If All the Points Lie On a Plane, Then Why Does the Linear Mapping Reduce to …?
I previously asked a question with regards to what the matrix $mathrm{H}_{3 times 3}$ is/represents in the following textbook excerpt:
In applying projective geometry to the imaging process, it is customary to model the world as a $3$D projective space, equal to $mathbb{R}^3$ along with points at infinity. Similarly the model for the image is the $2$D projective plane $mathbb{P}^2$. Central projection is simply a map from $mathbb{P}^3$ to $mathbb{P}^2$. If we consider points in $mathbb{P}^3$ written in terms of homogeneous coordinates $(mathrm{X}, mathrm{Y}, mathrm{Z}, mathrm{T})^T$ and let the centre of projection be the origin $(0, 0, 0, 1)^T$, then we see that the set of all points $(mathrm{X}, mathrm{Y}, mathrm{Z}, mathrm{T})^T$ for fixed $mathrm{X}$, $mathrm{Y}$, and $mathrm{Z}$, but varying $mathrm{T}$ form a single ray passing through the point centre of projection, and hence all mapping to the same point. Thus, the final coordinates of $(mathrm{X}, mathrm{Y}, mathrm{Z}, mathrm{T})$ is irrelevant to where the point is imaged. In fact, the image point is the point in $mathbb{P}^2$ with homogeneous coordinates $(mathrm{X}, mathrm{Y}, mathrm{Z})^T$. Thus, the mapping may be represented by a mapping of $3$D homogeneous coordinates, represented by a $3 times 4$ matrix $mathrm{P}$ with the block structure $P = [I_{3 times 3} | mathbf{0}_3]$, where $I_{3 times 3}$ is the $3 times 3$ identity matrix and $mathbf{0}_3$ a zero 3-vector. Making allowance for a different centre of projection, and a different projective coordinate frame in the image, it turns out that the most general imaging projection is represented by an arbitrary $3 times 4$ matrix of rank $3$, acting on the homogeneous coordinates of the point in $mathbb{P}^3$ mapping it to the imaged point in $mathbb{P}^2$. This matrix $mathrm{P}$ is known as the camera matrix.
In summary, the action of a projective camera on a point in space may be expressed in terms of a linear mapping of homogeneous coordinates as
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{P}_{3 times 4}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{Z} \
mathrm{T} \ end{bmatrix}$$
Furthermore, if all the points lie on a plane (we may choose this as the plane $mathrm{Z} = 0$) then the linear mapping reduces to
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{H}_{3 times 3}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{T} \ end{bmatrix}$$
which is a projective transformation.
It is now clear to me that I didn't understand this section properly. Specifically, it is not clear to me why choosing the plane $mathrm{Z} = 0$ means that the linear mapping
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{P}_{3 times 4}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{Z} \
mathrm{T} \ end{bmatrix}$$
reduces to
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{H}_{3 times 3}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{T} \ end{bmatrix}$$
More specifically, I don't understand why setting $mathrm{Z} = 0$ necessitates getting rid of the entirety of the 3rd column of $mathrm{P}_{3 times 4}$, which gets us $mathrm{H}_{3 times 3}$ (as per bounceback's answer in the aforementioned question)?
And I'm also wondering whether choosing the plane $mathrm{Z} = 5$ (or any other plane) instead of $mathrm{Z} = 0$ would still reduce the transformation from
$$begin{bmatrix} x \ y \ w end{bmatrix} = mathrm{P}_{3 times 4} begin{bmatrix} mathrm{X} \ mathrm{Y} \ 0 \ mathrm{T} \ end{bmatrix}$$
to
$$begin{bmatrix} x \ y \ w end{bmatrix} = mathrm{H}_{3 times 3} begin{bmatrix} mathrm{X} \ mathrm{Y} \ mathrm{T} \ end{bmatrix},$$
where
$$mathrm{H}_{3 times 3} = begin{bmatrix}1&0&0\0&1&0\0&0&0end{bmatrix}$$
?
I would greatly appreciate it if people could please take the time to clarify this.
linear-algebra transformation projective-geometry projective-space computer-vision
add a comment |
I previously asked a question with regards to what the matrix $mathrm{H}_{3 times 3}$ is/represents in the following textbook excerpt:
In applying projective geometry to the imaging process, it is customary to model the world as a $3$D projective space, equal to $mathbb{R}^3$ along with points at infinity. Similarly the model for the image is the $2$D projective plane $mathbb{P}^2$. Central projection is simply a map from $mathbb{P}^3$ to $mathbb{P}^2$. If we consider points in $mathbb{P}^3$ written in terms of homogeneous coordinates $(mathrm{X}, mathrm{Y}, mathrm{Z}, mathrm{T})^T$ and let the centre of projection be the origin $(0, 0, 0, 1)^T$, then we see that the set of all points $(mathrm{X}, mathrm{Y}, mathrm{Z}, mathrm{T})^T$ for fixed $mathrm{X}$, $mathrm{Y}$, and $mathrm{Z}$, but varying $mathrm{T}$ form a single ray passing through the point centre of projection, and hence all mapping to the same point. Thus, the final coordinates of $(mathrm{X}, mathrm{Y}, mathrm{Z}, mathrm{T})$ is irrelevant to where the point is imaged. In fact, the image point is the point in $mathbb{P}^2$ with homogeneous coordinates $(mathrm{X}, mathrm{Y}, mathrm{Z})^T$. Thus, the mapping may be represented by a mapping of $3$D homogeneous coordinates, represented by a $3 times 4$ matrix $mathrm{P}$ with the block structure $P = [I_{3 times 3} | mathbf{0}_3]$, where $I_{3 times 3}$ is the $3 times 3$ identity matrix and $mathbf{0}_3$ a zero 3-vector. Making allowance for a different centre of projection, and a different projective coordinate frame in the image, it turns out that the most general imaging projection is represented by an arbitrary $3 times 4$ matrix of rank $3$, acting on the homogeneous coordinates of the point in $mathbb{P}^3$ mapping it to the imaged point in $mathbb{P}^2$. This matrix $mathrm{P}$ is known as the camera matrix.
