Image Retrieval over Networks : Active Learning using Ant Algorithm

Abstract : In this article, we present a framework for distributed content based image retrieval with online learning based on ant-like mobile agents. Mobile agents crawl the network to find images matching a given example query. The images retrieved are shown to the user who labels them, following the classical relevant feedback scheme. The labels are used both to improve the similarity measure used for the retrieval and to learn paths leading to sites containing relevant images. The relevant paths are learned in an ethologically inspired way. We made experiments on the trecvid 2005 keyframe dataset showing that learning both the similarity function and the localization of the relevant images leads to a significant improvement. We also present an extension with the reuse of learned paths for later sessions leading to a further improvement.
Document type :
Journal articles
Complete list of metadatas

Cited literature [28 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-00656363
Contributor : David Picard <>
Submitted on : Wednesday, January 4, 2012 - 9:08:04 AM
Last modification on : Thursday, March 21, 2019 - 2:37:37 PM
Long-term archiving on : Thursday, April 5, 2012 - 2:21:46 AM

File

manuscript.pdf
Files produced by the author(s)

Identifiers

Citation

David Picard, Matthieu Cord, Arnaud Revel. Image Retrieval over Networks : Active Learning using Ant Algorithm. IEEE Transactions on Multimedia, Institute of Electrical and Electronics Engineers, 2008, 10 (7), pp.1356-1365. ⟨10.1109/TMM.2008.2004913⟩. ⟨hal-00656363⟩

Share

Metrics

Record views

720

Files downloads

258