<div>Hi Luis,</div>
<div> </div>
<div>Thanx a lot for the reply ..... i really appreciate it.</div>
<div> </div>
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<div>You wrote: </div>
<div><br>If you set a linear sequence of 3D points as the Source landmarks,<br>(eg. a sequence of points regularly spaced along the X axis).<br>and the 3D points that you arre trying to approximate, as the<br>TargetLandmarks, then you will be able to generate the approximating
<br>spline by calling Transform() with points that are in the input<br>space of the X axis.<br><br>That is, by using a sequence of input point with components:<br><br> p[ S, 0, 0 ]<br><br>you will generate transformed points along your curve, and they
<br>will be parameterized by "S".<br> </div>
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<p>I dont quite understand what you mean by this. All i have is a set of raw 3D points and i dont want to assume anything about the order of the points ( if that is what you meant by a linear sequence of 3D points ). I dont see a way to parameterize them ( for example i am afraid the data cannot be parameterized by arc length as the points are not properly ordered ).
</p>
<div>It would help me understand your idea better, if you could point me to some examples --- articles/code/images.</div>
<div> </div>
<div><br> Regards,<br><br><br> Luis<br><br><br>-----------------<br>Deepak Roy wrote:<br>> Hello,<br>><br>> I have a set of noisy/scattered 3D data points ( XYZ ) which ideally<br>> should belong to a curve in 3D space.
<br>><br>> I want to use a smoothing/approximation spline to approximate this 3D<br>> curve.<br>><br>> All the references/books on splines that i found deal with spline<br>> approximation in 2D and i am not able to find any reference which
<br>> computes an approximating spline curve in 3D space.<br>><br>> I have done a few experiments with the 2D smoothing spline in matlab. I<br>> extended this to 3D by fitting two splines --- for ZX data and ZY data.
<br>> Then i combined these two splines together to achieve a 3D approximating<br>> spline curve. But the problem with this is that it is done through<br>> projections, and consequently if there is more than one value at the
<br>> same data site then the smoothing spline gives a weighted average of the<br>> values ---- and this is not what is desired.<br>><br>> Is there a way to approximate scattered/noisy 3D data points using a<br>
> spline in ITK ??? Or can anyone throw light on how this is done ???<br>><br>> I would really appreciate the help.<br>><br>> Thanks in advance.<br>><br>> Regards,<br>><br>> Deepak<br>><br>>
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