Continuous skeleton computation by Voronoi diagram
CVGIP: Image Understanding
r-regular shape reconstruction from unorganized points
SCG '97 Proceedings of the thirteenth annual symposium on Computational geometry
The crust and the &Bgr;-Skeleton: combinatorial curve reconstruction
Graphical Models and Image Processing
Crust and anti-crust: a one-step boundary and skeleton extraction algorithm
SCG '99 Proceedings of the fifteenth annual symposium on Computational geometry
Curve reconstruction, the traveling salesman problem and Menger's theorem on length
SCG '99 Proceedings of the fifteenth annual symposium on Computational geometry
A simple provable algorithm for curve reconstruction
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
TSP-based curve reconstruction in polynomial time
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Closed Object Boundaries from Scattered Points
Closed Object Boundaries from Scattered Points
Closed Curve Reconstruction from Unorganized Sample Points
ISVD '06 Proceedings of the 3rd International Symposium on Voronoi Diagrams in Science and Engineering
An RNG-based heuristic for curve reconstruction
ISVD '06 Proceedings of the 3rd International Symposium on Voronoi Diagrams in Science and Engineering
Curve and Surface Reconstruction: Algorithms with Mathematical Analysis (Cambridge Monographs on Applied and Computational Mathematics)
A distance-based parameter free algorithm for curve reconstruction
Computer-Aided Design
VICUR: A human-vision-based algorithm for curve reconstruction
Robotics and Computer-Integrated Manufacturing
Optimization-based approach for curve and surface reconstruction
Computer-Aided Design
On the shape of a set of points in the plane
IEEE Transactions on Information Theory
Reconstructing curves with sharp corners
Computational Geometry: Theory and Applications
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Curve reconstruction is the problem of constructing polygonal curves from a set of sample points. Among all the research to solve this problem, visual perception based algorithms, DISCUR and VICUR, come up in recent years as intuitive methods. DISCUR and VICUR connect points into patterns that agree with human visual perception by applying two major Gestalt laws: nearness and smoothness. In this paper, the work in DISCUR and VICUR is extended by conducting an experiment to quantify how these two laws underlie human vision. DOE and ANOVA are used to test the hypotheses about how a connection may be influenced by its neighboring points whereas the multivariable nonlinear regression model is adopted to formulate the influence of Gestalt laws on point connectivity. The experimental results show that the proposed approach is effective.