Evaluation of Local Descriptors for Automatic Image Annotation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43931925" target="_blank" >RIV/49777513:23520/17:43931925 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.5220/0006194305270534" target="_blank" >http://dx.doi.org/10.5220/0006194305270534</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0006194305270534" target="_blank" >10.5220/0006194305270534</a>
Alternative languages
Result language
angličtina
Original language name
Evaluation of Local Descriptors for Automatic Image Annotation
Original language description
In this paper we aim at evaluation of three local descriptors for the automatic image annotation (AIA) task. LBP, POEM and LDP descriptors are successfully used in many other domains such as face recognition. However, the utilization of them in the AIA field is rather infrequent. The annotation algorithm is based on the K-nearest neighbours (KNN) classifier where labels from K most similar images are “transferred” to the annotated one. We propose a label transfer method that assigns variable number of labels to each image. It is compared with an existing approach using constant number of labels. The proposed method is evaluated on three image datasets: Li photography, IAPR-TC12 and ESP. We show that the results of the utilized local descriptors are comparable to, and in many cases outperform the texture features usually used in AIA. We also show that the proposed label transfer method can increase the overall system performance especially for the IAPR-TC12 dataset.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 9th International Conference on Agents and Artificial Intelligence (ICAART 2017)
ISBN
978-989-758-220-2
ISSN
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e-ISSN
neuvedeno
Number of pages
8
Pages from-to
527-534
Publisher name
SciTePress
Place of publication
Setúbal
Event location
Porto
Event date
Feb 24, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000413244200055