If All the Points Lie On a Plane, Then Why Does the Linear Mapping Reduce to …?












4














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.










share|cite|improve this question





























    4














    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.










    share|cite|improve this question



























      4












      4








      4







      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.










      share|cite|improve this question















      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






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      share|cite|improve this question













      share|cite|improve this question




      share|cite|improve this question








      edited Dec 7 at 22:24

























      asked Nov 28 at 22:58









      The Pointer

      2,59321334




      2,59321334






















          2 Answers
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          active

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          3





          +150









          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 $left[R begin{bmatrix} 1&0&0\0&1&0\0&0&0end{bmatrix} +begin{bmatrix} 0&0&tau_x\0&0&tau_y\0&0&tau_zend{bmatrix}right]begin{bmatrix} X\Y\Tend{bmatrix}$






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          • 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





















          0














          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
            2






            active

            oldest

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            active

            oldest

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            active

            oldest

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            3





            +150









            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 $left[R begin{bmatrix} 1&0&0\0&1&0\0&0&0end{bmatrix} +begin{bmatrix} 0&0&tau_x\0&0&tau_y\0&0&tau_zend{bmatrix}right]begin{bmatrix} X\Y\Tend{bmatrix}$






            share|cite|improve this answer























            • 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


















            3





            +150









            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 $left[R begin{bmatrix} 1&0&0\0&1&0\0&0&0end{bmatrix} +begin{bmatrix} 0&0&tau_x\0&0&tau_y\0&0&tau_zend{bmatrix}right]begin{bmatrix} X\Y\Tend{bmatrix}$






            share|cite|improve this answer























            • 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
















            3





            +150







            3





            +150



            3




            +150




            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 $left[R begin{bmatrix} 1&0&0\0&1&0\0&0&0end{bmatrix} +begin{bmatrix} 0&0&tau_x\0&0&tau_y\0&0&tau_zend{bmatrix}right]begin{bmatrix} X\Y\Tend{bmatrix}$






            share|cite|improve this answer














            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 $left[R begin{bmatrix} 1&0&0\0&1&0\0&0&0end{bmatrix} +begin{bmatrix} 0&0&tau_x\0&0&tau_y\0&0&tau_zend{bmatrix}right]begin{bmatrix} X\Y\Tend{bmatrix}$







            share|cite|improve this answer














            share|cite|improve this answer



            share|cite|improve this answer








            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




















            • 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













            0














            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}
            $
            .






            share|cite|improve this answer




























              0














              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}
              $
              .






              share|cite|improve this answer


























                0












                0








                0






                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}
                $
                .






                share|cite|improve this answer














                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}
                $
                .







                share|cite|improve this answer














                share|cite|improve this answer



                share|cite|improve this answer








                edited Dec 9 at 0:26

























                answered Dec 8 at 0:51









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