The algorithms will flag such a motion as to whether it arises from a person, a vehicle, or from trees blowing in the wind. In order to enhance the information content of the threat map, techniques for classifying motion will be applied. In particular, primary classification techniques have been formulated that can flag a motion as smooth, periodic, episodic, or statistical in nature. Smooth motions include those due to mostly rigid objects such as vehicles. Periodic motions arise primarily from locomoting people or animals and from certain sorts of machinery.
Episodic movements are time-bounded motions such as an explosion or throwing an object.
Statistical movements arise from non-rigid motions of complex objects such as waves on water, or vegetation blowing in the wind. Second tier classification techniques for periodic and statistical motions are being developed which have already exhibited some success. Work is also being done on classification techniques for episodic motion. Smooth motion does not have much distinguishing character, so object recognition techniques seem the best bet for identifying smoothly moving objects. The combination of information from color and multiple views for deriving a comprehensive interpretation of scene reflections and illumination.