In summary, the action of a projective camera on a point in space may be expressed in terms of a linear mapping of homogeneous coordinates as
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{P}_{3 times 4}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{Z} \
mathrm{T} \ end{bmatrix}$$
Furthermore, if all the points lie on a plane (we may choose this as the plane $mathrm{Z} = 0$) then the linear mapping reduces to
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{H}_{3 times 3}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{T} \ end{bmatrix}$$
which is a projective transformation.
It is now clear to me that I didn't understand this section properly. Specifically, it is not clear to me why choosing the plane $mathrm{Z} = 0$ means that the linear mapping
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{P}_{3 times 4}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{Z} \
mathrm{T} \ end{bmatrix}$$
reduces to
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{H}_{3 times 3}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{T} \ end{bmatrix}$$
More specifically, I don't understand why setting $mathrm{Z} = 0$ necessitates getting rid of the entirety of the 3rd column of $mathrm{P}_{3 times 4}$, which gets us $mathrm{H}_{3 times 3}$ (as per bounceback's answer in the aforementioned question)?
And I'm also wondering whether choosing the plane $mathrm{Z} = 5$ (or any other plane) instead of $mathrm{Z} = 0$ would still reduce the transformation from
$$begin{bmatrix} x \ y \ w end{bmatrix} = mathrm{P}_{3 times 4} begin{bmatrix} mathrm{X} \ mathrm{Y} \ 0 \ mathrm{T} \ end{bmatrix}$$
to
$$begin{bmatrix} x \ y \ w end{bmatrix} = mathrm{H}_{3 times 3} begin{bmatrix} mathrm{X} \ mathrm{Y} \ mathrm{T} \ end{bmatrix},$$
where
$$mathrm{H}_{3 times 3} = begin{bmatrix}1&0&0\0&1&0\0&0&0end{bmatrix}$$
?
I would greatly appreciate it if people could please take the time to clarify this.
linear-algebra transformation projective-geometry projective-space computer-vision
add a comment |
I previously asked a question with regards to what the matrix $mathrm{H}_{3 times 3}$ is/represents in the following textbook excerpt:
In applying projective geometry to the imaging process, it is customary to model the world as a $3$D projective space, equal to $mathbb{R}^3$ along with points at infinity. Similarly the model for the image is the $2$D projective plane $mathbb{P}^2$. Central projection is simply a map from $mathbb{P}^3$ to $mathbb{P}^2$. If we consider points in $mathbb{P}^3$ written in terms of homogeneous coordinates $(mathrm{X}, mathrm{Y}, mathrm{Z}, mathrm{T})^T$ and let the centre of projection be the origin $(0, 0, 0, 1)^T$, then we see that the set of all points $(mathrm{X}, mathrm{Y}, mathrm{Z}, mathrm{T})^T$ for fixed $mathrm{X}$, $mathrm{Y}$, and $mathrm{Z}$, but varying $mathrm{T}$ form a single ray passing through the point centre of projection, and hence all mapping to the same point. Thus, the final coordinates of $(mathrm{X}, mathrm{Y}, mathrm{Z}, mathrm{T})$ is irrelevant to where the point is imaged. In fact, the image point is the point in $mathbb{P}^2$ with homogeneous coordinates $(mathrm{X}, mathrm{Y}, mathrm{Z})^T$. Thus, the mapping may be represented by a mapping of $3$D homogeneous coordinates, represented by a $3 times 4$ matrix $mathrm{P}$ with the block structure $P = [I_{3 times 3} | mathbf{0}_3]$, where $I_{3 times 3}$ is the $3 times 3$ identity matrix and $mathbf{0}_3$ a zero 3-vector. Making allowance for a different centre of projection, and a different projective coordinate frame in the image, it turns out that the most general imaging projection is represented by an arbitrary $3 times 4$ matrix of rank $3$, acting on the homogeneous coordinates of the point in $mathbb{P}^3$ mapping it to the imaged point in $mathbb{P}^2$. This matrix $mathrm{P}$ is known as the camera matrix.
In summary, the action of a projective camera on a point in space may be expressed in terms of a linear mapping of homogeneous coordinates as
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{P}_{3 times 4}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{Z} \
mathrm{T} \ end{bmatrix}$$
Furthermore, if all the points lie on a plane (we may choose this as the plane $mathrm{Z} = 0$) then the linear mapping reduces to
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{H}_{3 times 3}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{T} \ end{bmatrix}$$
which is a projective transformation.
It is now clear to me that I didn't understand this section properly. Specifically, it is not clear to me why choosing the plane $mathrm{Z} = 0$ means that the linear mapping
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{P}_{3 times 4}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{Z} \
mathrm{T} \ end{bmatrix}$$
reduces to
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{H}_{3 times 3}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{T} \ end{bmatrix}$$
More specifically, I don't understand why setting $mathrm{Z} = 0$ necessitates getting rid of the entirety of the 3rd column of $mathrm{P}_{3 times 4}$, which gets us $mathrm{H}_{3 times 3}$ (as per bounceback's answer in the aforementioned question)?
And I'm also wondering whether choosing the plane $mathrm{Z} = 5$ (or any other plane) instead of $mathrm{Z} = 0$ would still reduce the transformation from
$$begin{bmatrix} x \ y \ w end{bmatrix} = mathrm{P}_{3 times 4} begin{bmatrix} mathrm{X} \ mathrm{Y} \ 0 \ mathrm{T} \ end{bmatrix}$$
to
$$begin{bmatrix} x \ y \ w end{bmatrix} = mathrm{H}_{3 times 3} begin{bmatrix} mathrm{X} \ mathrm{Y} \ mathrm{T} \ end{bmatrix},$$
where
$$mathrm{H}_{3 times 3} = begin{bmatrix}1&0&0\0&1&0\0&0&0end{bmatrix}$$
?
