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SIGIR
2011
ACM

Mining weakly labeled web facial images for search-based face annotation

7 years 9 months ago
Mining weakly labeled web facial images for search-based face annotation
In this paper, we investigate a search-based face annotation framework by mining weakly labeled facial images that are freely available on the internet. A key component of such a search-based annotation paradigm is to build a database of facial images with accurate labels. This is however challenging since facial images on the WWW are often noisy and incomplete. To improve the label quality of raw web facial images, we propose an effective Unsupervised Label Refinement (ULR) approach for refining the labels of web facial images by exploring machine learning techniques. We develop effective optimization algorithms to solve the large-scale learning tasks efficiently, and conduct an extensive empirical study on a web facial image database with 400 persons and 40,000 web facial images. Encouraging results showed that the proposed ULR technique can significantly boost the performance of the promising search-based face annotation scheme. Categories and Subject Descriptors H.3.3 [Informa...
Dayong Wang, Steven C. H. Hoi, Ying He
Added 17 Sep 2011
Updated 17 Sep 2011
Type Journal
Year 2011
Where SIGIR
Authors Dayong Wang, Steven C. H. Hoi, Ying He
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