities or building interiors. A primitive subsumes a set of
              corresponding points in the point-cloud and serves as a proxy for them. Therefore primitives are
              well suited to directly address the unavoidable oversampling of large point-clouds and lay the
              foundation for efficient point-cloud processing algorithms.
              
              The first contribution of this thesis is a novel shape primitive detection method that is efficient
              even on very large and noisy point-clouds. Several applications for the detected primitives are
              subsequently explored, resulting in a set of novel algorithms for primitive-based point-cloud
              processing in the areas of compression, recognition and completion. Each of these application
              directly exploits and benefits from one or more of the detected primitives' properties such as
              approximation, abstraction, segmentation and continuability.},
       url = {http://nbn-resolving.de/urn:nbn:de:hbz:5N-23194}
}