Abstract. Evaluation is crucial for the success of most research domains, and image retrieval is no exception to this. Recently, several benchmarks have been developed for visual i...
Most of the currently existing image retrieval systems make use of either low-level features or semantic (textual) annotations. A combined usage during annotation and retrieval is ...
One of the main challenges in content-based image retrieval still remains to bridge the gap between low-level features and semantic information. In this paper, we present our first...
Daniel Racoceanu, Caroline Lacoste, Roxana Teodore...
This paper describes research being employed in the Tripod project to improve the retrieval of photographs through a comprehensive knowledge of where they were taken. The methods ...
Popular image retrieval schemes generally rely only on a single mode, (either low level visual features or embedded text) for searching in multimedia databases. Many popular image...
We address the problem of large scale image retrieval in a wide-baseline setting, where for any query image all the matching database images will come from very different viewpoint...
—A major research subject in image databases is to support efficient and effective access to images based on their visual content. In color image databases, this requires to sup...
Alberto Del Bimbo, Mauro Mugnaini, Pietro Pala, F....
In this paper we propose a new General Image DataBase (GIDB) model. The model establishes taxonomy based on the systematisation of existing approaches. The GIDB model is based on t...
Blobworld is a system for image retrieval based on nding coherent image regions which roughly correspond to objects. Each image is automatically segmented into regions blobs"...
Chad Carson, Megan Thomas, Serge Belongie, Joseph ...
This paper presents a face detection technique and its applications in image retrieval. Even though this face detection method has relatively high false positives and low detectio...