Semantic hierarchies for image annotation: A survey

Anne-Marie Tousch 1, 2, 3 Stéphane Herbin 2 Jean-Yves Audibert 1, 3, 4
1 IMAGINE [Marne-la-Vallée]
LIGM - Laboratoire d'Informatique Gaspard-Monge, CSTB - Centre Scientifique et Technique du Bâtiment, ENPC - École des Ponts ParisTech
4 SIERRA - Statistical Machine Learning and Parsimony
DI-ENS - Département d'informatique de l'École normale supérieure, ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR8548
Abstract : In this survey, we argue that using structured vocabularies is capital to the success of image annotation. We analyze literature on image annotation uses and user needs, and we stress the need for automatic annotation. We briefly expose the difficulties posed to machines for this task and how it relates to controlled vocabularies. We survey contributions in the field showing how structures are introduced. First we present studies that use unstructured vocabulary, focusing on those introducing links between categories or between features. Then we review work using structured vocabularies as an input and we analyze how the structure is exploited.
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https://hal.archives-ouvertes.fr/hal-00624460
Contributor : Jean-Yves Audibert <>
Submitted on : Saturday, September 17, 2011 - 10:45:23 PM
Last modification on : Tuesday, March 26, 2019 - 2:24:42 PM

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Anne-Marie Tousch, Stéphane Herbin, Jean-Yves Audibert. Semantic hierarchies for image annotation: A survey. Pattern Recognition, Elsevier, 2012, 45 (1), pp.333-345. ⟨10.1016/j.patcog.2011.05.017⟩. ⟨hal-00624460⟩

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