Robust cross-media transfer for visual event detection

Authors:
Yang Yang;Yi Yang;Zi Huang;Jiajun Liu;Zhigang Ma
Affiliations:
The University of Queensland, Brisbane, Australia;Carnegie Mellon University, Pittsburgh, USA;The University of Queensland, Brisbane, Australia;The University of Queensland, Brisbane, Australia;University of Trento, Trento, Italy
Venue:
Proceedings of the 20th ACM international conference on Multimedia
Year:
2012

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Abstract

In this paper, we present a novel approach, named Robust Cross-Media Transfer (RCMT), for visual event detection in social multimedia environments. Different from most existing methods, the proposed method can directly take different types of noisy social multimedia data as input and conduct robust event detection. More specifically, we build a robust model by employing an l2,1-norm regression model featuring noise tolerance, and also manage to integrate different types of social multimedia data by minimizing the distribution difference among them. Experimental results on real-life Flickr image dataset and YouTube video dataset demonstrate the effectiveness of our proposal, compared to state-of-the-art algorithms.