Understanding perspective transform matrix elements interpretation












2












$begingroup$


I am representing 3D points (vectors) in the following way:



(* conversion from 3D point, represented by normal list of 
coordinates, to matrxi column, suitable for transforms *)
ToColumn[point_] := Transpose[{Append[point, 1]}];


enter image description here



(* conversion from matrix column, representing 3D point, to a list, 
representing the same point *)
ToPoint[column_] := Take[Transpose[column/column[[4, 1]]][[1]], 3];


enter image description here



I.e. forth element serves as the scale factor.



(Is this conventional representation and what is the name of it?)



I am representing perspective transform with the following matrix:



PerspectiveXYZ[{x_, y_, z_}] := {
{1, 0, 0, 0},
{0, 1, 0, 0},
{0, 0, 1, 0},
{x, y, z, 0}
};


so that



enter image description here



My question is: what is the sense of transform elements x, y and z?



I drew a cube of 8 points and transformed it with various values of these variables:



enter image description here



And found, that x and y controls projection plane orientation, while z controls both the scale and distance from origin point, while z=1 means projecting into some small region (1?), and that the smaller this value, the bigger is the scale, becoming infinite when z=0.



Is there any clear geometric interpretation of these values, especially z? May be they should be substituted with 1/z or something for better interpretation?



May be my vector model should be changed?










share|cite|improve this question











$endgroup$








  • 1




    $begingroup$
    It's a fact that if you use "homogeneous coordinates" then a perspective (or projective) transformation from a (projective) plane to a (projective) plane can be represented by a $3 times 3$ "homogeneous" matrix. This is one reason homogeneous coordinates are useful, though they seem unintuitive at first.
    $endgroup$
    – littleO
    Jun 14 '13 at 10:28










  • $begingroup$
    I am using 4x4 matrices.
    $endgroup$
    – Suzan Cioc
    Jun 14 '13 at 10:36










  • $begingroup$
    But warpPerspective accepts a $3 times 3$ matrix, so why are you using $4 times 4$ matrices? Also, I don't understand exactly what your question is.
    $endgroup$
    – littleO
    Jun 14 '13 at 11:51










  • $begingroup$
    See my update. 3x3 matrix gives the same result (I think) as 4x4 matrix with 3rd row/column excluded / turned to zero. My question is more general.
    $endgroup$
    – Suzan Cioc
    Jun 14 '13 at 11:55










  • $begingroup$
    Thanks. I'm confused now about why the $4 times 4$ matrix isn't invertible, I had thought that it should be. Btw, a decent reference for this stuff is the book Multiple View Geometry in Computer Vision by Hartley and Zisserman.
    $endgroup$
    – littleO
    Jun 14 '13 at 19:43


















2












$begingroup$


I am representing 3D points (vectors) in the following way:



(* conversion from 3D point, represented by normal list of 
coordinates, to matrxi column, suitable for transforms *)
ToColumn[point_] := Transpose[{Append[point, 1]}];


enter image description here



(* conversion from matrix column, representing 3D point, to a list, 
representing the same point *)
ToPoint[column_] := Take[Transpose[column/column[[4, 1]]][[1]], 3];


enter image description here



I.e. forth element serves as the scale factor.



(Is this conventional representation and what is the name of it?)



I am representing perspective transform with the following matrix:



PerspectiveXYZ[{x_, y_, z_}] := {
{1, 0, 0, 0},
{0, 1, 0, 0},
{0, 0, 1, 0},
{x, y, z, 0}
};


so that



enter image description here



My question is: what is the sense of transform elements x, y and z?



I drew a cube of 8 points and transformed it with various values of these variables:



enter image description here



And found, that x and y controls projection plane orientation, while z controls both the scale and distance from origin point, while z=1 means projecting into some small region (1?), and that the smaller this value, the bigger is the scale, becoming infinite when z=0.



Is there any clear geometric interpretation of these values, especially z? May be they should be substituted with 1/z or something for better interpretation?



May be my vector model should be changed?










share|cite|improve this question











$endgroup$








  • 1




    $begingroup$
    It's a fact that if you use "homogeneous coordinates" then a perspective (or projective) transformation from a (projective) plane to a (projective) plane can be represented by a $3 times 3$ "homogeneous" matrix. This is one reason homogeneous coordinates are useful, though they seem unintuitive at first.
    $endgroup$
    – littleO
    Jun 14 '13 at 10:28










  • $begingroup$
    I am using 4x4 matrices.
    $endgroup$
    – Suzan Cioc
    Jun 14 '13 at 10:36










  • $begingroup$
    But warpPerspective accepts a $3 times 3$ matrix, so why are you using $4 times 4$ matrices? Also, I don't understand exactly what your question is.
    $endgroup$
    – littleO
    Jun 14 '13 at 11:51










  • $begingroup$
    See my update. 3x3 matrix gives the same result (I think) as 4x4 matrix with 3rd row/column excluded / turned to zero. My question is more general.
    $endgroup$
    – Suzan Cioc
    Jun 14 '13 at 11:55










