IMAGE CLASSIFICATION BASED ON PYRAMID HISTOGRAM OF TOPICS

被引：0

作者：

Lu, Fuxiang ^{[1
]}

Yang, Xiaokang ^{[1
]}

Zhang, Rui ^{[1
]}

Yu, Songyu ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Inst Image Commun & Informat Proc, Shanghai Key Lab Digital Media Proc & Transmiss, Shanghai 200240, Peoples R China

来源：

ICME: 2009 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, VOLS 1-3 | 2009年

关键词：

Image classification; PHOTO; pLSA; AdaBoost;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

In this paper we propose PHOTO (Pyramid Histogram Of TOpics), a new representation for image classification. We partition the image into hierarchical cells and learn the topic histogram using pLSA over each cell with EM algorithm. Then we concatenate the topic histograms over the cells at all levels to form a "long" vector, i.e. pyramid histogram of topics. Finally AdaBoost classifiers are used to select the topics most discriminative for class recognition. Experimental results on two diverse databases show that our method performs significantly better than general topic representation.

引用

页码：398 / 401

页数：4

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