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The “B” in B-spline refers to the fact that a segment \({\bf{x}}\left( t \right)\)may be written in terms of a basis matrix, \(\,{M_S}\) , in a form similar to a Bézier curve. That is,

\({\bf{x}}\left( t \right) = G{M_S}{\bf{u}}\left( t \right)\)for \(\,0 \le t \le 1\)

where \(G\) is the geometry matrix \(\,\left( {{{\bf{p}}_{\bf{0}}}\,\,\,\,{{\bf{p}}_{{\bf{1}}\,\,\,}}\,{{\bf{p}}_{\bf{2}}}\,\,\,{{\bf{p}}_{\bf{3}}}} \right)\)and \({\bf{u}}\left( {\bf{t}} \right)\) is the column vector \(\left( {1,\,\,t,\,\,{t^2},\,{t^3}} \right)\) . In a uniform B-spline, each segment uses the same basis matrix \(\,{M_S}\), but the geometry matrix changes. Construct the basis matrix \(\,{M_S}\) for \({\bf{x}}\left( t \right)\).

Short Answer

Expert verified

The basis matrix is \({M_S} = \left( {\begin{array}{{}}1&{ - 3}&3&{ - 1}\\4&0&{ - 6}&3\\1&3&3&{ - 3}\\0&0&0&1\end{array}} \right)\).

Step by step solution

01

Write matrix \({\bf{x}}\left( t \right) = G{M_S}{\bf{u}}\left( t \right)\)for control points\(\,\left( {{{\bf{p}}_{\bf{0}}}\,\,\,\,{{\bf{p}}_{{\bf{1}}\,\,\,}}\,{{\bf{p}}_{\bf{2}}}\,\,\,{{\bf{p}}_{\bf{3}}}} \right)\)

The matrix \({\rm{x}}\left( t \right) = G{M_S}{\rm{u}}\left( t \right)\)is given as \({\bf{x}}\left( t \right) = \frac{1}{6}\left( {\left( {1 - 3t + 3{t^2} - {t^3}} \right){{\bf{p}}_o} + \left( {4 - 6{t^2} + 3{t^3}} \right){{\bf{p}}_1} + \left( {1 + 3t + 3{t^2} - 3{t^3}} \right){{\bf{p}}_2} + {t^3}{{\bf{p}}_3}} \right)\) for \(0 \le t \le 1\) .

02

Step 2:Write vector of weights of \({\bf{x}}\left( t \right)\)

The weighted vector of \({\rm{x}}\left( t \right)\)is\(\frac{1}{6}\left( {\begin{array}{{}}{1 - 3t + 3{t^2} - {t^3}}\\{4 - 6{t^2} + 3{t^3}}\\{1 + 3t + 3{t^2} - 3{t^3}}\\{\,\,\,\,\,\,{t^3}}\end{array}} \right)\).

03

The weighted matrix

Factor the weighted vector as\({M_S}{\bf{u}}\left( t \right)\), where\({\bf{u}}\left( t \right)\)is the column vector involving ascending powers of t as shown below:

\({M_S}{\bf{u}}\left( t \right) = \left( {\begin{array}{{}}1&{ - 3}&3&{ - 1}\\4&0&{ - 6}&3\\1&3&3&{ - 3}\\0&0&0&1\end{array}} \right)\left( \begin{array}{l}1\\t\\{t^2}\\{t^3}\end{array} \right)\)

04

Compare and write \({M_S}\)

The basis matrix is \({M_S} = \left( {\begin{array}{{}}1&{ - 3}&3&{ - 1}\\4&0&{ - 6}&3\\1&3&3&{ - 3}\\0&0&0&1\end{array}} \right)\).

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Most popular questions from this chapter

In Exercises 21–24, a, b, and c are noncollinear points in\({\mathbb{R}^{\bf{2}}}\)and p is any other point in\({\mathbb{R}^{\bf{2}}}\). Let\(\Delta {\bf{abc}}\)denote the closed triangular region determined by a, b, and c, and let\(\Delta {\bf{pbc}}\)be the region determined by p, b, and c. For convenience, assume that a, b, and c are arranged so that\(\left[ {\begin{array}{*{20}{c}}{\overrightarrow {\bf{a}} }&{\overrightarrow {\bf{b}} }&{\overrightarrow {\bf{c}} }\end{array}} \right]\)is positive, where\(\overrightarrow {\bf{a}} \),\(\overrightarrow {\bf{b}} \)and\(\overrightarrow {\bf{c}} \)are the standard homogeneous forms for the points.

23. Let p be any point in the interior of\(\Delta {\bf{abc}}\), with barycentric coordinates\(\left( {r,s,t} \right)\), so that

\(\left[ {\begin{array}{*{20}{c}}{\overrightarrow {\bf{a}} }&{\overrightarrow {\bf{b}} }&{\overrightarrow {\bf{c}} }\end{array}} \right]\left[ {\begin{array}{*{20}{c}}r\\s\\t\end{array}} \right] = \widetilde {\bf{p}}\)

Use Exercise 21 and a fact about determinants (Chapter 3) to show that

\(r = \left( {area of \Delta pbc} \right)/\left( {area of \Delta abc} \right)\)

\(s = \left( {area of \Delta apc} \right)/\left( {area of \Delta abc} \right)\)

\(t = \left( {area of \Delta abp} \right)/\left( {area of \Delta abc} \right)\)

In Exercises 1-6, determine if the set of points is affinely dependent. (See Practice Problem 2.) If so, construct an affine dependence relation for the points.

1.\(\left( {\begin{aligned}{{}}3\\{ - 3}\end{aligned}} \right),\left( {\begin{aligned}{{}}0\\6\end{aligned}} \right),\left( {\begin{aligned}{{}}2\\0\end{aligned}} \right)\)

Question 4: Repeat Exercise 2 where \(m\) is the minimum value of \(f\) on \(S\) instead of the maximum value.

Question: In Exercises 15-20, write a formula for a linear functional f and specify a number d, so that \(\left( {f:d} \right)\) the hyperplane H described in the exercise.

Let H be the column space of the matrix \(B = \left( {\begin{array}{*{20}{c}}{\bf{1}}&{\bf{0}}\\{ - {\bf{4}}}&{\bf{2}}\\{\bf{7}}&{ - {\bf{6}}}\end{array}} \right)\). That is, \(H = {\bf{Col}}\,B\).(Hint: How is \({\bf{Col}}\,B\) related to Nul \({B^T}\)? See section 6.1)

Question: 13. Suppose \(\left\{ {{{\rm{v}}_{\rm{1}}}{\rm{,}}{{\rm{v}}_{\rm{2}}}{\rm{,}}{{\rm{v}}_{\rm{3}}}} \right\}\) is a basis for \({\mathbb{R}^3}\). Show that Span \(\left\{ {{{\rm{v}}_{\rm{2}}} - {{\rm{v}}_{\rm{1}}},{{\rm{v}}_{\rm{3}}} - {{\rm{v}}_{\rm{1}}}} \right\}\) is a plane in \({\mathbb{R}^3}\). (Hint: What can you say about \({\rm{u}}\) and \({\rm{v}}\)when Span \(\left\{ {{\rm{u,v}}} \right\}\) is a plane?)

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