Please use this identifier to cite or link to this item: https://doi.org/10.1145/1873951.1874139
Title: One person labels one million images
Authors: Tang, J. 
Chen, Q.
Yan, S. 
Chua, T.-S. 
Jain, R.
Keywords: image
large-scale
manual annotation
Issue Date: 2010
Source: Tang, J.,Chen, Q.,Yan, S.,Chua, T.-S.,Jain, R. (2010). One person labels one million images. MM'10 - Proceedings of the ACM Multimedia 2010 International Conference : 1019-1022. ScholarBank@NUS Repository. https://doi.org/10.1145/1873951.1874139
Abstract: Targeting the same objective of alleviating the manual work as automatic annotation, in this paper, we propose a novel framework with minimal human effort to manually annotate a large-scale image corpus. In this framework, a dynamic multi-scale cluster labeling strategy is proposed to manually label the clusters of similar image regions. The users label the multi-scale clusters of regions instead of individual images, thus each labeling operation can annotate hundreds or even thousands of images simultaneously with much reduced manual work. Meanwhile the manual labeling guarantees the accuracy of the labels. Compared to automatic annotation, the proposed framework is more flexible, general and effective, especially for annotating those labels with large semantic gaps. Experiments on NUS-WIDE dataset demonstrate that the proposed fast manual annotation framework is much more effective than automatic annotation and comparatively efficient. © 2010 ACM.
Source Title: MM'10 - Proceedings of the ACM Multimedia 2010 International Conference
URI: http://scholarbank.nus.edu.sg/handle/10635/43266
ISBN: 9781605589336
DOI: 10.1145/1873951.1874139
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