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.
Chapter PDF
References
Makadia, A., Pavlovic, V., Kumar, S.: Baselines for image annotation. International Journal of Computer Vision 90(1), 88–105 (2010)
Verma, Y., Jawahar, C.V.: Image annotation using metric learning in semantic neighbourhoods. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part III. LNCS, vol. 7574, pp. 836–849. Springer, Heidelberg (2012)
Weston, J., Bengio, S., Usunier, N.: Wsabie: Scaling up to large vocabulary image annotation. In: IJCAI (2011)
Guillaumin, M., Mensink, T., Verbeek, J., Schmid, C.: Tagprop: Discriminative metric learning in nearest neighbor models for image auto-annotation. In: ICCV, pp. 309–316 (2009)
Jin, Y., Khan, L., Wang, L., Awad, M.: Image annotations by combining multiple evidence and wordnet. ACM Multimedia (2005)
Wang, M., Zhou, X., Xu, H.: Web image annotation based on automatically obtained noisy training set. In: Zhang, Y., Yu, G., Bertino, E., Xu, G. (eds.) APWeb 2008. LNCS, vol. 4976, pp. 637–648. Springer, Heidelberg (2008)
Opsahl, T., Agneessens, F., Skvoretz, J.: Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks 32(3), 245–251 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chandrashekar, V., Kumar, S., Jawahar, C.V. (2013). Image Annotation in Presence of Noisy Labels. In: Maji, P., Ghosh, A., Murty, M.N., Ghosh, K., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2013. Lecture Notes in Computer Science, vol 8251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45062-4_52
Download citation
DOI: https://doi.org/10.1007/978-3-642-45062-4_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-45061-7
Online ISBN: 978-3-642-45062-4
eBook Packages: Computer ScienceComputer Science (R0)