Automatic suggestion of presentation image for storytelling

Digital storytelling applications are playing an increasingly important role in people's daily life. In contemporary storytelling applications such as PowerPoint presentation and macro/micro blogs, good presentation images are always highly desired by content creators to boost their presentation in an intuitive and attractive way. Existing studies, however, have not yet addressed the challenging problem of how to select the most appropriate presentation images for storytelling. In this paper, we formulate this problem of presentation image suggestion (given a textual query) as selecting images by maximizing visual and semantic diversity from web image search results of suggested queries. The proposed framework consists of two novel components: 1) click-through-based query suggestion, which is designed to suggest textual queries by searching relevant queries in a constructed query graph that can reflect diverse aspects of a given query, and 2) query-based image selection, which selects the most appropriate presentation images by keeping semantic relevance while maximizing visual diversity and quality, using a novel model based on Conditional Random Field (CRF) by individual and correlation characters. We evaluate the proposed approach by comparing with several baselines and a thorough subjective survey. The evaluations show inspiring results using the proposed approach for automatic suggestion of images for storytelling.