I would greatly appreciate it if people could please take the time to clarify this.
linear-algebra transformation projective-geometry projective-space computer-vision
I previously asked a question with regards to what the matrix $mathrm{H}_{3 times 3}$ is/represents in the following textbook excerpt:
In applying projective geometry to the imaging process, it is customary to model the world as a $3$D projective space, equal to $mathbb{R}^3$ along with points at infinity. Similarly the model for the image is the $2$D projective plane $mathbb{P}^2$. Central projection is simply a map from $mathbb{P}^3$ to $mathbb{P}^2$. If we consider points in $mathbb{P}^3$ written in terms of homogeneous coordinates $(mathrm{X}, mathrm{Y}, mathrm{Z}, mathrm{T})^T$ and let the centre of projection be the origin $(0, 0, 0, 1)^T$, then we see that the set of all points $(mathrm{X}, mathrm{Y}, mathrm{Z}, mathrm{T})^T$ for fixed $mathrm{X}$, $mathrm{Y}$, and $mathrm{Z}$, but varying $mathrm{T}$ form a single ray passing through the point centre of projection, and hence all mapping to the same point. Thus, the final coordinates of $(mathrm{X}, mathrm{Y}, mathrm{Z}, mathrm{T})$ is irrelevant to where the point is imaged. In fact, the image point is the point in $mathbb{P}^2$ with homogeneous coordinates $(mathrm{X}, mathrm{Y}, mathrm{Z})^T$. Thus, the mapping may be represented by a mapping of $3$D homogeneous coordinates, represented by a $3 times 4$ matrix $mathrm{P}$ with the block structure $P = [I_{3 times 3} | mathbf{0}_3]$, where $I_{3 times 3}$ is the $3 times 3$ identity matrix and $mathbf{0}_3$ a zero 3-vector. Making allowance for a different centre of projection, and a different projective coordinate frame in the image, it turns out that the most general imaging projection is represented by an arbitrary $3 times 4$ matrix of rank $3$, acting on the homogeneous coordinates of the point in $mathbb{P}^3$ mapping it to the imaged point in $mathbb{P}^2$. This matrix $mathrm{P}$ is known as the camera matrix.
In summary, the action of a projective camera on a point in space may be expressed in terms of a linear mapping of homogeneous coordinates as
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{P}_{3 times 4}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{Z} \
mathrm{T} \ end{bmatrix}$$
Furthermore, if all the points lie on a plane (we may choose this as the plane $mathrm{Z} = 0$) then the linear mapping reduces to
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{H}_{3 times 3}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{T} \ end{bmatrix}$$
which is a projective transformation.
It is now clear to me that I didn't understand this section properly. Specifically, it is not clear to me why choosing the plane $mathrm{Z} = 0$ means that the linear mapping
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{P}_{3 times 4}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{Z} \
mathrm{T} \ end{bmatrix}$$
reduces to
$$begin{bmatrix}
x \
y \
w end{bmatrix} = mathrm{H}_{3 times 3}
begin{bmatrix}
mathrm{X} \
mathrm{Y} \
mathrm{T} \ end{bmatrix}$$
More specifically, I don't understand why setting $mathrm{Z} = 0$ necessitates getting rid of the entirety of the 3rd column of $mathrm{P}_{3 times 4}$, which gets us $mathrm{H}_{3 times 3}$ (as per bounceback's answer in the aforementioned question)?
And I'm also wondering whether choosing the plane $mathrm{Z} = 5$ (or any other plane) instead of $mathrm{Z} = 0$ would still reduce the transformation from
$$begin{bmatrix} x \ y \ w end{bmatrix} = mathrm{P}_{3 times 4} begin{bmatrix} mathrm{X} \ mathrm{Y} \ 0 \ mathrm{T} \ end{bmatrix}$$
to
$$begin{bmatrix} x \ y \ w end{bmatrix} = mathrm{H}_{3 times 3} begin{bmatrix} mathrm{X} \ mathrm{Y} \ mathrm{T} \ end{bmatrix},$$
where
$$mathrm{H}_{3 times 3} = begin{bmatrix}1&0&0\0&1&0\0&0&0end{bmatrix}$$
?
I would greatly appreciate it if people could please take the time to clarify this.
linear-algebra transformation projective-geometry projective-space computer-vision
linear-algebra transformation projective-geometry projective-space computer-vision
edited Dec 7 at 22:24
asked Nov 28 at 22:58
The Pointer
2,59321334
2,59321334
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2 Answers
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Lets write $P_{3times4}=begin{bmatrix}r_{11}&r_{12}&r_{13}&tau_1\ r_{21}&r_{22}&r_{23}&tau_2\r_{31}&r_{32}&r_{33}&tau_3\end{bmatrix}$
and call the $r$ terms $R_{3times3}$ and the $tau$ terms $tau_{3times1}$
thus $P_{3times 4}=[R,tau]$ (I dropped the dimension indices for brevity, but $tau$ is a column vector). Now $P_{3times 4} U_4$ becomes $R begin{bmatrix} X\Y\Z end{bmatrix} +Ttau=R U_3 +Ttau$. where I defined $U_3 =begin{bmatrix} X\Y\Z end{bmatrix}$.
Before dealing with the $Z=0$ case, lets look at the case where the plane does not pass through the origin: all points $U_3$ are on a plane, hence they obey $N^T U_3 =d$ where $N$ is a unit vector normal to the plane and $-dneq0$ is the distance of the origin from the plane. For this case we just have $1= {1over d} N^T U_3$ and therefor $$R U_3 +Ttau= R U_3 +(Ttau){1over d}(N^T U_3)$$ so that finally $P_{3times 4} U_4$ can be written as $[R +{Tover d}(tau N^T)]U_3$ and $H_{3times3}=[R+ {Tover d}(tau N^T)]$ is called a "Homography".
