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Content Based Detection of Popular Images in Large Image Databases
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology.
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology.ORCID iD: 0000-0001-7557-4904
2011 (English)In: 17th Scandinavian Conference on Image Analysis, SCIA 2011 / [ed] A. Heyden, F. Kahl, Berlin Heidelberg: Springer-Verlag , 2011, 218-227 p.Conference paper, Published paper (Refereed)
Abstract [en]

We investigate the use of standard image descriptors and a supervised learning algorithm for estimating the popularity of images. The intended application is in large scale image search engines, where the proposed approach can enhance the user experience by improving the sorting of images in a retrieval result. Classification methods are trained and evaluated on real-world user statistics recorded by a major image search engine. The conclusion is that for many image categories, the combination of supervised learning algorithms and standard image descriptors results in useful popularity predictions.

Place, publisher, year, edition, pages
Berlin Heidelberg: Springer-Verlag , 2011. 218-227 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 6688
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-68662DOI: 10.1007/978-3-642-21227-7_21ISBN: 978-3-642-21226-0 (print)OAI: oai:DiVA.org:liu-68662DiVA: diva2:419507
Available from: 2011-05-26 Created: 2011-05-26 Last updated: 2016-08-31

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Solli, MartinLenz, Reiner

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