Detecting prominence of objects in video information

A video-processing technique uses machine-trained logic to detect and track people that appear in video information. The technique then ranks the prominence of these people in the video information, to produce ranking information. The prominence of a person reflects a level of importance of the person in the video information, corresponding to the capacity of the person to draw the attention of a viewer. For instance, the prominence of the person reflects, at least in part, an extent to which the person appears in the video information. The technique performs its ranking based on person-specific feature information. The technique produces each instance of person-specific feature information by accumulating features pertaining to a particular person. One or more application systems make use of the ranking information to control the presentation of the video information.