The degenerate case is where $d=0$ and which also contains the case $Z=0$ by setting $N^T=[0,0,1]$. In this case instead of pushing $1= {1over d} N^T U_3$ we push $0= N^T U_3$ . So $$R U_3 +Ttau = (R (I-N N^T) +tau N^T )(U_3+T N)$$ , In the specific case $N^T=[0,0,1]$ we have $left[R begin{bmatrix} 1&0&0\0&1&0\0&0&0end{bmatrix} +begin{bmatrix} 0&0&tau_x\0&0&tau_y\0&0&tau_zend{bmatrix}right]begin{bmatrix} X\Y\Tend{bmatrix}$
Thanks for the answer. Can you please explain what happened in the first line? I have many questions. (1) What does it mean to "split" $U_4$ into $U_3=begin{bmatrix} X \ Y \ Zend{bmatrix}$ and $T$? (2) What does the notation $[R,tau]$ mean? (3) What are $R$ and $tau$ supposed to be? (4) And so how does $P_{3times 4} U_4$ become $R U_3 +Ttau$? My apologies for all the questions.
– The Pointer
Dec 5 at 15:39
1
I just wrote $P_{3times3}=begin{bmatrix}r_{11}&r_{12}&r_{13}&tau_1\ r_{21}&r_{22}&r_{23}&tau_2\r_{31}&r_{32}&r_{33}&tau_3\end{bmatrix} $ and called the $r$ terms $R$ and the $tau$ terms as $tau$. Then I wrote the product $ P_{3times4} begin{bmatrix} X\Y\Z\T end{bmatrix} $ in terms of this.
– user617446
Dec 5 at 15:48
Thanks for the clarification. After reading your answer further, it is not clear that some parts make any sense. For instance, you state that $H_{3times3}=[R+ {Tover d}(tau N^t)]$, but it is not clear how $[R+ {Tover d}(tau N^t)]$ is a $3 times 3$ matrix? You specified that $N^t$ is a vector, and we have that $tau$ is also a vector. And based on your previous response, we can assume that $R$ is a $3 times 3$ matrix. Given this, I'm not sure how it is that $[R+ {Tover d}(tau N^t)]$ can be considered a $3 times 3$ matrix? And [...]
– The Pointer
Dec 8 at 5:28
[...] the addition doesn't make any sense either, since we're adding the $3 times 3$ matrix $R$ to ${Tover d}(tau N^t)$, which, whatever it is (this is not clear either), it is not a $3 times 3$ matrix.
– The Pointer
Dec 8 at 5:33
Despite this, I will award you the bounty for effort.
– The Pointer
Dec 8 at 5:34
|
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If 2D is initial affine space we compose 1P - projective space by
$
left(
begin{matrix}
tilde{x} \
tilde{y}
end{matrix}
right)=
left(
begin{matrix}
a & b \
c& d
end{matrix}
right)
left(
begin{matrix}
x \
y
end{matrix}
right)
$.
Left hand are homogeneous coordinates of 1P - point. Right hand coordinates represent a vector in 2D.
In a similar way we compose 2P from 3D:
$
left(
begin{matrix}
tilde{x} \
tilde{y} \
tilde{z}
end{matrix}
right) =
left(
begin{matrix}
a_{11}& a_{12} & a_{13} \
a_{21}& a_{22}& a_{23} \
a_{31}& a_{32}& a_{33} \
end{matrix}
right)
left(
begin{matrix}
x \
y \
z \
end{matrix}
right)
$.
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{13}Z+p_{14}T}{p_{31}X+p_{32}Y+p_{33}Z+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{23}Z+p_{24}T}{p_{31}X+p_{32}Y+p_{33}Z+p_{34}T}
$.
If Z=0 then
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{14}T}{p_{31}X+p_{32}Y+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{24}T}{p_{31}X+p_{32}Y+p_{34}T}
$.
If Z=5 then
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{13}.5T+p_{14}T}{p_{31}X+p_{32}Y+p_{33}.5T+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{23}.5T+p_{24}T}{p_{31}X+p_{32}Y+p_{33}.5T+p_{34}T}
$.
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2 Answers
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2 Answers
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Lets write $P_{3times4}=begin{bmatrix}r_{11}&r_{12}&r_{13}&tau_1\ r_{21}&r_{22}&r_{23}&tau_2\r_{31}&r_{32}&r_{33}&tau_3\end{bmatrix}$
and call the $r$ terms $R_{3times3}$ and the $tau$ terms $tau_{3times1}$
thus $P_{3times 4}=[R,tau]$ (I dropped the dimension indices for brevity, but $tau$ is a column vector). Now $P_{3times 4} U_4$ becomes $R begin{bmatrix} X\Y\Z end{bmatrix} +Ttau=R U_3 +Ttau$. where I defined $U_3 =begin{bmatrix} X\Y\Z end{bmatrix}$.
Before dealing with the $Z=0$ case, lets look at the case where the plane does not pass through the origin: all points $U_3$ are on a plane, hence they obey $N^T U_3 =d$ where $N$ is a unit vector normal to the plane and $-dneq0$ is the distance of the origin from the plane. For this case we just have $1= {1over d} N^T U_3$ and therefor $$R U_3 +Ttau= R U_3 +(Ttau){1over d}(N^T U_3)$$ so that finally $P_{3times 4} U_4$ can be written as $[R +{Tover d}(tau N^T)]U_3$ and $H_{3times3}=[R+ {Tover d}(tau N^T)]$ is called a "Homography".
The degenerate case is where $d=0$ and which also contains the case $Z=0$ by setting $N^T=[0,0,1]$. In this case instead of pushing $1= {1over d} N^T U_3$ we push $0= N^T U_3$ . So $$R U_3 +Ttau = (R (I-N N^T) +tau N^T )(U_3+T N)$$ , In the specific case $N^T=[0,0,1]$ we have $left[R begin{bmatrix} 1&0&0\0&1&0\0&0&0end{bmatrix} +begin{bmatrix} 0&0&tau_x\0&0&tau_y\0&0&tau_zend{bmatrix}right]begin{bmatrix} X\Y\Tend{bmatrix}$
Thanks for the answer. Can you please explain what happened in the first line? I have many questions. (1) What does it mean to "split" $U_4$ into $U_3=begin{bmatrix} X \ Y \ Zend{bmatrix}$ and $T$? (2) What does the notation $[R,tau]$ mean? (3) What are $R$ and $tau$ supposed to be? (4) And so how does $P_{3times 4} U_4$ become $R U_3 +Ttau$? My apologies for all the questions.
