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
