Generic and Specific Object Recognition for Semantic Retrieval of Images
| 言語 | 英語 |
|---|---|
| 種類 | 国際会議等の予稿 |
| 著者 | Martin Klinkigt，Koichi Kise，Andreas Dengel |
| 論文名 | Generic and Specific Object Recognition for Semantic Retrieval of Images |
| 論文誌名 | 15th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems |
| Vol. | 6881 |
| ページ | pp.397-406 |
| 出版社 | Springer LNCS |
| 査読の有無 | 有 |
| 年月 | 2011年9月 |
| 分野 | 物体認識 |
| キー | Klinkigt2011a (id=1234) |
要約
Since the availability of large digital image collections the need for a proper management of them raises. New technologies as annotations or tagging support the user by doing this task. However, this task is time-consuming and, therefore, automatic annotation systems are requested. Working outside of controlled laboratory environments this request is challenging. In this paper we propose a system automatically adapted to the user's needs, providing useful annotations. We utilize Wikipedia to learn instances and abstract classes. With an evaluation in a complex use-case and dataset we show the possibility of such an attempt and achieve practical recognition rates of 26% on specific instance and 64% on abstract class level.
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