– The Pointer
Dec 5 at 15:39
1
I just wrote $P_{3times3}=begin{bmatrix}r_{11}&r_{12}&r_{13}&tau_1\ r_{21}&r_{22}&r_{23}&tau_2\r_{31}&r_{32}&r_{33}&tau_3\end{bmatrix} $ and called the $r$ terms $R$ and the $tau$ terms as $tau$. Then I wrote the product $ P_{3times4} begin{bmatrix} X\Y\Z\T end{bmatrix} $ in terms of this.
– user617446
Dec 5 at 15:48
Thanks for the clarification. After reading your answer further, it is not clear that some parts make any sense. For instance, you state that $H_{3times3}=[R+ {Tover d}(tau N^t)]$, but it is not clear how $[R+ {Tover d}(tau N^t)]$ is a $3 times 3$ matrix? You specified that $N^t$ is a vector, and we have that $tau$ is also a vector. And based on your previous response, we can assume that $R$ is a $3 times 3$ matrix. Given this, I'm not sure how it is that $[R+ {Tover d}(tau N^t)]$ can be considered a $3 times 3$ matrix? And [...]
– The Pointer
Dec 8 at 5:28
[...] the addition doesn't make any sense either, since we're adding the $3 times 3$ matrix $R$ to ${Tover d}(tau N^t)$, which, whatever it is (this is not clear either), it is not a $3 times 3$ matrix.
– The Pointer
Dec 8 at 5:33
Despite this, I will award you the bounty for effort.
– The Pointer
Dec 8 at 5:34
|
show 2 more comments
Lets write $P_{3times4}=begin{bmatrix}r_{11}&r_{12}&r_{13}&tau_1\ r_{21}&r_{22}&r_{23}&tau_2\r_{31}&r_{32}&r_{33}&tau_3\end{bmatrix}$
and call the $r$ terms $R_{3times3}$ and the $tau$ terms $tau_{3times1}$
thus $P_{3times 4}=[R,tau]$ (I dropped the dimension indices for brevity, but $tau$ is a column vector). Now $P_{3times 4} U_4$ becomes $R begin{bmatrix} X\Y\Z end{bmatrix} +Ttau=R U_3 +Ttau$. where I defined $U_3 =begin{bmatrix} X\Y\Z end{bmatrix}$.
Before dealing with the $Z=0$ case, lets look at the case where the plane does not pass through the origin: all points $U_3$ are on a plane, hence they obey $N^T U_3 =d$ where $N$ is a unit vector normal to the plane and $-dneq0$ is the distance of the origin from the plane. For this case we just have $1= {1over d} N^T U_3$ and therefor $$R U_3 +Ttau= R U_3 +(Ttau){1over d}(N^T U_3)$$ so that finally $P_{3times 4} U_4$ can be written as $[R +{Tover d}(tau N^T)]U_3$ and $H_{3times3}=[R+ {Tover d}(tau N^T)]$ is called a "Homography".
The degenerate case is where $d=0$ and which also contains the case $Z=0$ by setting $N^T=[0,0,1]$. In this case instead of pushing $1= {1over d} N^T U_3$ we push $0= N^T U_3$ . So $$R U_3 +Ttau = (R (I-N N^T) +tau N^T )(U_3+T N)$$ , In the specific case $N^T=[0,0,1]$ we have $left[R begin{bmatrix} 1&0&0\0&1&0\0&0&0end{bmatrix} +begin{bmatrix} 0&0&tau_x\0&0&tau_y\0&0&tau_zend{bmatrix}right]begin{bmatrix} X\Y\Tend{bmatrix}$
Thanks for the answer. Can you please explain what happened in the first line? I have many questions. (1) What does it mean to "split" $U_4$ into $U_3=begin{bmatrix} X \ Y \ Zend{bmatrix}$ and $T$? (2) What does the notation $[R,tau]$ mean? (3) What are $R$ and $tau$ supposed to be? (4) And so how does $P_{3times 4} U_4$ become $R U_3 +Ttau$? My apologies for all the questions.
– The Pointer
Dec 5 at 15:39
1
I just wrote $P_{3times3}=begin{bmatrix}r_{11}&r_{12}&r_{13}&tau_1\ r_{21}&r_{22}&r_{23}&tau_2\r_{31}&r_{32}&r_{33}&tau_3\end{bmatrix} $ and called the $r$ terms $R$ and the $tau$ terms as $tau$. Then I wrote the product $ P_{3times4} begin{bmatrix} X\Y\Z\T end{bmatrix} $ in terms of this.
– user617446
Dec 5 at 15:48
Thanks for the clarification. After reading your answer further, it is not clear that some parts make any sense. For instance, you state that $H_{3times3}=[R+ {Tover d}(tau N^t)]$, but it is not clear how $[R+ {Tover d}(tau N^t)]$ is a $3 times 3$ matrix? You specified that $N^t$ is a vector, and we have that $tau$ is also a vector. And based on your previous response, we can assume that $R$ is a $3 times 3$ matrix. Given this, I'm not sure how it is that $[R+ {Tover d}(tau N^t)]$ can be considered a $3 times 3$ matrix? And [...]
– The Pointer
Dec 8 at 5:28
[...] the addition doesn't make any sense either, since we're adding the $3 times 3$ matrix $R$ to ${Tover d}(tau N^t)$, which, whatever it is (this is not clear either), it is not a $3 times 3$ matrix.
– The Pointer
Dec 8 at 5:33
Despite this, I will award you the bounty for effort.
