Extraction of combined features from global/local statistics of visual words using relevant operations

Tetsu Matsukawa, Takio Kurita

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Pages (from-to)2870-2874
Number of pages5
JournalIEICE Transactions on Information and Systems
VolumeE93-D
Issue number10
DOIs
Publication statusPublished - Jan 1 2010
Externally publishedYes

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All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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