Abstract. Information graphics such as bar, line and pie charts appear frequently in electronic media and often contain information that is not found elsewhere in documents. Unfortunately, sight-impaired users have difficulty accessing and assimilating information graphics. Our goal is an interactive natural language system that provides effective access to information graphics for sight-impaired individuals. This paper describes how image processing has been applied to transform an information graphic into an XML representation that captures all aspects of the graphic that might be relevant to extracting knowledge from it. It discusses the problems that were encountered in analyzing and categorizing components of the graphic, and the algorithms and heuristics that were successfully applied. The resulting XML representation serves as input to an evidential reasoning component that hypothesizes the message that the graphic was intended to convey.
This paper presents a corpus study that explores the extent to which captions contribute to recognizing the intended message of an information graphic. It then presents an implemented graphic interpretation system that takes into account a variety of communicative signals, and an evaluation study showing that evidence obtained from shallow processing of the graphic's caption has a significant impact on the system's success. This work is part of a larger project whose goal is to provide sight-impaired users with effective access to information graphics.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.