Video, at its most basic, is a time sequence of images, which are in turn simply two dimensional arrays of color information. In order to segment a video into meaningful pieces (objects in images, or scenes within videos), it is necessary to provide a context, both in space and time, to extract meaningful elements from this image sequence. Humans are naturally able to perform this task, but it's desirable to do so algorithmically. Developing a method to achieve this, however, is a complex problem. At an NTSC frame rate of 30 frames per second, even a short video of 30 seconds comprises 900 frames. The identification of distinct video elements would be tedious if human intervention were required for every frame. For moderate amounts of video material, manual segmentation is clearly unrealistic.