A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Object modelling by registration of multiple range images
Image and Vision Computing - Special issue: range image understanding
A Reflective Symmetry Descriptor for 3D Models
Algorithmica
Pictorial Structures for Object Recognition
International Journal of Computer Vision
Shape segmentation using local slippage analysis
Proceedings of the 2004 Eurographics/ACM SIGGRAPH symposium on Geometry processing
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Salient geometric features for partial shape matching and similarity
ACM Transactions on Graphics (TOG)
Accurate detection of symmetries in 3D shapes
ACM Transactions on Graphics (TOG)
A planar-reflective symmetry transform for 3D shapes
ACM SIGGRAPH 2006 Papers
Partial and approximate symmetry detection for 3D geometry
ACM SIGGRAPH 2006 Papers
ACM SIGGRAPH 2007 papers
Multi-scale features for approximate alignment of point-based surfaces
SGP '05 Proceedings of the third Eurographics symposium on Geometry processing
Folding meshes: hierarchical mesh segmentation based on planar symmetry
SGP '06 Proceedings of the fourth Eurographics symposium on Geometry processing
Detecting symmetry and symmetric constellations of features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Symmetry factored embedding and distance
ACM SIGGRAPH 2010 papers
Inference-based procedural modeling of solids
Computer-Aided Design
Feature-based 3D morphing based on geometrically constrained spherical parameterization
Computer Aided Geometric Design
Exploring Shape Variations by 3D-Model Decomposition and Part-based Recombination
Computer Graphics Forum
International Journal of Computer Vision
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Symmetry detection aims at discovering redundancy in the form of reoccurring structures in geometric objects. In this paper, we present a new symmetry detection algorithm for geometry represented as point clouds that is based on analyzing a graph of surface features. We combine a general feature detection scheme with a RANSAC-based randomized subgraph searching algorithm in order to reliably detect reoccurring patterns of locally unique structures. A subsequent segmentation step based on a simultaneous region growing variant of the ICP algorithm is applied to verify that the actual point cloud data supports the pattern detected in the feature graphs. We apply our algorithm to synthetic and real-world 3D scanner data sets, demonstrating robust symmetry detection results in the presence of scanning artifacts and noise. The modular and flexible nature of the graph-based detection scheme allows for easy generalizations of the algorithm, which we demonstrate by applying the same technique to other data modalities such as images or triangle meshes.