  • $begingroup$
    Thanks. I'm confused now about why the $4 times 4$ matrix isn't invertible, I had thought that it should be. Btw, a decent reference for this stuff is the book Multiple View Geometry in Computer Vision by Hartley and Zisserman.
    $endgroup$
    – littleO
    Jun 14 '13 at 19:43
















2












2








2


1



$begingroup$


I am representing 3D points (vectors) in the following way:



(* conversion from 3D point, represented by normal list of 
coordinates, to matrxi column, suitable for transforms *)
ToColumn[point_] := Transpose[{Append[point, 1]}];


enter image description here



(* conversion from matrix column, representing 3D point, to a list, 
representing the same point *)
ToPoint[column_] := Take[Transpose[column/column[[4, 1]]][[1]], 3];


enter image description here



I.e. forth element serves as the scale factor.



(Is this conventional representation and what is the name of it?)



I am representing perspective transform with the following matrix:



PerspectiveXYZ[{x_, y_, z_}] := {
{1, 0, 0, 0},
{0, 1, 0, 0},
{0, 0, 1, 0},
{x, y, z, 0}
};


so that



enter image description here



My question is: what is the sense of transform elements x, y and z?



I drew a cube of 8 points and transformed it with various values of these variables:



enter image description here



And found, that x and y controls projection plane orientation, while z controls both the scale and distance from origin point, while z=1 means projecting into some small region (1?), and that the smaller this value, the bigger is the scale, becoming infinite when z=0.



Is there any clear geometric interpretation of these values, especially z? May be they should be substituted with 1/z or something for better interpretation?



May be my vector model should be changed?










share|cite|improve this question











$endgroup$




I am representing 3D points (vectors) in the following way:



(* conversion from 3D point, represented by normal list of 
coordinates, to matrxi column, suitable for transforms *)
ToColumn[point_] := Transpose[{Append[point, 1]}];


enter image description here



(* conversion from matrix column, representing 3D point, to a list, 
representing the same point *)
ToPoint[column_] := Take[Transpose[column/column[[4, 1]]][[1]], 3];


enter image description here



I.e. forth element serves as the scale factor.



(Is this conventional representation and what is the name of it?)



I am representing perspective transform with the following matrix:



PerspectiveXYZ[{x_, y_, z_}] := {
{1, 0, 0, 0},
{0, 1, 0, 0},
{0, 0, 1, 0},
{x, y, z, 0}
};


so that



enter image description here



My question is: what is the sense of transform elements x, y and z?



I drew a cube of 8 points and transformed it with various values of these variables:



enter image description here



And found, that x and y controls projection plane orientation, while z controls both the scale and distance from origin point, while z=1 means projecting into some small region (1?), and that the smaller this value, the bigger is the scale, becoming infinite when z=0.



Is there any clear geometric interpretation of these values, especially z? May be they should be substituted with 1/z or something for better interpretation?



May be my vector model should be changed?







transformation






share|cite|improve this question















share|cite|improve this question













share|cite|improve this question




share|cite|improve this question








edited Jun 14 '13 at 11:54







Suzan Cioc

















asked Jun 14 '13 at 9:09









Suzan CiocSuzan Cioc

401621




401621








  • 1




    $begingroup$
    It's a fact that if you use "homogeneous coordinates" then a perspective (or projective) transformation from a (projective) plane to a (projective) plane can be represented by a $3 times 3$ "homogeneous" matrix. This is one reason homogeneous coordinates are useful, though they seem unintuitive at first.
    $endgroup$
    – littleO
    Jun 14 '13 at 10:28










  • $begingroup$
    I am using 4x4 matrices.
    $endgroup$
    – Suzan Cioc
    Jun 14 '13 at 10:36










  • $begingroup$
    But warpPerspective accepts a $3 times 3$ matrix, so why are you using $4 times 4$ matrices? Also, I don't understand exactly what your question is.
    $endgroup$
    – littleO
    Jun 14 '13 at 11:51










  • $begingroup$
    See my update. 3x3 matrix gives the same result (I think) as 4x4 matrix with 3rd row/column excluded / turned to zero. My question is more general.
    $endgroup$
    – Suzan Cioc
    Jun 14 '13 at 11:55










  • $begingroup$
    Thanks. I'm confused now about why the $4 times 4$ matrix isn't invertible, I had thought that it should be. Btw, a decent reference for this stuff is the book Multiple View Geometry in Computer Vision by Hartley and Zisserman.
    $endgroup$
    – littleO
    Jun 14 '13 at 19:43
















  • 1




    $begingroup$
    It's a fact that if you use "homogeneous coordinates" then a perspective (or projective) transformation from a (projective) plane to a (projective) plane can be represented by a $3 times 3$ "homogeneous" matrix. This is one reason homogeneous coordinates are useful, though they seem unintuitive at first.
    $endgroup$
    – littleO
    Jun 14 '13 at 10:28










