Face detection and facial feature extraction using support vector machines

Dihua Xi, Seong Whan Lee

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


This paper proposes a new fast algorithm for detecting human face and extracting the facial features. For this task, we have developed a flexible coordinate system and several support vector machines. The design of a face model for both detection and extraction is based on multi-resolution wavelet decomposition (MWD). Using a mean face, the MWD and a small number of feature points are applied for rough searching by estimating the modified cross correlation (MCC). More accurate results can be achieved by a serious of support vector machines (SVMs). Experimental results show that the proposed approach is fast and has a high detection rate even in cases when a face is embedded in a complicated background.

Original languageEnglish
Pages (from-to)209-212
Number of pages4
JournalProceedings - International Conference on Pattern Recognition
Issue number4
Publication statusPublished - 2002

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition


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