Discrete & Computational Geometry
A class of convex programs with applications to computational geometry
SCG '92 Proceedings of the eighth annual symposium on Computational geometry
A Subexponential Algorithm for Abstract Optimization Problems
SIAM Journal on Computing
On linear-time deterministic algorithms for optimization problems in fixed dimension
Journal of Algorithms
Linear Programming in Linear Time When the Dimension Is Fixed
Journal of the ACM (JACM)
Explicit and implicit enforcing: randomized optimization
Computational Discrete Mathematics
SWAT '98 Proceedings of the 6th Scandinavian Workshop on Algorithm Theory
Fast and Robust Smallest Enclosing Balls
ESA '99 Proceedings of the 7th Annual European Symposium on Algorithms
Unique Sink Orientations of Cubes
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
Approximate minimum enclosing balls in high dimensions using core-sets
Journal of Experimental Algorithmics (JEA)
Collision detection for deforming necklaces
Computational Geometry: Theory and Applications - Special issue on the 18th annual symposium on computational geometrySoCG2002
Efficient updates of bounding sphere hierarchies for geometrically deformable models
Journal of Visual Communication and Image Representation
Coverage in Biomimetic Pattern Recognition
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
A robust fuzzy rough set model based on minimum enclosing ball
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Covering and piercing disks with two centers
ISAAC'11 Proceedings of the 22nd international conference on Algorithms and Computation
Ball ranking machines for content-based multimedia retrieval
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Soft Minimum-Enclosing-Ball Based Robust Fuzzy Rough Sets
Fundamenta Informaticae - Rough Sets and Knowledge Technology (RSKT 2010)
Covering and piercing disks with two centers
Computational Geometry: Theory and Applications
Protein structure optimization by side-chain positioning via beta-complex
Journal of Global Optimization
Fast and robust approximation of smallest enclosing balls in arbitrary dimensions
SGP '13 Proceedings of the Eleventh Eurographics/ACMSIGGRAPH Symposium on Geometry Processing
Hi-index | 0.00 |
We develop algorithms for computing the smallest enclosing ball of a set of n balls in d-dimensional space. Unlike previous methods, we explicitly address small cases (n= d+1), derive the necessary primitive operations and show that they can efficiently be realized with rational arithmetic. An exact implementation (along with a fast For d=3, a set of 1,000,000 balls is processed in less than two seconds on a modern PC. and robust floating-point version) is available as part of the CGAL library.See http://www.cgal.org.Our algorithms are based on novel insights into the combinatorial structure of the problem. As it turns out, results for smallest enclosing balls of points do not extend as one might expect. For example, we show that Welzl's randomized linear-time algorithm for computing the ball spanned by a set of points fails to work for balls. Consequently, David White's adaptation of the method to the ball case---as the only available implementation so far it is mentioned in many link collections---is incorrect and may crash or, in the better case, produce wrong balls.In solving the small cases we may assume that the ball centers are affinely independent; in this case, the problem is surprisingly well-behaved: via a geometric transformation and suitable generalization, it fits into the combinatorial model of unique sink orientations whose rich structure has recently received considerable attention. One consequence is that Welzl's algorithm does work for small instances; moreover, there is a wide variety of pivoting methods for unique sink orientations which have the potential of being fast in practice even for high dimension.As a by-product, we show that the problem of finding the smallest enclosing ball of balls is computationally equivalent to the problem of finding the minimum-norm point in the convex hull of a set of balls.