An adaptive subdivision method for surface-fitting from sampled data
SIGGRAPH '86 Proceedings of the 13th annual conference on Computer graphics and interactive techniques
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Computer Aided Geometric Design
Constrained B-spline curve and surface fitting
Computer-Aided Design
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Computer Aided Geometric Design
Fundamentals of computer aided geometric design
Fundamentals of computer aided geometric design
Data point selection for piecewise linear curve approximation
Computer Aided Geometric Design
The NURBS book
Surface fitting with hierarchical splines
ACM Transactions on Graphics (TOG)
Curves and surfaces for CAGD: a practical guide
Curves and surfaces for CAGD: a practical guide
Advanced surface fitting techniques
Computer Aided Geometric Design
An error-bounded approximate method for representing planar curves in B-splines
Computer Aided Geometric Design
Adaptive T-spline surface fitting to z-map models
GRAPHITE '05 Proceedings of the 3rd international conference on Computer graphics and interactive techniques in Australasia and South East Asia
B-spline curve fitting based on adaptive curve refinement using dominant points
Computer-Aided Design
Technical Section: An extended iterative format for the progressive-iteration approximation
Computers and Graphics
The application of evolutionary algorithm in b-spline curved surface fitting
AICI'12 Proceedings of the 4th international conference on Artificial Intelligence and Computational Intelligence
A study of surface reconstruction for 3D mannequins based on feature curves
Computer-Aided Design
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By expanding the idea of B-spline curve fitting using dominant points (Park and Lee 2007 [13]), we propose a new approach to B-spline surface fitting to rectangular grid points, which is based on adaptive knot placement using dominant columns along u- and v-directions. The approach basically takes approximate B-spline surface lofting which performs adaptive multiple B-spline curve fitting along and across rows of the grid points to construct a resulting B-spline surface. In multiple B-spline curve fitting, rows of points are fitted by compatible B-spline curves with a common knot vector whose knots are computed by averaging the parameter values of dominant columns selected from the points. We address how to select dominant columns which play a key role in realizing adaptive knot placement and thereby yielding better surface fitting. Some examples demonstrate the usefulness and quality of the proposed approach.