An approach to personalized video summarization based on user preferences analysis

Video summary is a sequence of still or moving pictures that represents the content of a video. Personalized summary provides a person with brief information reflecting essential message of the video according to his/her interests. Existing methods of discovering user's personal interests often demands from the user either extra efforts or extra equipment, e.g. manually setting up relative preferences or camera to capture of eyes movement. The paper presents an approach to constructing personalized video summary utilizing user's “like/neutral/dislike” estimations of videos watched beforehand. Summary is built as a sequence of scenes extracted from the video, which are most influencing the user. Most influencing scene contain a set of objects detected on video, which are in range of user's interest. Formal definitions of most influencing scene and range of interest are given and mathematical model of constructing personalized video summary is described.