In this paper, we propose a new method to measure the visualness of a concept. The visualness of a concept is generally defined as what extent a concept has visual characteristics. Even though the visualness of a concept is important and useful for various image search tasks, it has not received much spotlight yet. In this work, we especially focus on how to measure the visualness of a complex concept such as “round table”, “dry bed ” rather than a simple concept like “ball”, “apple”. To measure the visualness, we first collect sample images of a complex concept using web image search engines, and then group the images based on the visual features. Finally, we compute visual purity and weighted entropy of the clusters, which will act as a visualness score for the concept. Through various experiments, we show and discuss interesting results about the visualness of a concept
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