In this paper, we presentan approach to clustering images for efficient retrieval using relative entropy. We start with the assumption that visual features are represented by prob...
The state of the art in visual object retrieval from large databases is achieved by systems that are inspired by text retrieval. A key component of these approaches is that local ...
James Philbin, Ondrej Chum, Michael Isard, Josef S...
State-of-the-art image retrieval systems achieve scalability by using bag-of-words representation and textual retrieval methods, but their performance degrades quickly in the face...
The paper presents a model of visual attention combined with eye tracking to drive content-based retrieval of image data in order to facilitate understanding and development of ne...
Mariofanna G. Milanova, Stuart Harvey Rubin, Roume...
Content based search in audio-visual collections requires media specific analysis for extracting low level features to be efficiently indexed and searched. We present the SAPIR ...
Walter Allasia, Fabrizio Falchi, Francesco Gallo, ...