Publication details

Evaluation Platform for Content-based Image Retrieval Systems



Year of publication 2011
Type Article in Proceedings
Conference International Conference on Theory and Practice of Digital Libraries 2011, LNCS 6966
MU Faculty or unit

Faculty of Informatics

Field Informatics
Keywords large-scale image dataset; visual and textual annotation; ground truth; collaboration service
Description In all subelds of information retrieval, test datasets and ground truth data are important tools for testing and comparison of new search methods. This is also reflected by the image retrieval community where several benchmarking activities have been created in past years using different test data. However, the number of available test collections is still rather small and the existing ones are often limited in size or accessible only to the participants of benchmarking competitions. In this work, we present a new freely-available large-scale dataset for evaluation of content-based image retrieval systems. The dataset consists of 20 million high-quality images with ve visual descriptors and rich and systematic textual annotations, a set of 100 test query objects and a semi-automatically collected ground truth data veried by users. Furthermore, we provide services that enable exploitation and collaborative expansion of the ground truth.
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