Image Annotation in Presence of Noisy Labels
Venue
International Conference on Pattern Recognition and Machine Intelligence (2013) (to appear)
Publication Year
2013
Authors
Chandrashekhar V., Shailesh Kumar, C. V. Jawahar
BibTeX
Abstract
Labels associated with social images are valuable source of information for tasks
of image annotation, understanding and retrieval. These labels are often found to
be noisy, mainly due to the collaborative tagging activities of users. Existing
methods on annotation have been developed and verified on noise free labels of
images. In this paper, we propose a novel and generic framework that exploits the
collective knowledge embedded in noisy label co-occurrence pairs to derive robust
annotations. We compare our method with a well-known image annotation algorithm and
show its superiority in terms of annotation accuracy on benchmark Corel5K and ESP
datasets in presence of noisy labels.
