10. The process of claim 9 , wherein the frequency of motion features comprise one or more of: a motion frequency feature measuring the percentage of frames in the video where the magnitude of motion is greater than or equal to a prescribed motion frequency threshold; or another motion frequency feature measuring the percentage of frames in the video where the magnitude of motion is greater than or equal to another prescribed motion frequency threshold; or a motion present feature measuring the length of the longest sequence of frames in the video where there is motion; or a motion not present feature measuring the length of the longest sequence of frames in the video where there is no motion.
9. A computer-implemented process for identifying the presentation style of a video, comprising the actions of: using one or more computing devices that are in communication with each other via a computer network to perform the following process actions: receiving the video; computing a set of motion features that represent the video, wherein the motion features are based on how the video changes from frame to frame, the motion features comprising one or more of, frequency of motion features measuring how often motion occurs in the video, or amount of motion features measuring how much motion takes place in the video, or type of motion features specifying the type of motion that takes place in the video; and using a pre-learned video presentation style classifier to weight each of the motion features in said set and determine a presentation style that is predominately employed in the video, said presentation style determination being based on the weighting of said features.