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Extraction of Combined Features from Global/Local Statistics of Visual Words Using Relevant Operations
Tetsu MATSUKAWA Takio KURITA
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2010/10/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
combined feature, bag-of-features, feature selection, image classification,
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This paper presents a combined feature extraction method to improve the performance of bag-of-features image classification. We apply 10 relevant operations to global/local statistics of visual words. Because the pairwise combination of visual words is large, we apply feature selection methods including fisher discriminant criterion and L1-SVM. The effectiveness of the proposed method is confirmed through the experiment.