Image and Video Indexing using Networks of Operators

Stéphane Ayache 1 Georges Quénot 2
2 MRIM - Modélisation et Recherche d’Information Multimédia [Grenoble]
LIG - Laboratoire d'Informatique de Grenoble, Inria - Institut National de Recherche en Informatique et en Automatique
Abstract : This article presents a framework for the design of concept detection systems for image and video indexing. This framework integrates in a homogeneous way all the data and processing types. The semantic gap is crossed in a number of steps, each producing a small increase in the abstraction level of the handled data. All the data inside the semantic gap and on both sides included are seen as a homogeneous type called \em numcept and all the processing modules between the various numcepts are seen as a homogeneous type called \em operator. Concepts are extracted from the raw signal using networks of operators operating on numcepts. These networks can be represented as data-flow graphs and the introduced homogenizations allow fusing elements regardless of their nature. Low-level descriptors can be fused with intermediate of final concepts.
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Journal articles
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https://hal.inria.fr/hal-00953803
Contributor : Marie-Christine Fauvet <>
Submitted on : Friday, February 28, 2014 - 4:00:56 PM
Last modification on : Friday, April 12, 2019 - 11:06:11 AM

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  • HAL Id : hal-00953803, version 1

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Stéphane Ayache, Georges Quénot. Image and Video Indexing using Networks of Operators. EURASIP Journal on Image and Video Processing, Springer, 2007. ⟨hal-00953803⟩

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