With cameras $C_1$ and $C_2$ with respective camera matrices $P_1^{\{W\}} = \begin{bmatrix} R_1 & t_1 \\ \mathbf{0} & 1 \end{bmatrix}$ and $P_2^{\{W\}} = \begin{bmatrix} R_2 & t_2 \\ \mathbf{0} & 1 \end{bmatrix}$, where $W$ denotes the world frame, we want to find the transformation matrix $P_1^{\{2\}}$ that is the transformation from $C_1$ to $C_2$. You can just use $P_1^{\{W\}}$ and $P_2^{\{W\}}$ to find this, since you know they are both given in the same frame. The basic process is to transform from $C_1$ to $W$ to $C_2$.
Step 1:
Given a point $q^{\{1\}}$ in $C_1$, the the world coordinate is given by $q^{\{W\}} = t_1 + R_1 q^{\{1\}}$
Step 2:
Given a point $q^{\{W\}}$ in $W$, the $C_2$ coordinate is given by $q^{\{2\}} = R_2^{-1} (q^{\{W\}} - t_2)$
Step 3:
Combine steps 1 and 2. You have
$$ q^{\{2\}} = R_2^{-1} (q^{\{W\}} - t_2) $$
$$ q^{\{2\}} = R_2^{-1} ((t_1 + R_1 q^{\{1\}}) - t_2) $$
$$ q^{\{2\}} = R_2^{-1} (R_1 q^{\{1\}} + t_1 - t_2) $$
$$ q^{\{2\}} = R_2^{-1} R_1 q^{\{1\}} + R_2^{-1} (t1-t2) $$
which you can write as
$$ q^{\{2\}} = P_1^{\{2\}} q^{\{1\}} $$
where
$$
P_1^{\{2\}} = \begin{bmatrix} R_2^{-1} R_1 & R_2^{-1} (t_1 - t_2) \\ \mathbf{0} & 1\end{bmatrix}
$$
If you'd like to simplify with notation a bit, and knowing that since $R_2$ is orthonormal that $R_2^{-1} = R_2^T$, you can write
$$
P_1^{\{2\}} = \begin{bmatrix} R_2^{T} R_1 & t_{12} \\ \mathbf{0} & 1\end{bmatrix}
$$
where $t_{12} = t_1^{\{2\}} - t_2^{\{2\}}$.
I can answer this:
What is the affine transformation converting world coordinates to camera coordinates? (camera world coordinates: $c=(c_x,c_y,c_z)^\top$, visual center world coordinates, $v=(v_x,v_y,v_z)^\top$)
I'm assuming the traditional camera image coordinates (before projection) having $z$ drilling "into" the image, $x$ pointing from left to right, and $y$ pointing downward.
Now let's track how the axes must be rotated without translation:
1. the new $z$ axis ($z'$) will point along $v-c$.
1. the new $x$ axis ($x'$) is perpendicular to $z$ and $z'$
1. the new $y$ axis ($y'$) is perpendicular to $x'$ and $z'$.
You can find three vectors that point along the new axes in world coordinates, normalize them, then put them in the rows of a $3\times 3$ matrix $R$: this converts world coordinates to rotated camera orientation.
Finally, if you know the translation $t$ in world coordinates (it would be $(-10,-10,-10)^\top$ to translate to the camera's position in world coordinates) then the translation in camera coordinates is $t'=Rt$
Let's actually carry this out for your example. Let's work on a triad of orthogonal vectors:
$z'=(-1,-1,-1)$, pointing in the direction the camera must face.
$x'=z'\times z=(-1,1,0)^\top$
$y'=z'\times x'=(1,1,-2)^\top$
Normalizing these and using them as the rows of a matrix you get:
$$
R=\frac{1}{\sqrt{6}}\begin{bmatrix}
-\sqrt{3}&\sqrt{3}&0\\
1&1&-2\\
-\sqrt{2}&-\sqrt{2}&-\sqrt{2}
\end{bmatrix}
$$
Then $t'=Rt=(0,0,10\sqrt{3})$.
Notice that the angle of declination is an odd angle near $35^\circ$ rather than exactly $45^\circ$. (I had a hard time seeing this at first, but if you draw a cube and check the angle between $(1,1,0)$ and $(1,1,1)$ you'll see what I mean.)
Now you've converted world coordinates to rotated frame that is aligned with your camera's frame, but differs by a translation.
This gives you the resulting affine transformation $\begin{bmatrix}R&t'\\0_{1\times 3}&1\end{bmatrix}$
which carries world coordinates to camera coordinates.
As a sanity check, you can confirm that the world's origin maps to camera $(0,0,10\sqrt{3})^\top$ and that the world camera location $(10,10,10)$ now maps to the camera's origin. A third check of your choice should be sufficient to convince you this is the right $R$ and $t'$.
One caveat: I'm not 100% sure the step with $z\times z'$ is always in this order. I picked it this way on this occasion because it gave the right orientation for $x'$ and $y'$ in the end. Hopefully that is all consistent, but maybe there is some sign ambiguity after all.
The second question is how to construct the "UP" vector.
I don't understand what you are asking. If you mean the camera coordinates for the direction of the world $z$-axis, then that would just be $R(0,0,1)^\top +t'$.
Finally, I will have to rotate camera as well from "landscape" to "portrait" orientation .
I'm interpreting this to mean that you'd want to rotate the image plane so that the $y$-axis is horizontal, which could be done with a $\pi/4$ rotation in either way around the camera $z$-axis.
This transformation should be entirely obvious:
$$U=
\begin{bmatrix}
0&-1&0\\
1&0&0\\
0&0&1\end{bmatrix}
$$
$U$ gives the rotation in the clockwise direction around the $z$ axis (which would look to be counterclockwise if you are looking up the $z$ axis into the picture) and $U^\top$ would give the rotation in the other direction.
Best Answer
Assuming your matrix is an extrinsic parameter matrix of the kind described in the Wikipedia article, it is a mapping from world coordinates to camera coordinates. So, to find the position $C$ of the camera, we solve
$$\begin{align*}0 &= RC + T\\ C &= -R^T T \approx (-2.604, 2.072, -0.427).\end{align*}$$
The orientation of the camera is given simply by $R^T.$ So if the "in" axis is the z-axis, for instance, then the vector pointing in the direction the camera is pointing is
$$R^T \left[\begin{array}{c}0\\0\\1\end{array}\right] = (0.718, -0.595, 0.36).$$