Object of Interest-based visual navigation, retrieval and semantic content identification system - Archive ouverte HAL Access content directly
Journal Articles Computer Vision and Image Understanding Year : 2004

Object of Interest-based visual navigation, retrieval and semantic content identification system

Abstract

This study presents a content-based image retrieval system IMALBUM based on local region of interest called object of interest (OOI). Each segmented or user-selected OOI is indexed with new local adapted descriptors associated to color, texture, and shape features. This local approach is an efficient way to associate the local semantic content with low-level descriptors (color, texture, shape, etc.) computed on regions selected by the user. So the user actively takes part in the indexing process (offline) and can use a selected OOI as a query for the retrieval system (online). The IMALBUM system proposes original functionalities. A visual navigation tool allows to surf in the image database when the user has no precise idea of what he is really searching for in the database. Furthermore, when an OOI is selected as a query for retrieval, a semantic content identification tool indicates to the user the probable class of this unknown object. The performance of these different tools are evaluated on different databases.
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Dates and versions

hal-01541465 , version 1 (28-11-2022)

Licence

Attribution - NonCommercial

Identifiers

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Khalid Idrissi, Guillaume Lavoué, Julien Ricard, Atilla Baskurt. Object of Interest-based visual navigation, retrieval and semantic content identification system. Computer Vision and Image Understanding, 2004, 94 (1-3), pp.271-294. ⟨10.1016/j.cviu.2003.10.014⟩. ⟨hal-01541465⟩
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