A New Method for Identifying the Relationship of Characters in the Video

With the development of information technology, more and more videos appear on the Internet. As relationship of characters is an important part of a video content, audiences can understand storyline of the video easily through the relationship. Meanwhile, the relationship can facilitate audiences to watch videos that they are interested in efficiently. In the last years, researchers have analyzed video characters in researches of video content detection. However, they treated characters as a number of independent objects and ignore their relationships. In this paper, we present a new approach to analyze the relationship of characters in a video by extracting the semantics of the video. The semantics of the video are a description of the things that made up with subtitle, action, character expression, Video semantic features are extracted and fused to identify the relationship of characters in the video. In our experiment, images are selected from the video that can easily show the relationship of the characters as the dataset. The accuracy of in the experiment is 89%. Its performance is better than the accuracy of using only one feature. At the same time, we predicted the relationship of characters using our model in Friends. The relationship of characters is almost accurately predicted under the comparison of the facts of Friends.