[scilab-Users] finding polynomials of best fit

[Mathieu Dubois]

Hello,
On 08/16/2011 04:50 PM, beemc2 at aol.com wrote:
> I'm a first-year engineering student working with a professor on 
> stereoscopic cameras, and one of my assignments is to determine lens 
> distortion in the cameras and put together an algorithm to correct 
> it.  My basic plan is take photos of a known grid of dots and put 
> together a list of their actual positions and their positions as they 
> appear in the image, the use some form of statistical regression 
> technique to give myself a good approximation of the radial distortion 
> as a function of distance from the center.  (a perfect camera with no 
> distortion should give a linear relation between the real position and 
> the position in the image.)  Since I don't have much information on 
> the geometry of the lenses themselves, i can't solve the problem 
> analytically.  I want to just get the function as a fourth- or 
> fifth-degree Taylor polynomial (I'm told that the fourth term is the 
> highest one that will likely be significant).
> So is there a decent function in Scilab that will allow me to find a 
> polynomial of best fit for a given set of data?  There's something 
> similar in Excel but I'd rather not have to go through the hassle of 
> exporting and then re-importing the the data, and I also might need it 
> later for other applications.
> YMW
Such functions are found in OpenCV so you may look at SIVP: 
http://www.scilab.org/products/modules/pem/sivp (I don't know if it's in).