Motion field

In computer vision, the motion field is an ideal representation of motion in three-dimensional space (3D) as it is projected onto a camera image.

The motion field can formally be defined as the time derivative of the image position of all image points given that they correspond to fixed 3D points.

This means that the motion field can be represented as a function which maps image coordinates to a 2-dimensional vector.

: Assuming that the scene depicted by the camera is dynamic; it consists of objects moving relative each other, objects which deform, and possibly also the camera is moving relative to the scene, a fixed point in 3D space is mapped to varying points in the image.

Differentiating the previous expression with respect to time gives Here is the motion field and the vector u is dependent both on the image position

matrix This relation implies that the motion field, at a specific image point, is invariant to 3D motions which lies in the null space of

For example, in the case of a pinhole camera all 3D motion components which are directed to or from the camera focal point cannot be detected in the motion field.

In practice, however, the true motion field can only be approximated based on measurements on image data.

The problem is that in most cases each image point has an individual motion which therefore has to be locally measured by means of a neighborhood operation on the image data.

As consequence, the correct motion field cannot be determined for certain types of neighborhood and instead an approximation, often referred to as the optical flow, has to be used.

For example, a neighborhood which has a constant intensity may correspond to a non-zero motion field, but the optical flow is zero since no local image motion can be measured.

Similarly, a neighborhood which is intrinsic 1-dimensional (for example, an edge or line) can correspond to an arbitrary motion field, but the optical flow can only capture the normal component of the motion field.

There are also other effects, such as image noise, 3D occlusion, temporal aliasing, which are inherent to any method for measuring optical flow and causes the resulting optical flow to deviate from the true motion field.

In short, the motion field cannot be correctly measured for all image points, and the optical flow is an approximation of the motion field.