Publication detail
Annotating images with suggestions - user study of a tagging system
HRADIŠ, M. KOLÁŘ, M. KRÁL, J. LÁNÍK, A. ZEMČÍK, P. SMRŽ, P.
Original Title
Annotating images with suggestions - user study of a tagging system
English Title
Annotating images with suggestions - user study of a tagging system
Type
conference paper
Language
en
Original Abstract
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.
English abstract
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.
Keywords
Restricted Boltzmann Machine, human-assisted learning, user interface, image tagging, crowdsourcing, image classification
RIV year
2012
Released
10.07.2012
Publisher
Springer Verlag
Location
Brno
ISBN
978-3-642-33139-8
Book
Advanced Concepts for Intelligent Vision Systems
Edition
Lecture Notes in Computer Science
Issue number
NEUVEDEN
Pages from
155
Pages to
166
Pages count
12
URL
Documents
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",
annote="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.",
address="Springer Verlag",
booktitle="Advanced Concepts for Intelligent Vision Systems",
chapter="96955",
doi="10.1007/978-3-642-33140-4_14",
edition="Lecture Notes in Computer Science",
howpublished="print",
institution="Springer Verlag",
number="7517",
year="2012",
month="july",
pages="155--166",
publisher="Springer Verlag",
type="conference paper"
}