Face detection and tracking in color images using color centroids segmentation

Qieshi Zhang*, Sei Ichiro Kamata, Jun Zhang

*この研究の対応する著者

研究成果: Conference contribution

18 被引用数 (Scopus)

抄録

Human face detection plays an important role in many application areas such as video surveillance, human computer interface, face recognition, face search and face image database management etc. In human face detection applications, face region usually form an inconsequential part of images. Consequently, preliminary segmentation of images into regions that contain "non-face" objects and regions that may contain "face" candidates can greatly accelerate the process of human face detection. Color information based methods take a great attention, because colors have obviously character and robust visual cue for detection. This paper proposed a new method based on RGB color centroids segmentation (CCS) for face detection. This paper include two parts, first part is color image thresholding based on CCS and the second part is face detection based on region growing and facial features structure character combined method. The experimental results show the ideal thresholding result and better than the result of other color space analysis based thresholding methods. Proposed method can conquer the influence of different background conditions, position, scale instance and orientation in images from several photo collections and database; the effect is also better than existing skin color segmentation based methods.

本文言語English
ホスト出版物のタイトル2008 IEEE International Conference on Robotics and Biomimetics, ROBIO 2008
出版社IEEE Computer Society
ページ1008-1013
ページ数6
ISBN(印刷版)9781424426799
DOI
出版ステータスPublished - 2009
イベント2008 IEEE International Conference on Robotics and Biomimetics, ROBIO 2008 - Bangkok, Thailand
継続期間: 2009 2月 212009 2月 26

出版物シリーズ

名前2008 IEEE International Conference on Robotics and Biomimetics, ROBIO 2008

Conference

Conference2008 IEEE International Conference on Robotics and Biomimetics, ROBIO 2008
国/地域Thailand
CityBangkok
Period09/2/2109/2/26

ASJC Scopus subject areas

  • バイオテクノロジー
  • 人工知能
  • コンピュータ ビジョンおよびパターン認識
  • 電子工学および電気工学

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