Constructing vocabulary ensembles by different clustering algorithms for object categorization

Authors:
Hui-Lan Luo;Hui Wei;Yuan Ren
Affiliations:
Lab of Algorithm for Cognitive Model, School of Computer Science, Fudan University, Shanghai, China and School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, Ji ...;Lab of Algorithm for Cognitive Model, School of Computer Science, Fudan University, Shanghai, China;Lab of Algorithm for Cognitive Model, School of Computer Science, Fudan University, Shanghai, China
Venue:
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Year:
2009

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Abstract

In this paper, the advantages of ensemble methods are adapted to image categorization. A novel method is introduced for image categorization by constructing vocabulary ensembles using different clustering algorithms in the popular vocabulary approach. The vocabulary approach describes an image as a bag of discrete visual words, where the frequency distributions of these words are used for image categorization. Based on vocabularies formed by various clustering algorithms, a classifier ensemble is learned, which can jointly exploit different data structure of high dimensional descriptors. High classification accuracies of the proposed algorithm are demonstrated on three different datasets.