Recognition of motion from temporal texture

A method of visual motion recognition applicable to a range of naturally occurring motions that are characterized by spatial and temporal uniformity is described. The underlying motivation is the observation that, for objects that typically move, it is frequently easier to identify them when they are moving than when they are stationary. Specifically, it is shown that certain statistical spatial and temporal features that can be derived from approximations to the motion field have invariant properties, and can be used to classify regional activities such as windblown trees, ripples on water, or chaotic fluid flow, that are characterized by complex, non-rigid motion. The technique is referred to as temporal texture analysis, in analogy to the techniques developed to classify gray-scale textures. The techniques are demonstrated on a number of real-world image sequences containing complex movement. The work has practical application in monitoring and surveillance, and as a component of a sophisticated visual system.<>