Edit Propagation using Geometric Analogies

Paul Guerrero
Edit Propagation using Geometric Analogies
Supervisor: Michael Wimmer
Duration: 2008 - 2014
[Thesis]

Information

Abstract

Modeling complex geometrical shapes, like city scenes or terrains with dense vegetation, is a time-consuming task that cannot be automated trivially. The problem of creating and editing many similar, but not identical models requires specialized methods that understand what makes these objects similar in order to either create new variations of these models from scratch or to propagate edit operations from one object to all similar objects. In this thesis, we present new methods to significantly reduce the effort required to model complex scenes.

For 2D scenes containing deformable objects, such as fish or snakes, we present a method to find partial matches between deformed shapes that can be used to transfer localized properties such as texture between matching shapes. Shapes are considered similar if they are related by pointwise correspondences and if neighboring points have correspondences with similar transformation parameters. Unlike previous work, this approach allows us to successfully establish matches between strongly deformed objects, even in the presence of occlusions and sparse or unevenly distributed sets of matching features.

For scenes consisting of 2D shape arrangements, such as floor plans, we propose methods to find similar locations in the arrangements, even though the arrangements themselves are dissimilar. Edit operations, such as object placements, can be propagated between similar locations. Our approach is based on simple geometric relationships between the location and the shape arrangement, such as the distance of the location to a shape boundary or the direction to the closest shape corner. Two locations are similar of they have many similar relations to their surrounding shape arrangement. To the best of our knowledge, there is no method that explicitly attempts to find similar locations in dissimilar shape arrangements. We demonstrate populating large scenes such as floor plans with hundreds of objects like pieces of furniture, using relatively few edit operations.

Additionally, we show that providing several examples of an edit operation helps narrowing down the supposed modeling intention of the user and improves the quality of the edit propagation. A probabilistic model is learned from the examples and used to suggest similar edit operations. Also, extensions are shown that allow application of this method in 3D scenes. Compared to previous approaches that use entire scenes as examples, our method provides more user control and has no need for large databases of example scenes or domain-specific knowledge. We demonstrate generating 3D interior decoration and complex city scenes, including buildings with detailed facades, using only few edit operations.

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BibTeX

@phdthesis{Guerrero_Paul_2014_EPG,
  title =      "Edit Propagation using Geometric Analogies",
  author =     "Paul Guerrero",
  year =       "2014",
  abstract =   "Modeling complex geometrical shapes, like city scenes or
               terrains with dense vegetation, is a time-consuming task
               that cannot be automated trivially. The problem of creating
               and editing many similar, but not identical models requires
               specialized methods that understand what makes these objects
               similar in order to either create new variations of these
               models from scratch or to propagate edit operations from one
               object to all similar objects. In this thesis, we present
               new methods to significantly reduce the effort required to
               model complex scenes.  For 2D scenes containing deformable
               objects, such as fish or snakes, we present a method to find
               partial matches between deformed shapes that can be used to
               transfer localized properties such as texture between
               matching shapes. Shapes are considered similar if they are
               related by pointwise correspondences and if neighboring
               points have correspondences with similar transformation
               parameters. Unlike previous work, this approach allows us to
               successfully establish matches between strongly deformed
               objects, even in the presence of occlusions and sparse or
               unevenly distributed sets of matching features.  For scenes
               consisting of 2D shape arrangements, such as floor plans, we
               propose methods to find similar locations in the
               arrangements, even though the arrangements themselves are
               dissimilar. Edit operations, such as object placements, can
               be propagated between similar locations. Our approach is
               based on simple geometric relationships between the location
               and the shape arrangement, such as the distance of the
               location to a shape boundary or the direction to the closest
               shape corner. Two locations are similar of they have many
               similar relations to their surrounding shape arrangement. To
               the best of our knowledge, there is no method that
               explicitly attempts to find similar locations in dissimilar
               shape arrangements. We demonstrate populating large scenes
               such as floor plans with hundreds of objects like pieces of
               furniture, using relatively few edit operations. 
               Additionally, we show that providing several examples of an
               edit operation helps narrowing down the supposed modeling
               intention of the user and improves the quality of the edit
               propagation.  A probabilistic model is learned from the
               examples and used to suggest similar edit operations. Also,
               extensions are shown that allow application of this method
               in 3D scenes. Compared to previous approaches that use
               entire scenes as examples, our method provides more user
               control and has no need for large databases of example
               scenes or domain-specific knowledge. We demonstrate
               generating 3D interior decoration and complex city scenes,
               including buildings with detailed facades, using only few
               edit operations.",
  month =      nov,
  address =    "Favoritenstrasse 9-11/186, A-1040 Vienna, Austria",
  school =     "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2014/Guerrero_Paul_2014_EPG/",
}