Thinning Methodologies-A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generating skeletons and centerlines from the distance transform
CVGIP: Graphical Models and Image Processing
The Euclidean distance transform in arbitrary dimensions
Pattern Recognition Letters
Computation of the Medial Axis Transform of 3-D polyhedra
SMA '95 Proceedings of the third ACM symposium on Solid modeling and applications
OBBTree: a hierarchical structure for rapid interference detection
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
FORMS: a flexible object recognition and modeling system
International Journal of Computer Vision
Computing and simplifying 2D and 3D continuous skeletons
Computer Vision and Image Understanding
Skeleton-based modeling operations on solids
SMA '97 Proceedings of the fourth ACM symposium on Solid modeling and applications
Zoom-invariant vision of figural shape: the mathematics of cores
Computer Vision and Image Understanding
Fast computation of generalized Voronoi diagrams using graphics hardware
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Smooth surface reconstruction via natural neighbour interpolation of distance functions
Proceedings of the sixteenth annual symposium on Computational geometry
Approximate medial axis as a voronoi subcomplex
Proceedings of the seventh ACM symposium on Solid modeling and applications
Shape Description By Medial Surface Construction
IEEE Transactions on Visualization and Computer Graphics
Efficient computation of a simplified medial axis
SM '03 Proceedings of the eighth ACM symposium on Solid modeling and applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Accurate Computation of the Medial Axis of a Polyhedron
Accurate Computation of the Medial Axis of a Polyhedron
The power crust, unions of balls, and the medial axis transform
Computational Geometry: Theory and Applications
Homotopy-preserving medial axis simplification
Proceedings of the 2005 ACM symposium on Solid and physical modeling
Simplified engineering analysis via medial mesh reduction
Proceedings of the 2005 ACM symposium on Solid and physical modeling
Tracking shape change using a 3D skeleton hierarchy
ACM SIGGRAPH 2006 Research posters
Curve-Skeleton Properties, Applications, and Algorithms
IEEE Transactions on Visualization and Computer Graphics
Computer-Aided Design
b-morphs between b-compatible curves in the plane
2009 SIAM/ACM Joint Conference on Geometric and Physical Modeling
Recovering structure from r-sampled objects
SGP '09 Proceedings of the Symposium on Geometry Processing
Algebraic reduction of beams for CAD-integrated analysis
Computer-Aided Design
Sampled medial loci for 3D shape representation
Computer Vision and Image Understanding
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The medial axis can be viewed as a compact representation for an arbitrary model; it is an essential geometric structure in many applications. A number of practical algorithms for its computation have been aimed at speeding up its computation and at addressing its instabilities. In this paper we propose a new algorithm to compute the medial axis with arbitrary precision. It exhibits several desirable properties not previously combined in a practical and efficient algorithm. First, it allows for a tradeoff between computation time and accuracy, making it well-suited for applications in which an approximation of the medial axis suffices, but computational efficiency is of particular concern. Second, it is output sensitive: the computation complexity of the algorithm does not depend on the size of the representation of a model, but on the size of the representation of the resulting medial axis. Third, the densities of the approximated medial axis points in different areas are adaptive to local free space volumes, based on the assumption that a coarser approximation in wide open area can still suffice the requirements of the applications. We present theoretical results, bounding the error introduced by the approximation process. The algorithm has been implemented and experimental results are presented that illustrate its computational efficiency and robustness.