Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICTAI.2012.64
Title: Web image organization and object discovery by actively creating visual clusters through crowdsourcing
Authors: Chen, Q.
Wang, G.
Tan, C.L. 
Keywords: active clustering
crowdsourcing
image organization
object discovery
Issue Date: 2012
Citation: Chen, Q., Wang, G., Tan, C.L. (2012). Web image organization and object discovery by actively creating visual clusters through crowdsourcing. Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI 1 : 419-427. ScholarBank@NUS Repository. https://doi.org/10.1109/ICTAI.2012.64
Abstract: In this paper, we propose to organize web images by actively creating visual clusters via crowd sourcing. We develop a two-phase framework to efficiently and effectively combine computers and a large number of human workers to build high quality visual clusters. The first phase partitions an image collection into multiple clusters, the second phase refines each generated cluster independently. In both phases, informative images are selected by computers and manually labeled by the crowds to learn improved models. Our method can be naturally extended to discover object categories in a collection of image segments. Experimental results on several data sets demonstrate the promise of our developed approach on both web image organization and object discovery tasks. © 2012 IEEE.
Source Title: Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI
URI: http://scholarbank.nus.edu.sg/handle/10635/78428
ISBN: 9780769549156
ISSN: 10823409
DOI: 10.1109/ICTAI.2012.64
Appears in Collections:Staff Publications

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