論文

査読有り
2009年

FAST ALGORITHM FOR GMM-BASED PATTERN CLASSIFIER

2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS
  • Shogo Muramatsu
  • ,
  • Hidenori Watanabe

開始ページ
633
終了ページ
636
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1109/ICASSP.2009.4959663
出版者・発行元
IEEE

This work proposes a fast decision algorithm in pattern classification based on Gaussian mixture models (GMM). Statistical pattern classification problems often meet a situation that comparison between probabilities is obvious and involve redundant computations. When GMM is adopted for the probability model, the exponential function should be evaluated. This work firstly reduces the exponential computations to simple and rough interval calculations. The exponential function is realized by scaling and multiplication with powers of two so that the decision is efficiently realized. For finer decision, a refinement process is also proposed. In order to verify the significance, experimental results on TI DM6437 EVM board are shown through the application to a skin-color extraction problem. It is verified that the classification was almost completed without any refinement process and the refinement process can proceed the residual decisions.

Web of Science ® 被引用回数 : 1

リンク情報
DOI
https://doi.org/10.1109/ICASSP.2009.4959663
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000268919200159&DestApp=WOS_CPL
URL
http://dblp.uni-trier.de/db/conf/icassp/icassp2009.html#conf/icassp/MuramatsuW09
ID情報
  • DOI : 10.1109/ICASSP.2009.4959663
  • ISSN : 1520-6149
  • Web of Science ID : WOS:000268919200159

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