DocumentCode :
509154
Title :
Constructing Vocabulary Ensembles by Different Clustering Algorithms for Object Categorization
Author :
Luo, Hui-lan ; Wei, Hui ; Ren, Yuan
Author_Institution :
Lab. of Algorithm for Cognitive Model, Fudan Univ., Shanghai, China
Volume :
2
fYear :
2009
fDate :
21-22 Nov. 2009
Firstpage :
461
Lastpage :
464
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.
Keywords :
image recognition; object recognition; classifier ensemble; clustering algorithms; discrete visual words; frequency distributions; image categorization; object categorization; vocabulary ensembles; Application software; Clustering algorithms; Computer science; Data structures; Electronic mail; Histograms; Humans; Information technology; Machine learning algorithms; Vocabulary; Image categorization; clustering algorithm; machine learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
Conference_Location :
Nanchang
Print_ISBN :
978-0-7695-3859-4
Type :
conf
DOI :
10.1109/IITA.2009.38
Filename :
5369514
Link To Document :
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