Please use this identifier to cite or link to this item: https://doi.org/10.1145/1646396.1646452
Title: NUS-WIDE: A real-world web image database from National University of Singapore
Authors: Chua, T.-S. 
Tang, J. 
Hong, R. 
Li, H. 
Luo, Z.
Zheng, Y.
Keywords: Annotation
Flickr
Retrieval
Tag refinement
Training set construction
Web image
Issue Date: 2009
Source: Chua, T.-S.,Tang, J.,Hong, R.,Li, H.,Luo, Z.,Zheng, Y. (2009). NUS-WIDE: A real-world web image database from National University of Singapore. CIVR 2009 - Proceedings of the ACM International Conference on Image and Video Retrieval : 368-375. ScholarBank@NUS Repository. https://doi.org/10.1145/1646396.1646452
Abstract: This paper introduces a web image dataset created by NUS's Lab for Media Search. The dataset includes: (1) 269,648 images and the associated tags from Flickr, with a total of 5,018 unique tags; (2) six types of low-level features extracted from these images, including 64-D color histogram, 144-D color correlogram, 73-D edge direction histogram, 128-D wavelet texture, 225-D block-wise color moments extracted over 5x5 fixed grid partitions, and 500-D bag of words based on SIFT descriptions; and (3) ground-truth for 81 concepts that can be used for evaluation. Based on this dataset, we highlight characteristics of Web image collections and identify four research issues on web image annotation and retrieval. We also provide the baseline results for web image annotation by learning from the tags using the traditional k-NN algorithm. The benchmark results indicate that it is possible to learn effective models from sufficiently large image dataset to facilitate general image retrieval. Copyright 2009 ACM.
Source Title: CIVR 2009 - Proceedings of the ACM International Conference on Image and Video Retrieval
URI: http://scholarbank.nus.edu.sg/handle/10635/40888
ISBN: 9781605584805
DOI: 10.1145/1646396.1646452
Appears in Collections:Staff Publications

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