The Internet has a huge volume of unlabeled videos from diverse sources, making it difficult for video providers to organize and for viewers to consume the content. This paper defines the problem of video aboutness generation (i.e., the automatic generation of a concise natural-language description about a video) and characterizes its differences from closely related problems such as video summarization and video caption. We then made an attempt to provide a solution to this problem. Our proposed system exploits multi-modal analyses of audio, text and visual content of the video and leverages the Internet to identify a top-matched aboutness description. Through an exploratory study involving human judges evaluating a variety of test videos, we found support of the proposed approach.
展开▼
