Face detection based on knowledge and independent component

Quan Xue Gao, Quan Pan, Hong Cai Zhang, Chun Hui Zhao

Research output: Contribution to journalArticlepeer-review

Abstract

In order to improve the speed and robustness of detecting human faces in grayscale scene image, an approach that combines independent component analysis (ICA) with knowledge-based is proposed for face detection. A new detection rule is presented by analyzing face predigest models usually used in painting face. Moreover, in order to further reduce the time of face detection, the hierarchical detection processes and extended projection are used in the process of rough face detection. In addition, adaptive threshold selection is realized by maximizing between-class variance. Experimental results show that the new algorithm is feasible and efficient.

Original languageEnglish
Pages (from-to)2869-2871
Number of pages3
JournalXitong Fangzhen Xuebao / Journal of System Simulation
Volume16
Issue number12
StatePublished - Dec 2004

Keywords

  • Detection rule
  • Extended projection
  • Face detection
  • Hierarchical detection
  • Independent component analysis

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