– The Pointer
Dec 8 at 5:34
|
show 2 more comments
Lets write $P_{3times4}=begin{bmatrix}r_{11}&r_{12}&r_{13}&tau_1\ r_{21}&r_{22}&r_{23}&tau_2\r_{31}&r_{32}&r_{33}&tau_3\end{bmatrix}$
and call the $r$ terms $R_{3times3}$ and the $tau$ terms $tau_{3times1}$
thus $P_{3times 4}=[R,tau]$ (I dropped the dimension indices for brevity, but $tau$ is a column vector). Now $P_{3times 4} U_4$ becomes $R begin{bmatrix} X\Y\Z end{bmatrix} +Ttau=R U_3 +Ttau$. where I defined $U_3 =begin{bmatrix} X\Y\Z end{bmatrix}$.
Before dealing with the $Z=0$ case, lets look at the case where the plane does not pass through the origin: all points $U_3$ are on a plane, hence they obey $N^T U_3 =d$ where $N$ is a unit vector normal to the plane and $-dneq0$ is the distance of the origin from the plane. For this case we just have $1= {1over d} N^T U_3$ and therefor $$R U_3 +Ttau= R U_3 +(Ttau){1over d}(N^T U_3)$$ so that finally $P_{3times 4} U_4$ can be written as $[R +{Tover d}(tau N^T)]U_3$ and $H_{3times3}=[R+ {Tover d}(tau N^T)]$ is called a "Homography".
The degenerate case is where $d=0$ and which also contains the case $Z=0$ by setting $N^T=[0,0,1]$. In this case instead of pushing $1= {1over d} N^T U_3$ we push $0= N^T U_3$ . So $$R U_3 +Ttau = (R (I-N N^T) +tau N^T )(U_3+T N)$$ , In the specific case $N^T=[0,0,1]$ we have $left[R begin{bmatrix} 1&0&0\0&1&0\0&0&0end{bmatrix} +begin{bmatrix} 0&0&tau_x\0&0&tau_y\0&0&tau_zend{bmatrix}right]begin{bmatrix} X\Y\Tend{bmatrix}$
Lets write $P_{3times4}=begin{bmatrix}r_{11}&r_{12}&r_{13}&tau_1\ r_{21}&r_{22}&r_{23}&tau_2\r_{31}&r_{32}&r_{33}&tau_3\end{bmatrix}$
and call the $r$ terms $R_{3times3}$ and the $tau$ terms $tau_{3times1}$
thus $P_{3times 4}=[R,tau]$ (I dropped the dimension indices for brevity, but $tau$ is a column vector). Now $P_{3times 4} U_4$ becomes $R begin{bmatrix} X\Y\Z end{bmatrix} +Ttau=R U_3 +Ttau$. where I defined $U_3 =begin{bmatrix} X\Y\Z end{bmatrix}$.
Before dealing with the $Z=0$ case, lets look at the case where the plane does not pass through the origin: all points $U_3$ are on a plane, hence they obey $N^T U_3 =d$ where $N$ is a unit vector normal to the plane and $-dneq0$ is the distance of the origin from the plane. For this case we just have $1= {1over d} N^T U_3$ and therefor $$R U_3 +Ttau= R U_3 +(Ttau){1over d}(N^T U_3)$$ so that finally $P_{3times 4} U_4$ can be written as $[R +{Tover d}(tau N^T)]U_3$ and $H_{3times3}=[R+ {Tover d}(tau N^T)]$ is called a "Homography".
The degenerate case is where $d=0$ and which also contains the case $Z=0$ by setting $N^T=[0,0,1]$. In this case instead of pushing $1= {1over d} N^T U_3$ we push $0= N^T U_3$ . So $$R U_3 +Ttau = (R (I-N N^T) +tau N^T )(U_3+T N)$$ , In the specific case $N^T=[0,0,1]$ we have $left[R begin{bmatrix} 1&0&0\0&1&0\0&0&0end{bmatrix} +begin{bmatrix} 0&0&tau_x\0&0&tau_y\0&0&tau_zend{bmatrix}right]begin{bmatrix} X\Y\Tend{bmatrix}$
edited Dec 9 at 12:17
answered Dec 5 at 14:46
user617446
3162
3162
Thanks for the answer. Can you please explain what happened in the first line? I have many questions. (1) What does it mean to "split" $U_4$ into $U_3=begin{bmatrix} X \ Y \ Zend{bmatrix}$ and $T$? (2) What does the notation $[R,tau]$ mean? (3) What are $R$ and $tau$ supposed to be? (4) And so how does $P_{3times 4} U_4$ become $R U_3 +Ttau$? My apologies for all the questions.
– The Pointer
Dec 5 at 15:39
1
I just wrote $P_{3times3}=begin{bmatrix}r_{11}&r_{12}&r_{13}&tau_1\ r_{21}&r_{22}&r_{23}&tau_2\r_{31}&r_{32}&r_{33}&tau_3\end{bmatrix} $ and called the $r$ terms $R$ and the $tau$ terms as $tau$. Then I wrote the product $ P_{3times4} begin{bmatrix} X\Y\Z\T end{bmatrix} $ in terms of this.
– user617446
Dec 5 at 15:48
Thanks for the clarification. After reading your answer further, it is not clear that some parts make any sense. For instance, you state that $H_{3times3}=[R+ {Tover d}(tau N^t)]$, but it is not clear how $[R+ {Tover d}(tau N^t)]$ is a $3 times 3$ matrix? You specified that $N^t$ is a vector, and we have that $tau$ is also a vector. And based on your previous response, we can assume that $R$ is a $3 times 3$ matrix. Given this, I'm not sure how it is that $[R+ {Tover d}(tau N^t)]$ can be considered a $3 times 3$ matrix? And [...]
– The Pointer
Dec 8 at 5:28
[...] the addition doesn't make any sense either, since we're adding the $3 times 3$ matrix $R$ to ${Tover d}(tau N^t)$, which, whatever it is (this is not clear either), it is not a $3 times 3$ matrix.
– The Pointer
Dec 8 at 5:33
Despite this, I will award you the bounty for effort.
