Detail publikace

Annotating images with suggestions - user study of a tagging system

HRADIŠ, M. KOLÁŘ, M. KRÁL, J. LÁNÍK, A. ZEMČÍK, P. SMRŽ, P.

Originální název

Annotating images with suggestions - user study of a tagging system

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

This paper explores the concept of image-wise tagging. It introduces a web-based user interface for image annotation, and a novel method for modeling dependencies of tags using Restricted Boltzmann Machines which is able to suggest probable tags for an image based on previously assigned tags. According to our user study, our tag suggestion methods improve both user experience and annotation speed. Our results demonstrate that large datasets with semantic labels (such as in TRECVID Semantic Indexing) can be annotated much more efficiently with the proposed approach than with current class-domain-wise methods, and produce higher quality data.

Klíčová slova

Restricted Boltzmann Machine, human-assisted learning, user interface, image tagging, crowdsourcing, image classification

Autoři

HRADIŠ, M.; KOLÁŘ, M.; KRÁL, J.; LÁNÍK, A.; ZEMČÍK, P.; SMRŽ, P.

Rok RIV

2012

Vydáno

10. 7. 2012

Nakladatel

Springer Verlag

Místo

Brno

ISBN

978-3-642-33139-8

Kniha

Advanced Concepts for Intelligent Vision Systems

Edice

Lecture Notes in Computer Science

ISSN

0302-9743

Periodikum

Lecture Notes in Computer Science

Číslo

7517

Stát

Spolková republika Německo

Strany od

155

Strany do

166

Strany počet

12

URL

BibTex

@inproceedings{BUT96955,
  author="Michal {Hradiš} and Martin {Kolář} and Jiří {Král} and Aleš {Láník} and Pavel {Zemčík} and Pavel {Smrž}",
  title="Annotating images with suggestions - user study of a tagging system",
  booktitle="Advanced Concepts for Intelligent Vision Systems",
  year="2012",
  series="Lecture Notes in Computer Science",
  journal="Lecture Notes in Computer Science",
  number="7517",
  pages="155--166",
  publisher="Springer Verlag",
  address="Brno",
  doi="10.1007/978-3-642-33140-4\{_}14",
  isbn="978-3-642-33139-8",
  issn="0302-9743",
  url="https://www.fit.vut.cz/research/publication/9990/"
}

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