  • $begingroup$
    I am using 4x4 matrices.
    $endgroup$
    – Suzan Cioc
    Jun 14 '13 at 10:36










  • $begingroup$
    But warpPerspective accepts a $3 times 3$ matrix, so why are you using $4 times 4$ matrices? Also, I don't understand exactly what your question is.
    $endgroup$
    – littleO
    Jun 14 '13 at 11:51










  • $begingroup$
    See my update. 3x3 matrix gives the same result (I think) as 4x4 matrix with 3rd row/column excluded / turned to zero. My question is more general.
    $endgroup$
    – Suzan Cioc
    Jun 14 '13 at 11:55










  • $begingroup$
    Thanks. I'm confused now about why the $4 times 4$ matrix isn't invertible, I had thought that it should be. Btw, a decent reference for this stuff is the book Multiple View Geometry in Computer Vision by Hartley and Zisserman.
    $endgroup$
    – littleO
    Jun 14 '13 at 19:43










1




1




$begingroup$
It's a fact that if you use "homogeneous coordinates" then a perspective (or projective) transformation from a (projective) plane to a (projective) plane can be represented by a $3 times 3$ "homogeneous" matrix. This is one reason homogeneous coordinates are useful, though they seem unintuitive at first.
$endgroup$
– littleO
Jun 14 '13 at 10:28




$begingroup$
It's a fact that if you use "homogeneous coordinates" then a perspective (or projective) transformation from a (projective) plane to a (projective) plane can be represented by a $3 times 3$ "homogeneous" matrix. This is one reason homogeneous coordinates are useful, though they seem unintuitive at first.
$endgroup$
– littleO
Jun 14 '13 at 10:28












$begingroup$
I am using 4x4 matrices.
$endgroup$
– Suzan Cioc
Jun 14 '13 at 10:36




$begingroup$
I am using 4x4 matrices.
$endgroup$
– Suzan Cioc
Jun 14 '13 at 10:36












$begingroup$
But warpPerspective accepts a $3 times 3$ matrix, so why are you using $4 times 4$ matrices? Also, I don't understand exactly what your question is.
$endgroup$
– littleO
Jun 14 '13 at 11:51




$begingroup$
But warpPerspective accepts a $3 times 3$ matrix, so why are you using $4 times 4$ matrices? Also, I don't understand exactly what your question is.
$endgroup$
– littleO
Jun 14 '13 at 11:51












$begingroup$
See my update. 3x3 matrix gives the same result (I think) as 4x4 matrix with 3rd row/column excluded / turned to zero. My question is more general.
$endgroup$
– Suzan Cioc
Jun 14 '13 at 11:55




$begingroup$
See my update. 3x3 matrix gives the same result (I think) as 4x4 matrix with 3rd row/column excluded / turned to zero. My question is more general.
$endgroup$
– Suzan Cioc
Jun 14 '13 at 11:55












$begingroup$
Thanks. I'm confused now about why the $4 times 4$ matrix isn't invertible, I had thought that it should be. Btw, a decent reference for this stuff is the book Multiple View Geometry in Computer Vision by Hartley and Zisserman.
$endgroup$
– littleO
Jun 14 '13 at 19:43






$begingroup$
Thanks. I'm confused now about why the $4 times 4$ matrix isn't invertible, I had thought that it should be. Btw, a decent reference for this stuff is the book Multiple View Geometry in Computer Vision by Hartley and Zisserman.
$endgroup$
– littleO
Jun 14 '13 at 19:43












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$begingroup$

The matrix



enter image description here



defines a perspective projection onto the plane with equation



$Ax + By + Cz + D=0$



Perspective is build with the center in the origin.






share|cite|improve this answer









$endgroup$













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    1 Answer
    1






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes









    0












    $begingroup$

    The matrix



    enter image description here



    defines a perspective projection onto the plane with equation



    $Ax + By + Cz + D=0$



    Perspective is build with the center in the origin.






    share|cite|improve this answer









    $endgroup$


















      0












      $begingroup$

      The matrix



      enter image description here



      defines a perspective projection onto the plane with equation



      $Ax + By + Cz + D=0$



      Perspective is build with the center in the origin.






      share|cite|improve this answer









      $endgroup$
















        0












        0








        0





        $begingroup$

        The matrix



        enter image description here



        defines a perspective projection onto the plane with equation



        $Ax + By + Cz + D=0$



        Perspective is build with the center in the origin.






        share|cite|improve this answer









        $endgroup$



        The matrix



        enter image description here



        defines a perspective projection onto the plane with equation



        $Ax + By + Cz + D=0$



        Perspective is build with the center in the origin.







        share|cite|improve this answer












        share|cite|improve this answer



        share|cite|improve this answer










        answered Jun 14 '13 at 22:09









        Suzan CiocSuzan Cioc

        401621




        401621






























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