– The Pointer
Dec 8 at 5:34
|
show 2 more comments
Thanks for the answer. Can you please explain what happened in the first line? I have many questions. (1) What does it mean to "split" $U_4$ into $U_3=begin{bmatrix} X \ Y \ Zend{bmatrix}$ and $T$? (2) What does the notation $[R,tau]$ mean? (3) What are $R$ and $tau$ supposed to be? (4) And so how does $P_{3times 4} U_4$ become $R U_3 +Ttau$? My apologies for all the questions.
– The Pointer
Dec 5 at 15:39
1
I just wrote $P_{3times3}=begin{bmatrix}r_{11}&r_{12}&r_{13}&tau_1\ r_{21}&r_{22}&r_{23}&tau_2\r_{31}&r_{32}&r_{33}&tau_3\end{bmatrix} $ and called the $r$ terms $R$ and the $tau$ terms as $tau$. Then I wrote the product $ P_{3times4} begin{bmatrix} X\Y\Z\T end{bmatrix} $ in terms of this.
– user617446
Dec 5 at 15:48
Thanks for the clarification. After reading your answer further, it is not clear that some parts make any sense. For instance, you state that $H_{3times3}=[R+ {Tover d}(tau N^t)]$, but it is not clear how $[R+ {Tover d}(tau N^t)]$ is a $3 times 3$ matrix? You specified that $N^t$ is a vector, and we have that $tau$ is also a vector. And based on your previous response, we can assume that $R$ is a $3 times 3$ matrix. Given this, I'm not sure how it is that $[R+ {Tover d}(tau N^t)]$ can be considered a $3 times 3$ matrix? And [...]
– The Pointer
Dec 8 at 5:28
[...] the addition doesn't make any sense either, since we're adding the $3 times 3$ matrix $R$ to ${Tover d}(tau N^t)$, which, whatever it is (this is not clear either), it is not a $3 times 3$ matrix.
– The Pointer
Dec 8 at 5:33
Despite this, I will award you the bounty for effort.
– The Pointer
Dec 8 at 5:34
Thanks for the answer. Can you please explain what happened in the first line? I have many questions. (1) What does it mean to "split" $U_4$ into $U_3=begin{bmatrix} X \ Y \ Zend{bmatrix}$ and $T$? (2) What does the notation $[R,tau]$ mean? (3) What are $R$ and $tau$ supposed to be? (4) And so how does $P_{3times 4} U_4$ become $R U_3 +Ttau$? My apologies for all the questions.
– The Pointer
Dec 5 at 15:39
Thanks for the answer. Can you please explain what happened in the first line? I have many questions. (1) What does it mean to "split" $U_4$ into $U_3=begin{bmatrix} X \ Y \ Zend{bmatrix}$ and $T$? (2) What does the notation $[R,tau]$ mean? (3) What are $R$ and $tau$ supposed to be? (4) And so how does $P_{3times 4} U_4$ become $R U_3 +Ttau$? My apologies for all the questions.
– The Pointer
Dec 5 at 15:39
1
1
I just wrote $P_{3times3}=begin{bmatrix}r_{11}&r_{12}&r_{13}&tau_1\ r_{21}&r_{22}&r_{23}&tau_2\r_{31}&r_{32}&r_{33}&tau_3\end{bmatrix} $ and called the $r$ terms $R$ and the $tau$ terms as $tau$. Then I wrote the product $ P_{3times4} begin{bmatrix} X\Y\Z\T end{bmatrix} $ in terms of this.
– user617446
Dec 5 at 15:48
I just wrote $P_{3times3}=begin{bmatrix}r_{11}&r_{12}&r_{13}&tau_1\ r_{21}&r_{22}&r_{23}&tau_2\r_{31}&r_{32}&r_{33}&tau_3\end{bmatrix} $ and called the $r$ terms $R$ and the $tau$ terms as $tau$. Then I wrote the product $ P_{3times4} begin{bmatrix} X\Y\Z\T end{bmatrix} $ in terms of this.
– user617446
Dec 5 at 15:48
Thanks for the clarification. After reading your answer further, it is not clear that some parts make any sense. For instance, you state that $H_{3times3}=[R+ {Tover d}(tau N^t)]$, but it is not clear how $[R+ {Tover d}(tau N^t)]$ is a $3 times 3$ matrix? You specified that $N^t$ is a vector, and we have that $tau$ is also a vector. And based on your previous response, we can assume that $R$ is a $3 times 3$ matrix. Given this, I'm not sure how it is that $[R+ {Tover d}(tau N^t)]$ can be considered a $3 times 3$ matrix? And [...]
– The Pointer
Dec 8 at 5:28
Thanks for the clarification. After reading your answer further, it is not clear that some parts make any sense. For instance, you state that $H_{3times3}=[R+ {Tover d}(tau N^t)]$, but it is not clear how $[R+ {Tover d}(tau N^t)]$ is a $3 times 3$ matrix? You specified that $N^t$ is a vector, and we have that $tau$ is also a vector. And based on your previous response, we can assume that $R$ is a $3 times 3$ matrix. Given this, I'm not sure how it is that $[R+ {Tover d}(tau N^t)]$ can be considered a $3 times 3$ matrix? And [...]
– The Pointer
Dec 8 at 5:28
[...] the addition doesn't make any sense either, since we're adding the $3 times 3$ matrix $R$ to ${Tover d}(tau N^t)$, which, whatever it is (this is not clear either), it is not a $3 times 3$ matrix.
– The Pointer
Dec 8 at 5:33
[...] the addition doesn't make any sense either, since we're adding the $3 times 3$ matrix $R$ to ${Tover d}(tau N^t)$, which, whatever it is (this is not clear either), it is not a $3 times 3$ matrix.
– The Pointer
Dec 8 at 5:33
Despite this, I will award you the bounty for effort.
– The Pointer
Dec 8 at 5:34
Despite this, I will award you the bounty for effort.
– The Pointer
Dec 8 at 5:34
|
show 2 more comments
If 2D is initial affine space we compose 1P - projective space by
$
left(
begin{matrix}
tilde{x} \
tilde{y}
end{matrix}
right)=
left(
begin{matrix}
a & b \
c& d
end{matrix}
right)
left(
begin{matrix}
x \
y
end{matrix}
right)
$.
