Improving the performance of SIFT using bilateral filter and its application to generic object recognition

Tomoaki Yamazaki*, Tetsuya Fujikawa, Jiro Katto

*この研究の対応する著者

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

Feature extraction of images can be applied to image matching, image searching, object recognition, image tracking etc. One of the effective methods to extract features of images is Scale-Invariant Feature Transform (SIFT) [1], In this paper, we indicate problems of SIFT and propose a method to improve its performance by applying Bilateral Filter [2]. In addition, we implement its acceleration by GPGPU (general purpose GPU), apply this method to generic object recognition and perform a comparison experiment. We compare the proposed method with the original method using SIFT and confirm improvement of the identification rate by the proposed method.

本文言語English
ホスト出版物のタイトル2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
ページ945-948
ページ数4
DOI
出版ステータスPublished - 2012 10月 23
イベント2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Kyoto, Japan
継続期間: 2012 3月 252012 3月 30

出版物シリーズ

名前ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN(印刷版)1520-6149

Conference

Conference2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
国/地域Japan
CityKyoto
Period12/3/2512/3/30

ASJC Scopus subject areas

  • ソフトウェア
  • 信号処理
  • 電子工学および電気工学

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