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

Fingerprint

Feature extraction
Statistics
Image classification
Experiments

All Science Journal Classification (ASJC) codes

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

Cite this

Extraction of combined features from global/local statistics of visual words using relevant operations. / Matsukawa, Tetsu; Kurita, Takio.

In: IEICE Transactions on Information and Systems, Vol. E93-D, No. 10, 01.01.2010, p. 2870-2874.

Research output: Contribution to journalArticle

@article{09df854c20ae4fde90cccc02f0ec428f,
title = "Extraction of combined features from global/local statistics of visual words using relevant operations",
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.",
author = "Tetsu Matsukawa and Takio Kurita",
year = "2010",
month = "1",
day = "1",
doi = "10.1587/transinf.E93.D.2870",
language = "English",
volume = "E93-D",
pages = "2870--2874",
journal = "IEICE Transactions on Information and Systems",
issn = "0916-8532",
publisher = "一般社団法人電子情報通信学会",
number = "10",

}

TY - JOUR

T1 - Extraction of combined features from global/local statistics of visual words using relevant operations

AU - Matsukawa, Tetsu

AU - Kurita, Takio

PY - 2010/1/1

Y1 - 2010/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=77957827908&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77957827908&partnerID=8YFLogxK

U2 - 10.1587/transinf.E93.D.2870

DO - 10.1587/transinf.E93.D.2870

M3 - Article

VL - E93-D

SP - 2870

EP - 2874

JO - IEICE Transactions on Information and Systems

JF - IEICE Transactions on Information and Systems

SN - 0916-8532

IS - 10

ER -