SIRET Research Group
Department of Software Engineering
Faculty of Mathematics and Physics
Charles University
Malostranské nám. 25,
118 00 Prague
Czech Republic
email: | info@siret.cz |
phone: | +420 95155 4227 |
SIR
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(Smart image retrieval)
When determining visual similarity of two images, it is evaluated on feature representations which consist of some content-based image properties. The conventional feature representations aggregate and store these properties in global feature histograms (e.g., Recent feature representations, however, adaptively aggregate local image features in more flexible feature signatures, which can be Currently, the SIR engine operates in a demo mode as a standalone image search engine. In order to manage large image collections in real time, the engine employs original database indexing technology. The SIR engine also includes meta-search functionality that allows to augment/rerank/explore results provided by other image search engines, such as Google Images and others. The actual version of the online re-ranking and exploration tool employes the particle physics model, that both distributes images on the screen and automatically creates visually similar clusters (as a side effect). To refer this tool, you can refer our publications - Image Exploration using Online Feature Extraction and Reranking (ICMR, 2012) and SIR: The Smart Image Retrieval Engine (SISAP, 2012).
Multimedia
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SIRET Research Group
Department of Software Engineering
Faculty of Mathematics and Physics
Charles University
Malostranské nám. 25,
118 00 Prague
Czech Republic
email: | info@siret.cz |
phone: | +420 95155 4227 |