Abstract
Besides the use of traditional textual semantic description to convey the meanings of a certain word or concept, visual illustration is a complementary and often more intuitive way to interpret the concept. Thus the technique that converts word to image is desirable though it is very difficult. Since a concept usually has different semantic aspects, we need several correct and semantically-rich images to represent the concept under different context. In this chapter, we explore how to leverage the web image collection and existing knowledge resources to fulfill such task and develop a novel multimedia application system named Word2Image. Various techniques, including the correlation analysis, semantic and visual clustering are adapted into our system to produce the sets of high quality, precise, diverse and representative images to visually translate a given concept. The objective and subjective evaluations show the feasibility and effectiveness of our approach.
Keywords: Word2Image, Image Search, Social Media, Flickr, Semantic Aspect, Visual Translation, Multimedia Dictionary, Visual Saliency, Correlation Analysis, Tag Saliency
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