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Symmetry Detection Using Feature Lines
Author(s) -
Bokeloh M.,
Berner A.,
Wand M.,
Seidel H.P.,
Schilling A.
Publication year - 2009
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2009.01410.x
Subject(s) - mirroring , computer science , redundancy (engineering) , feature (linguistics) , data redundancy , translation (biology) , symmetry (geometry) , algorithm , translational symmetry , artificial intelligence , matching (statistics) , pattern recognition (psychology) , theoretical computer science , mathematics , geometry , linguistics , philosophy , biochemistry , chemistry , communication , statistics , sociology , messenger rna , gene , operating system
In this paper, we describe a new algorithm for detecting structural redundancy in geometric data sets. Our algorithm computes rigid symmetries, i.e., subsets of a surface model that reoccur several times within the model differing only by translation, rotation or mirroring. Our algorithm is based on matching locally coherent constellations of feature lines on the object surfaces. In comparison to previous work, the new algorithm is able to detect a large number of symmetric parts without restrictions to regular patterns or nested hierarchies. In addition, working on relevant features only leads to a strong reduction in memory and processing costs such that very large data sets can be handled. We apply the algorithm to a number of real world 3D scanner data sets, demonstrating high recognition rates for general patterns of symmetry.