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Formulating queries for collecting training examples in visual concept classification

Albatal, Rami orcid logoORCID: 0000-0002-9269-8578, McGuinness, Kevin orcid logoORCID: 0000-0003-1336-6477, Hu, Feiyan orcid logoORCID: 0000-0001-7451-6438 and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2014) Formulating queries for collecting training examples in visual concept classification. In: Proceedings of the Third Workshop on Vision and Language, 23 Aug 2014, Dublin, Ireland. ISBN 978-1-873769-28-1

Video content can be automatically analysed and indexed using trained classifiers which map low-level features to semantic concepts. Such classifiers need training data consisting of sets of images which contain such concepts and recently it has been discovered that such training data can be located using text-based search to image databases on the internet. Formulating the text queries which locate these training images is the challenge we address here. In this paper we present preliminary results on TRECVid data of concept classification using automatically crawled images as training data and we compare the results with those obtained from manually annotated training sets.
Item Type:Conference or Workshop Item (Poster)
Event Type:Workshop
Additional Information:alan.smeaton@dcu.ie
Subjects:Computer Science > Computational linguistics
Computer Science > Digital video
Computer Science > Information retrieval
DCU Faculties and Centres:Research Institutes and Centres > INSIGHT Centre for Data Analytics
Published in: The 3rd Annual Meeting Of The EPSRC Network On Vision & Language and The 1st Technical Meeting of the European Network on Integrating Vision and Language A Workshop of the 25th International Conference on Computational Linguistics (COLING 2014). . Association for Computational Linguistics. ISBN 978-1-873769-28-1
Publisher:Association for Computational Linguistics
Official URL:http://www.aclweb.org/anthology/W14-5416
Copyright Information:This work is licensed under a Creative Commons Attribution 4.0 International Licence.
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland
ID Code:20078
Deposited On:10 Sep 2014 12:16 by Alan Smeaton . Last Modified 19 May 2021 11:10

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