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# Parametric splines

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Hi; Did anyone implemented (or had the formulas) a program to, given a set of N points in 3d space, calculate the N-1 parametric equations for the segments? thanx

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depends on how you want to interpolate between those points of yours doesnt it? more information would be nice, like are the point evenly spaced?

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Well, its something like this: i have a camera, and i want it to follow a path....so i will choose some points from my world , and then the camera would pass in each point, in a curved path, like splines from MAX...the points are not linearly distributed, they are random....

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The most natural algorithm for this would be a natural cubic spline. Searching for that might find something useful. There are probably a lot of libraries, as well, that implement various cubic splines, NURBS, etc. I wrote my own to do various cubic splines about a year ago, but I don''t have it with me right now, and it probably could use some cleaning up, anyway.

int Agony() { return *((int*)0); }    Mwahaha... >8)

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Given 4 points, (p0, p1, p2, p3), and the parameter t, in the range of [0,1] and denoting an arbitrary point between p1 and p2:
P = (p3 - p2) - (p0 - p1)Q = (p0 - p1) - PR = p2 - p0S = p1return P*t*t*t + Q*t*t + R*t + S

It''s called cubic interpolation and requires 4 control points on the curve to calculate.

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@vertexnomral

i find that method works not very good. although the path is constant, the speed is lower close to the control points or something.

heres my personal favorite:

multiply this matrix:

[0, 1, 0, 0]
[-1/2, 0, 1/2, 0]
[1, -5/2, 2, -1/2]
[-1/2, 3/2, -3/2, 1/2]

with a matrix looking like this:
(cp stands for contol point)

[cp0x, cp0y, cp0z]
[cp1x, cp1y, cp1z]
[cp2x, cp2y, cp2z]
[cp3x, cp3y, cp3z]

the outcome matrix looks like this:

[c0x, c1x, c2x, c3x]
[c0y, c1y, c2y, c3y]
[c0z, c1z, c2z, c3z]

which are the coefficients for a third order curve, the number denoting the power of each term, ie x = c0x + c1x*i + c2x*i^2 + c3x*i^3, etc.

''i'' being in the range 0-1.

by far the best interpolation method ive come across, and all it needs as input are four points, you dont have to worry about setting directions or anything.

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Thanx guys!! i got it now...

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quote:
Original post by Eelco
@vertexnomral

[0, 1, 0, 0]
[-1/2, 0, 1/2, 0]
[1, -5/2, 2, -1/2]
[-1/2, 3/2, -3/2, 1/2]

by far the best interpolation method ive come across, and all it needs as input are four points, you dont have to worry about setting directions or anything.

Funny ! Can you explain this a bit more ?
What is the matrix for a 5 control points spline ?

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quote:

Funny ! Can you explain this a bit more ?

yes, i can.

what do you know about the curve C(i) = c0 + c1*i + c2*i^2 + c3*i^3 we want?

we want C(0) to be cp1
we want C(1) to be cp2

so:

C(0) = cp1
C(1) = cp2

we have four unknown, our coefficients c0 to c3, so we need two more equations. we havnt yet defined anything about the direction, or derivative of our curve.

(cp2-cp0)/2 is the average gradient between these points. cp1 lies in the middle of them, so this would be a nice candidate for the derivative of C at point cp1 aka i=0. so:

C''(0) = (cp2-cp0)/2

and following the same logic:

C''(1) = (cp3-cp1)/2

yay, four equations.

c0*1 + c1*0 + c2*0 + c3*0 = cp1
c0*1 + c1*1 + c2*1 + c3*1 = cp2
c0*0 + c1*1 + c2*0 + c3*0 = (cp2-cp0)/2
c0*0 + c1*1 + c2*2 + c3*3 = (cp3-cp1)/2

omg, a martix!!11

if you rewrite that a bit you have the matrix that transforms your constants into your control points. invert it, and you get the opposite.

quote:

What is the matrix for a 5 control points spline ?

i dont think a 5-control point spline would make much sense, since your control points wouldnt lie symetricly spaced around your interval. 6 control point would though. if you pick 6 convenient relations between your function on the interval 0-1 and these 6 control points, you can apply the same logic to that, and get a 6x6 matrix.

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hey thats weird...

my last post didnt increase the number of posts, not did it bump this thread..

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