Paper Info
Title
Modeling and Exploring Co-variations in the Geometry and Configuration of Man-made 3D Shape Families
Abstract
AbstractWe introduce co-variation analysis as a tool for modeling the way part geometries and configurations co-vary across a family of man-made 3D shapes. While man-made 3D objects exhibit large geometric and structural variations, the geometry, structure, and configuration of their individual components usually do not vary independently from each other but in a correlated fashion. The size of the body of an airplane, for example, constrains the range of deformations its wings can undergo to ensure that the entire object remains a functionally-valid airplane. These co-variation constraints, which are often non-linear, can be either physical, and thus they can be explicitly enumerated, or implicit to the design and style of the shape family. In this article, we propose a data-driven approach, which takes pre-segmented 3D shapes with known component-wise correspondences and learns how various geometric and structural properties of their components co-vary across the set. We demonstrate, using a variety of 3D shape families, the utility of the proposed co-variation analysis in various applications including 3D shape repositories exploration and shape editing where the propagation of deformations is guided by the co-variation analysis. We also show that the framework can be used for context-guided orientation of objects in 3D scenes.
Year
DOI
Venue
2017
10.1111/cgf.13241
Periodicals
Field
DocType
Volume
Computer vision,3d shapes,Computer science,Airplane,Artificial intelligence,Geometry,Shape analysis (digital geometry)
Journal
36
Issue
ISSN
Citations 
5
0167-7055
1
PageRank 
References 
Authors
0.36
19
2
Name
Order
Citations
PageRank
Hamid Laga137627.28
Hedi Tabia227816.27