Computer Vision Geometry - Collinear Points In A Pinhole Camera Model

In summary, in order to prove that a line in 3D space is imaged to a line on the image plane in a pinhole camera model, one can imagine a plane containing the line and the pinhole, which then intersects with the image plane to form the image of the original line. This can be represented mathematically using parametric equations and the focal point of the camera.
  • #1
jenny_shoars
21
0

Homework Statement


Prove that a line in 3D space is imaged to a line on the image plane in a pinhole camera model.

Homework Equations


A 3D point give by (X,Y,Z) will be imaged on the image plane at
x = f([itex]\frac{X}{Z}[/itex])
and
y = f([itex]\frac{Y}{Z}[/itex])
where f is the focal point.

The Attempt at a Solution


My first thought was a more intuitive one. If you have a line in 3D space and the point which is the pinhole, you have a plane on which both the pinhole and line lie. Where this plane intersects the image plane it forms a line and this is where the 3D line is mapped to on the image plane. However, this seems like too much hand waving.

Instead I decided to try saying that for the line in 3D there must be a parametric equation given by
X = at + d
Y = bt + e
Z = ct + g
Then
x = f[itex]\frac{at+i}{ct+k}[/itex]
y = f[itex]\frac{bt+j}{ct+k}[/itex]
From here I know that for a line to exist on the image plane there must be a q and m such that
y = mx + q
Yet, this doesn't seem to lead me in the right direction.

Any suggestions? Thank you for your time!
 
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  • #2
jenny_shoars said:

Homework Statement


Prove that a line in 3D space is imaged to a line on the image plane in a pinhole camera model.

Homework Equations


A 3D point give by (X,Y,Z) will be imaged on the image plane at
x = f([itex]\frac{X}{Z}[/itex])
and
y = f([itex]\frac{Y}{Z}[/itex])
where f is the focal point.

The Attempt at a Solution


My first thought was a more intuitive one. If you have a line in 3D space and the point which is the pinhole, you have a plane on which both the pinhole and line lie. Where this plane intersects the image plane it forms a line and this is where the 3D line is mapped to on the image plane. However, this seems like too much hand waving.

Instead I decided to try saying that for the line in 3D there must be a parametric equation given by
X = at + d
Y = bt + e
Z = ct + g
Then
x = f[itex]\frac{at+i}{ct+k}[/itex]
y = f[itex]\frac{bt+j}{ct+k}[/itex]
From here I know that for a line to exist on the image plane there must be a q and m such that
y = mx + q
Yet, this doesn't seem to lead me in the right direction.

Any suggestions? Thank you for your time!

imaging a plane containing the line and the pinhole; this plane intersects with the image plane, the intersection
is obviously a line, isn't it just the image of the original line? I apologize for giving the answer directly, I simply can't think of any more disguised form ...
 
  • #3
Like I said, that was my first thought, but it seemed to hand wavy. Maybe I'm just worrying to much and that's a fine answer.

Thank you.
 
  • #4
jenny_shoars said:
Like I said, that was my first thought, but it seemed to hand wavy. Maybe I'm just worrying to much and that's a fine answer.

Thank you.

You're welcome, it's good to worry a bit more than others, as long as you're not obsessive :)
 

1. What is a pinhole camera model in computer vision geometry?

A pinhole camera model is a simplified mathematical representation of how a camera works. It assumes that light travels in straight lines and that a tiny pinhole is used to capture the image. This model is commonly used in computer vision to understand the relationship between the 3D world and the 2D image captured by the camera.

2. What are collinear points in computer vision geometry?

Collinear points are points that lie on the same straight line. In computer vision geometry, collinear points are used to determine the position and orientation of an object in 3D space. By identifying three or more collinear points in an image, the geometry of the object can be calculated.

3. How is the pinhole camera model used to estimate the position of collinear points?

The pinhole camera model uses a set of equations known as the camera projection matrix to map the 3D coordinates of an object onto a 2D image. By using the known parameters of the camera, such as focal length and image sensor size, the camera projection matrix can be used to estimate the position of collinear points in the image.

4. Can the pinhole camera model be used for all types of cameras?

No, the pinhole camera model is a simplified representation and may not accurately reflect the behavior of all types of cameras. For example, cameras with wide-angle lenses or fisheye lenses may require more complex models to accurately estimate the position of collinear points.

5. How can the accuracy of the pinhole camera model be improved?

The accuracy of the pinhole camera model can be improved by using more sophisticated camera models that take into account lens distortion and other factors. Additionally, using more advanced techniques such as bundle adjustment can help refine the estimated positions of collinear points and improve overall accuracy.

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