Volume intersection with optimal set of directions
Pattern Recognition Letters
How Far 3D Shapes Can Be Understood from 2D Silhouettes
IEEE Transactions on Pattern Analysis and Machine Intelligence
How many 2D silhouettes does it take to reconstruct a 3D object?
Computer Vision and Image Understanding
Curve reconstruction from unorganized points
Computer Aided Geometric Design
Robust Centerline Extraction Framework Using Level Sets
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A Spectral Technique for Correspondence Problems Using Pairwise Constraints
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Defining and computing curve-skeletons with medial geodesic function
SGP '06 Proceedings of the fourth Eurographics symposium on Geometry processing
Skeleton extraction by mesh contraction
ACM SIGGRAPH 2008 papers
Curve-Skeleton Extraction Using Iterative Least Squares Optimization
IEEE Transactions on Visualization and Computer Graphics
Curve skeleton extraction from incomplete point cloud
ACM SIGGRAPH 2009 papers
Discrete scale axis representations for 3D geometry
ACM SIGGRAPH 2010 papers
Point Cloud Skeletons via Laplacian Based Contraction
SMI '10 Proceedings of the 2010 Shape Modeling International Conference
Perceptual models of viewpoint preference
ACM Transactions on Graphics (TOG)
Generalized Swept Mid-structure for Polygonal Models
Computer Graphics Forum
Computer Graphics Forum
Reconstructing the Curve-Skeletons of 3D Shapes Using the Visual Hull
IEEE Transactions on Visualization and Computer Graphics
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Curve-skeletons are compact and semantically relevant shape descriptors, able to summarise both topology and pose of a wide range of digital objects. Most of the state-of-the-art algorithms for their computation rely on the type of geometric primitives used and sampling frequency. In this paper, we introduce a formally sound and intuitive definition of a curve-skeleton, then we propose a novel method for skeleton extraction that relies on the visual appearance of the shapes. To achieve this result, we inspect the properties of occluding contours, showing how information about the symmetry axes of a 3D shape can be inferred from a small set of its planar projections. The proposed method is fast, insensitive to noise and resolution, capable of working with different shape representations, and easy to implement.