Virtual object for evaluating adaptable K-nearest neighbor method solving various conditions of object recognition

Wittayathawon Kanlaya, Le Dung, Makoto Mizukawa

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

In order for robots to be able to manipulate the proper objects, robots firstly need visual ability to precisely recognize and identify objects. One of the most basic problems with robot vision is that environments can change under various weather conditions (various illuminations). Furthermore, each object's category consists of many objects with various poses. In order to obtain the best performance in term of accuracy and efficiency, we compared three feature extraction approaches that have been widely used to solve this problem: Principal Components Analysis (PCA), Linear Discriminant Analysis (LDA), and contour matching with Log Polar Histogram (LPH). We also introduced an improved algorithm called Adaptable K-Nearest Neighbor (AK-NN) that allows the object recognition system to use an automatic adaptable K value to improve the accuracy of classification. To evaluate the object recognition system, we generated virtual objects with various conditions for realistic testing.

本文言語English
ホスト出版物のタイトルICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
ページ4338-4342
ページ数5
出版ステータスPublished - 2009 12 1
イベントICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009 - Fukuoka, Japan
継続期間: 2009 8 182009 8 21

出版物シリーズ

名前ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings

Conference

ConferenceICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009
国/地域Japan
CityFukuoka
Period09/8/1809/8/21

ASJC Scopus subject areas

  • 情報システム
  • 制御およびシステム工学
  • 産業および生産工学

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