An Overview of Data Models and Query Languages for Content-based Video Retrieval

As a large amount of video data becomes publicly available, the need to model and query this data efficiently becomes significant. Consequently, content-based retrieval of video data turns out to be a challenging and important problem addressing areas such as video modelling, indexing, querying, etc. This paper reviews the video data models and query techniques, and surveys some open research problems in these areas. In particular, we investigate techniques that enable modelling and querying the video structure together with the content with emphasis on mapping low-level visual content (video features) to high-level semantics. We compare existing models, query languages, and give the concluding remarks.