Left hand are homogeneous coordinates of 1P - point. Right hand coordinates represent a vector in 2D.
In a similar way we compose 2P from 3D:
$
left(
begin{matrix}
tilde{x} \
tilde{y} \
tilde{z}
end{matrix}
right) =
left(
begin{matrix}
a_{11}& a_{12} & a_{13} \
a_{21}& a_{22}& a_{23} \
a_{31}& a_{32}& a_{33} \
end{matrix}
right)
left(
begin{matrix}
x \
y \
z \
end{matrix}
right)
$.
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{13}Z+p_{14}T}{p_{31}X+p_{32}Y+p_{33}Z+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{23}Z+p_{24}T}{p_{31}X+p_{32}Y+p_{33}Z+p_{34}T}
$.
If Z=0 then
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{14}T}{p_{31}X+p_{32}Y+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{24}T}{p_{31}X+p_{32}Y+p_{34}T}
$.
If Z=5 then
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{13}.5T+p_{14}T}{p_{31}X+p_{32}Y+p_{33}.5T+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{23}.5T+p_{24}T}{p_{31}X+p_{32}Y+p_{33}.5T+p_{34}T}
$.
add a comment |
If 2D is initial affine space we compose 1P - projective space by
$
left(
begin{matrix}
tilde{x} \
tilde{y}
end{matrix}
right)=
left(
begin{matrix}
a & b \
c& d
end{matrix}
right)
left(
begin{matrix}
x \
y
end{matrix}
right)
$.
Left hand are homogeneous coordinates of 1P - point. Right hand coordinates represent a vector in 2D.
In a similar way we compose 2P from 3D:
$
left(
begin{matrix}
tilde{x} \
tilde{y} \
tilde{z}
end{matrix}
right) =
left(
begin{matrix}
a_{11}& a_{12} & a_{13} \
a_{21}& a_{22}& a_{23} \
a_{31}& a_{32}& a_{33} \
end{matrix}
right)
left(
begin{matrix}
x \
y \
z \
end{matrix}
right)
$.
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{13}Z+p_{14}T}{p_{31}X+p_{32}Y+p_{33}Z+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{23}Z+p_{24}T}{p_{31}X+p_{32}Y+p_{33}Z+p_{34}T}
$.
If Z=0 then
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{14}T}{p_{31}X+p_{32}Y+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{24}T}{p_{31}X+p_{32}Y+p_{34}T}
$.
If Z=5 then
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{13}.5T+p_{14}T}{p_{31}X+p_{32}Y+p_{33}.5T+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{23}.5T+p_{24}T}{p_{31}X+p_{32}Y+p_{33}.5T+p_{34}T}
$.
add a comment |
If 2D is initial affine space we compose 1P - projective space by
$
left(
begin{matrix}
tilde{x} \
tilde{y}
end{matrix}
right)=
left(
begin{matrix}
a & b \
c& d
end{matrix}
right)
left(
begin{matrix}
x \
y
end{matrix}
right)
$.
Left hand are homogeneous coordinates of 1P - point. Right hand coordinates represent a vector in 2D.
In a similar way we compose 2P from 3D:
$
left(
begin{matrix}
tilde{x} \
tilde{y} \
tilde{z}
end{matrix}
right) =
left(
begin{matrix}
a_{11}& a_{12} & a_{13} \
a_{21}& a_{22}& a_{23} \
a_{31}& a_{32}& a_{33} \
end{matrix}
right)
left(
begin{matrix}
x \
y \
z \
end{matrix}
right)
$.
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{13}Z+p_{14}T}{p_{31}X+p_{32}Y+p_{33}Z+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{23}Z+p_{24}T}{p_{31}X+p_{32}Y+p_{33}Z+p_{34}T}
$.
If Z=0 then
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{14}T}{p_{31}X+p_{32}Y+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{24}T}{p_{31}X+p_{32}Y+p_{34}T}
$.
If Z=5 then
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{13}.5T+p_{14}T}{p_{31}X+p_{32}Y+p_{33}.5T+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{23}.5T+p_{24}T}{p_{31}X+p_{32}Y+p_{33}.5T+p_{34}T}
$.
If 2D is initial affine space we compose 1P - projective space by
$
left(
begin{matrix}
tilde{x} \
tilde{y}
end{matrix}
right)=
left(
begin{matrix}
a & b \
c& d
end{matrix}
right)
left(
begin{matrix}
x \
y
end{matrix}
right)
$.
Left hand are homogeneous coordinates of 1P - point. Right hand coordinates represent a vector in 2D.
In a similar way we compose 2P from 3D:
$
left(
begin{matrix}
tilde{x} \
tilde{y} \
tilde{z}
end{matrix}
right) =
left(
begin{matrix}
a_{11}& a_{12} & a_{13} \
a_{21}& a_{22}& a_{23} \
a_{31}& a_{32}& a_{33} \
end{matrix}
right)
left(
begin{matrix}
x \
y \
z \
end{matrix}
right)
$.
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{13}Z+p_{14}T}{p_{31}X+p_{32}Y+p_{33}Z+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{23}Z+p_{24}T}{p_{31}X+p_{32}Y+p_{33}Z+p_{34}T}
$.
If Z=0 then
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{14}T}{p_{31}X+p_{32}Y+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{24}T}{p_{31}X+p_{32}Y+p_{34}T}
$.
If Z=5 then
$
frac{x}{omega}=frac{p_{11}X+p_{12}Y+p_{13}.5T+p_{14}T}{p_{31}X+p_{32}Y+p_{33}.5T+p_{34}T} \
frac{y}{omega}=frac{p_{21}X+p_{22}Y+p_{23}.5T+p_{24}T}{p_{31}X+p_{32}Y+p_{33}.5T+p_{34}T}
$.
edited Dec 9 at 0:26
answered Dec 8 at 0:51
Станчо Павлов
12
12
add a comment |
add a comment |
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Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown