As motion detection is of fundamental importance to both artificial and biological visual systems, there have been a large amount of studies on this subject ranging between two extremes of a wide spectrum. From a pure computer vision point of view, the goal of the studies at one end of the spectrum is to compute motion, such as optic flow, using whatever mathematical tools most effective for the goal. The studies at the other end of the spectrum are concerned with the motion processing in the biological visual system with biological plausibility in mind. There have been many algorithms and models developed to compute motions for either of the two purposes. Most of them are just variations and different implementations of a few basic types of methods, based on gradient, correlation, or spatiotemporal energy models. In the following we will briefly review these basic methods. For more detailed discussion of the specific algorithms and models, the reader is referred to two survey articles [18] (for computer vision study) and [19] (for biological vision study) and the literatures thereby cited.