In computer vision a camera matrix or (camera) projection matrix is a matrix which describes the mapping of a pinhole camera from 3D points in the world to 2D points in an image.
Let be a representation of a 3D point in homogeneous coordinates (a 4-dimensional vector), and let be a representation of the image of this point in the pinhole camera (a 3-dimensional vector). Then the following relation holds
where is the camera matrix and the sign implies that the left and right hand sides are equal up to a non-zero scalar multiplication.
Since the camera matrix is involved in the mapping between elements of two projective spaces, it too can be regarded as a projective element. This means that it has only 11 degrees of freedom since any multiplication by a non-zero scalar results in an equivalent camera matrix.
Read more about Camera Matrix: Derivation, Normalized Camera Matrix and Normalized Image Coordinates, General Camera Matrix
Famous quotes containing the words camera and/or matrix:
“The camera relieves us of the burden of memory. It surveys us like God, and it surveys for us. Yet no other god has been so cynical, for the camera records in order to forget.”
—John Berger (b. 1926)
“As all historians know, the past is a great darkness, and filled with echoes. Voices may reach us from it; but what they say to us is imbued with the obscurity of the matrix out of which they come; and try as we may, we cannot always decipher them precisely in the clearer light of our day.”
—Margaret Atwood (b. 1939)