Discriminative Reference-Based Scene Image Categorization

Qun LI  Ding XU  Le AN  

IEICE TRANSACTIONS on Information and Systems   Vol.E97-D   No.10   pp.2823-2826
Publication Date: 2014/10/01
Publicized: 2014/07/22
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2014EDL8118
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
scene categorization,  reference-based scheme,  affinity propagation algorithm,  discriminative reference-set,  

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A discriminative reference-based method for scene image categorization is presented in this letter. Reference-based image classification approach combined with K-SVD is approved to be a simple, efficient, and effective method for scene image categorization. It learns a subspace as a means of randomly selecting a reference-set and uses it to represent images. A good reference-set should be both representative and discriminative. More specifically, the reference-set subspace should well span the data space while maintaining low redundancy. To automatically select reference images, we adapt affinity propagation algorithm based on data similarity to gather a reference-set that is both representative and discriminative. We apply the discriminative reference-based method to the task of scene categorization on some benchmark datasets. Extensive experiment results demonstrate that the proposed scene categorization method with selected reference set achieves better performance and higher efficiency compared to the state-of-the-art methods.