Augmenting image processing with social tag mining for landmark recognition

Authors:
Amogh Mahapatra;Xin Wan;Yonghong Tian;Jaideep Srivastava
Affiliations:
Department of CS, University of Minnesota;Department of CS, University of Minnesota;School of EE & CS, Peking University, China;Department of CS, University of Minnesota
Venue:
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part I
Year:
2011

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Social Multimedia Computing

Computer

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Abstract

Social Multimedia computing is a new approach which combines the contextual information available in the social networks with available multimedia content to achieve greater accuracy in traditional multimedia problems like face and landmark recognition. Tian et al.[12] introduce this concept and suggest various fields where this approach yields significant benefits. In this paper, this approach has been applied to the landmark recognition problem. The dataset of flickr.com was used to select a set of images for a given landmark. Then image processing techniques were applied on the images and text mining techniques were applied on the accompanying social metadata to determine independent rankings. These rankings were combined using models similar to meta search engines to develop an improved integrated ranking system. Experiments have shown that the recombination approach gives better results than the separate analysis.