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CURVES -
REPRESENTATION
Many technological applications
 Design of products (e.g. CAD)
 Calculation of the path for a robot
Design of fonts
 Large sized fonts must be smooth
Interpolating measuring data
Approximating measuring data
Why designing curves?
Controllability
 Changes must be predictable in effect
 Intuitive to use for the designer
Locality
 Local changes should stay local
Smoothness
 No sharp bends
Criterias for curves
 3 basic representation strategies:
 Explicit: y = mx + b
 Implicit: ax + by + c = 0
 Parametric: P = P0 + t (P1 - P0)
Curve Representations
 More degrees of freedom
 Directly transformable
 Dimension independent
 No infinite slope problems
 Separates dependent and independent variables
 Inherently bounded
 Easy to express in vector and matrix form
 Common form for many curves and surfaces
Advantages of parametric forms
 Spline curve
 Convex hull
 Control graph
 Piecewise cubic splines
Spline Representations
 Smooth curve that is defined by a sequence of points.
Spline curve
Interpolating spline Approximating spline
 Smallest polygon that encloses all points
Convex hull
Interpolating spline Approximating spline
Convex hull
 Polyline through sequence of points
Control graph
Interpolating spline Approximating spline
Control graph
Piecewise cubic splines
Segments
Interpolation
 Very bad locality
 Tend to oscillate
 Small changes may result in
catastrophe
 Bad controllability
 All you know is, that it
interpolates the points
 High effort to evaluate curve
 Imagine a curve with several
million given points
Interpolation vs Approximation
Approximation
 Unlike interpolation the points are
not necessarily interpolated
 Points give a means for
controlling of where the curve
goes
 Often used when creating the
design of new (i.e. non-existing)
things
 No strict shape is given
 Parametric continuity Cx
 Only P is continuous: C0
 Positional continuity
 P and first derivative dP/du are continuous: C1
 Tangential continuity
 P + first + second: C2
 Curvature continuity
 Geometric continuity Gx
 Only directions have to match
Continuity in Curves - Representation
Parametric continuity Cx - Order of continuity
Zero-order parametric continuity
C0: P(1) = Q(0).
Endpoint of P(u) coincides with start point Q(v).
P(u) Q(v)
First order parametric continuity
C1: dP(1)/du = dQ(0)/dv.
Direction of P(1) coincides with direction of Q(0).
First order parametric continuity gives a smooth
curve. Sometimes good enough, sometimes not.
P(u) Q(v)
Contd..
Second order parametric continuity
C2: d2P(1)/du2 = d2Q(0)/dv2.
Curvatures in P(1) and Q(0) are equal.
P(u) Q(v)
Geometric continuity Gx
 Here the vectors are exactly equal.
 It suffices to require that the directions are the same.
First order geometric continuity:
G1: dP(1)/du =  dQ(0)/dv with  >0.
Direction of P(1) coincides with direction Q(0).
P(u) Q(v)
THANK YOU

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Curves

  • 2. Many technological applications  Design of products (e.g. CAD)  Calculation of the path for a robot Design of fonts  Large sized fonts must be smooth Interpolating measuring data Approximating measuring data Why designing curves?
  • 3. Controllability  Changes must be predictable in effect  Intuitive to use for the designer Locality  Local changes should stay local Smoothness  No sharp bends Criterias for curves
  • 4.  3 basic representation strategies:  Explicit: y = mx + b  Implicit: ax + by + c = 0  Parametric: P = P0 + t (P1 - P0) Curve Representations
  • 5.  More degrees of freedom  Directly transformable  Dimension independent  No infinite slope problems  Separates dependent and independent variables  Inherently bounded  Easy to express in vector and matrix form  Common form for many curves and surfaces Advantages of parametric forms
  • 6.  Spline curve  Convex hull  Control graph  Piecewise cubic splines Spline Representations
  • 7.  Smooth curve that is defined by a sequence of points. Spline curve Interpolating spline Approximating spline
  • 8.  Smallest polygon that encloses all points Convex hull Interpolating spline Approximating spline Convex hull
  • 9.  Polyline through sequence of points Control graph Interpolating spline Approximating spline Control graph
  • 11. Interpolation  Very bad locality  Tend to oscillate  Small changes may result in catastrophe  Bad controllability  All you know is, that it interpolates the points  High effort to evaluate curve  Imagine a curve with several million given points Interpolation vs Approximation Approximation  Unlike interpolation the points are not necessarily interpolated  Points give a means for controlling of where the curve goes  Often used when creating the design of new (i.e. non-existing) things  No strict shape is given
  • 12.  Parametric continuity Cx  Only P is continuous: C0  Positional continuity  P and first derivative dP/du are continuous: C1  Tangential continuity  P + first + second: C2  Curvature continuity  Geometric continuity Gx  Only directions have to match Continuity in Curves - Representation
  • 13. Parametric continuity Cx - Order of continuity Zero-order parametric continuity C0: P(1) = Q(0). Endpoint of P(u) coincides with start point Q(v). P(u) Q(v) First order parametric continuity C1: dP(1)/du = dQ(0)/dv. Direction of P(1) coincides with direction of Q(0). First order parametric continuity gives a smooth curve. Sometimes good enough, sometimes not. P(u) Q(v)
  • 14. Contd.. Second order parametric continuity C2: d2P(1)/du2 = d2Q(0)/dv2. Curvatures in P(1) and Q(0) are equal. P(u) Q(v)
  • 15. Geometric continuity Gx  Here the vectors are exactly equal.  It suffices to require that the directions are the same. First order geometric continuity: G1: dP(1)/du =  dQ(0)/dv with  >0. Direction of P(1) coincides with direction Q(0). P(u) Q(v)