Relation To Optical Flow
The motion field is an ideal construction, based on the idea that it is possible to determine the motion of each image point, and above it is described how this 2D motion is related to 3D motion. 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 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. There are several different ways to compute the optical flow based on different criteria of how an optical estimation should be made.
Read more about this topic: Motion Field
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