Web画像検索のためのキーワード特徴の抽出と合成によるクエリ画像生成

概要

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Keyword-based image retrieval (KBIR) from WWW image database enables users to obtain a lot of images corresponding their query keywords. However, when users need images that have severely limited features, KBIR is an inefficient option. Content-based image retrieval (CBIR) is proposed for solving this problem, but it requires that users prepare their query images, which is also time consuming. We have developed a new easy-to-use method to create precise query images only from the keywords. In our method, the query keywords are divided into those for KBIR and those for representing specific features. Then, original features of images from KBIR are modified into the extracted features. From these synthesized images, users can easily choose the query image that best represents what they want with relevance feedback. The experimental results show that our method enables users to obtain proper query images more easily than conventional methods.
社団法人映像情報メディア学会の論文