Normal form transformation for object recognition based on support vector machines

Shinsuke Sugaya, Einoshin Suzuki

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

This paper proposes Normal Form Transformation (NFT) as a preprocessing of Support Vector Machines (SVMs). Object recognition from images can be regarded as a fundamental technique in discovery science. Aspect-based recognition with SVMs is effective under constrained situations. However, object recognition from rotated, shifted, magnified or reduced images is a difficult task for simple SVMs. In order to circumvent this problem, we propose NFT, which rotates an image based on low-luminance directed vector and shifts, magnifies or reduces the image based on the object’s maximum horizontal distance and maximum vertical distance. We have applied SVMs with NFT to a database of 7200 images concerning 100 different objects. The recognition rates were over 97% in these experiments except for cases of extreme reduction. These results clearly demonstrate the effectiveness of the proposed approach in aspect-based recognition.

本文言語英語
ホスト出版物のタイトルDiscovery Science - 2nd International Conference, DS 1999, Proceedings
編集者Setsuo Arikawa, Koichi Furukawa
出版社Springer Verlag
ページ306-315
ページ数10
ISBN(印刷版)354066713X, 9783540667131
DOI
出版ステータス出版済み - 1 1 1999
外部発表はい
イベント2nd International Conference on Discovery Science, DS 1999 - Tokyo, 日本
継続期間: 12 6 199912 8 1999

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
1721
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

その他

その他2nd International Conference on Discovery Science, DS 1999
Country日本
CityTokyo
Period12/6/9912/8/99

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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