Visual Entity Linking: A Preliminary Study
(2014) AAAI 2014 Workshop on Cognitive Computing for Augmented Human Intelligence p.46-49- Abstract
- In this paper, we describe a system that jointly extracts
entities appearing in images and mentioned in their ac-
companying captions. As input, the entity linking pro-
gram takes a segmented image together with its cap-
tion. It consists of a sequence of processing steps: part-
of-speech tagging, dependency parsing, and coreference
resolution that enables us to identify the entities as well
as possible textual relations from the captions. The pro-
gram uses the image regions labelled with a set of pre-
defined categories and computes WordNet similarities
between these labels and the entity names. Finally, the
program links the entities it... (More) - In this paper, we describe a system that jointly extracts
entities appearing in images and mentioned in their ac-
companying captions. As input, the entity linking pro-
gram takes a segmented image together with its cap-
tion. It consists of a sequence of processing steps: part-
of-speech tagging, dependency parsing, and coreference
resolution that enables us to identify the entities as well
as possible textual relations from the captions. The pro-
gram uses the image regions labelled with a set of pre-
defined categories and computes WordNet similarities
between these labels and the entity names. Finally, the
program links the entities it detected across the text and
the images. We applied our system on the Segmented
and Annotated IAPR TC-12 dataset that we enriched
with entity annotations and we obtained a correct as-
signment rate of 55.48% (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4580516
- author
- Weegar, Rebecka
; Hammarlund, Linus
; Tegen, Agnes
; Oskarsson, Magnus
LU
; Åström, Karl LU
and Nugues, Pierre LU
- organization
- publishing date
- 2014
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Cognitive computing for augmented human intelligence, papers presented at the Twenty-Eighth AAAI Conference on Artificial Intelligence
- pages
- 4 pages
- publisher
- AAAI
- conference name
- AAAI 2014 Workshop on Cognitive Computing for Augmented Human Intelligence
- conference dates
- 2014-07-27
- external identifiers
-
- scopus:84974688497
- ISBN
- 978-1-57735-664-6
- language
- English
- LU publication?
- yes
- id
- 07cb3525-9704-46c8-8e2c-deb259fcb965 (old id 4580516)
- date added to LUP
- 2016-04-04 13:33:12
- date last changed
- 2022-04-09 02:16:29
@inproceedings{07cb3525-9704-46c8-8e2c-deb259fcb965, abstract = {{In this paper, we describe a system that jointly extracts<br/><br> entities appearing in images and mentioned in their ac-<br/><br> companying captions. As input, the entity linking pro-<br/><br> gram takes a segmented image together with its cap-<br/><br> tion. It consists of a sequence of processing steps: part-<br/><br> of-speech tagging, dependency parsing, and coreference<br/><br> resolution that enables us to identify the entities as well<br/><br> as possible textual relations from the captions. The pro-<br/><br> gram uses the image regions labelled with a set of pre-<br/><br> defined categories and computes WordNet similarities<br/><br> between these labels and the entity names. Finally, the<br/><br> program links the entities it detected across the text and<br/><br> the images. We applied our system on the Segmented<br/><br> and Annotated IAPR TC-12 dataset that we enriched<br/><br> with entity annotations and we obtained a correct as-<br/><br> signment rate of 55.48%}}, author = {{Weegar, Rebecka and Hammarlund, Linus and Tegen, Agnes and Oskarsson, Magnus and Åström, Karl and Nugues, Pierre}}, booktitle = {{Cognitive computing for augmented human intelligence, papers presented at the Twenty-Eighth AAAI Conference on Artificial Intelligence}}, isbn = {{978-1-57735-664-6}}, language = {{eng}}, pages = {{46--49}}, publisher = {{AAAI}}, title = {{Visual Entity Linking: A Preliminary Study}}, url = {{https://lup.lub.lu.se/search/files/19769215/4580517.pdf}}, year = {{2014}}, }