Shifting an integral I have posted my initial question question "Arc-Length parameterization of a cubic bezier curve" here.
I was a bit confused with the mathematics but now i have understood most of it, only one question remains which i think is better to posted in the Mathematics forums.
The paper i use as a basic, describes the calculation of the Arc-Length of a curve segment as follows:
$l_i = \int_{t_i}^{t_{i+1}}\sqrt{(x'(t))^2 + (y'(t))^2 + (z'(t))^2}dt$, where i is the i varies from $0$ to $n-1$ and $n$ is is the number of segments in the curve. Therefore the total Arc-Length of the curve would be $\sum_{i=0}^{n-1}l_1$
Now to calculate that integral and implement it, i found a website which tells me to use the Gauss Quadrature and shows:$\int_{0}^{z}\sqrt{(x'(t))^2 + (y'(t))^2 + (z'(t))^2}dt = \frac{z}{2} [C_1 f(\frac{z}{2} t_1+\frac{z}{2})+\cdots+C_n f(\frac{z}{2} t_n+\frac{z}{2})]$,  where z is from $0$ to a value smaller or equal to $1$.
In order to implement it, the second solution seems what want to go for. The problem is it always calculates the Arc-length for $0$ to the time specified in $z$ of the original curve.
My question can i use the second formula or modify it so that i can use $\int_{t_i}^{t_{i+1}}$ where $t_i$ would be the time of a segment point and $t_{i+1}$ the time of the next segment point on the bezier curve.
 A: For a brief answer, put $l_i = \displaystyle \int_{t_i}^{t_{i+1}} \| M'(t)\| \ \mathrm dt$, $L_i = \displaystyle \sum_{k \mathop = 0}^i l_k$. Then you want $l_i$ from the given $L_i$. 
One way to do this is via $l_i = L_{i+1} - L_i$.
Maybe the other answer is what you are looking for, but I suspect that you may not want to reparametrise your integral as this does not actually help you calculating the desired quantities from your given primitive.
You could have a look at the Fundamental Theorem of Calculus.
A: If I understand correctly, you need to send the interval $(t_i,t_{i+1})$ to $(0,z)$ where $0 < z \le 1$. So, basically you need to send the interval to the origin and then rescale it (or viceversa).
Traslating the intervals. The left side of the intervals is $t_i\,$ (assuming $t_i < t_{i+1}$). Taking the change of variables $s = t - t_i$,
$$
\int_{t_i}^{t_{i+1}} \|M'(t)\| dt = \int_{0}^{t_{i+1}-t_i} \|M'(s + t_i) \| ds,
$$
where $M(t) = \big(x(t),y(t),z(t)\big)$ is your parametrized curve.
Rescaling the intervals. The length of the intervals is $t_{i+1} - t_i$, and you need to rescale it to be $z$. Taking the change of variables $x = \frac{z}{t_{i+1} - t_i}s$,
$$
\int_{t_i}^{t_{i+1}} \|M'(t)\| dt = \int_{0}^{t_{i+1}-t_i} \|M'(s + t_i) \| ds = \frac{t_{i+1} - t_i}{z} \int_0^z \big\|M'\big(\tfrac{t_{i+1} - t_i}{z} x + t_i\big) \big\|dx,
$$
and you are done.
Note that the last step might not be necessary if $0 < t_1 < \ldots < t_n \le 1$.
A: The Gaussian Quadrature is in the interval [-1,1] and to map any interval [a,b] to that simply use:
$\int_a^bf(x)dx = \frac{b-a}2 \simeq \frac{b-a}{2}[C_1 * f(\frac{b-a}2 * t_1 + \frac{b+a}2) + ... + C_n * f(\frac{b-a}2 * t_n + \frac{b+a}2)]$
Where $C_1 ... C_n$ are the weights and $t_1 ... t_n$ are the abscissae from the those Tables
