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. © 2011 Springer-Verlag.
CITATION STYLE
Klinkigt, M., Kise, K., & Dengel, A. (2011). Generic and specific object recognition for semantic retrieval of images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6881 LNAI, pp. 397–406). https://doi.org/10.1007/978-3-642-23851-2_41
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