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      Returning to the examples, Figure 1.3 depicts a quadratic (i.e. p = 2) B-spline curve, where the knot-vector was chosen as:

      [1.11] images

      This knot-vector is characterized as uniform since all interior knots are equally spaced. The influence of the knot-vector is shown in Figure 1.4, where we only changed one knot of the initial knot-vector such that:

      [1.12] images

      This new knot-vector is characterized as non-uniform because the interior knots are not equally spaced.

      1.2.2.2. B-spline basis functions

Schematic illustration of examples of B-spline basis functions of different degrees.

      [1.14] images

      Again, we refer to Piegl and Tiller (1997) for efficient algorithms regarding these calculations.

      1.2.2.3. NURBS curves

      The NURBS basis functions, denoted by image in the following, are defined from a B-spline basis of the same degree image. In order to do so, it is necessary to introduce the weights wi for the control points xi. More precisely, the piecewise rational functions image read as follows:

      Then, NURBS curves are defined similarly to those in [1.9]:

      [1.16] images

      Consequently, a NURBS curve takes the same inputs as a B-spline curve,

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