"Image Search by Concept Map" is an example of how multimedia has increased the complexity of information-retrieval problems. Digital images are, after text, the second-most prevalent media on the Web. The challenge is to devise a more intuitive way for users to query for images.
"[Image Search by Concept Map] is a totally new way of searching web images," says Xian-Sheng Hua of Microsoft Research Asia. "When compared to text-box-based image searches. In this model, we allow users to specify the spatial positions of the query terms. The typed keywords indicate the desired visual concepts, or objects, within the image. The spatial relation of the keywords indicates the desired layout of the visual contents. We translate from a concept map to a visual instance map."
The authors present in this paper a system that lets users indicate not only what semantic concepts are expected to appear but also how these concepts are spatially distributed in the desired images. To this end, they propose a new image search interface to enable users to formulate a query, called "concept map", by intuitively typing textual queries in a blank canvas to indicate the desired spatial positions of the concepts. In the ranking process, by interpreting each textual concept as a set of representative visual instances, the concept map query is translated into a visual instance map, which is then used to evaluate the relevance of the image in the database. Experimental results demonstrate the effectiveness of the proposed system.
For a detailed discussion of this topic, see Image Search by Concept Map.