State classification with array sensor using support vector machine forwireless monitoring systems

Jihoon Hong, Tomoaki Ohtsuki

研究成果: Article査読

12 被引用数 (Scopus)

抄録

We have previously proposed an indoor monitoring and security system with an array sensor. The array sensor has some advantages, such as low privacy concern, easy installation with low cost, and wide detection range. Our study is different from the previously proposed classification method for array sensor, which uses a threshold to classify only two states for intrusion detection: nothing and something happening. This paper describes a novel state classification method based on array signal processing with a machine learning algorithm. The proposed method uses eigenvector and eigenvalue spanning the signal subspace as features, obtained from the array sensor, and assisted by multiclass support vector machines (SVMs) to classify various states of a human being or an object. The experimental results show that our proposed method can provide high classification accuracy and robustness, which is very useful for monitoring and surveillance applications.

本文言語English
ページ(範囲)3088-3095
ページ数8
ジャーナルIEICE Transactions on Communications
E95-B
10
DOI
出版ステータスPublished - 2012 10月

ASJC Scopus subject areas

  • ソフトウェア
  • コンピュータ ネットワークおよび通信
  • 電子工学および電気工学

フィンガープリント

「State classification with array sensor using support vector machine forwireless monitoring systems」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル