Computer Vision Foundations · free preview

Cameras as Linear Systems

Every camera as a matrix that maps a vector of world rays to a vector of sensor readings.

1. From glass to algebra

From glass to algebra

2. Flatland, a one-dimensional world

Flatland, a one-dimensional world

3. The pinhole is the identity

The pinhole is the identity

4. Cameras that do not look like cameras

Cameras that do not look like cameras

5. The meaning of the identity matrix

A flatland pinhole camera has imaging matrix A=I3\mathbf{A} = \mathbf{I}_3 and the world vector is (3,5,7)(3, 5, 7). What does the sensor read and why?

6. When measurements are not a picture

Which statement best captures why some cameras produce readings that do not look like images?

7. Reading a two-row matrix

A flatland camera has imaging matrix A=[100010]\mathbf{A} = \begin{bmatrix} 1 & 0 & 0 \\ 0 & 1 & 0 \end{bmatrix} and the world vector is (3,5,7)(3, 5, 7). Compute the sensor vector and write its second entry.

Practice this interactively

Free account · instant grading · spaced review that schedules itself.

Start this course for free