Face detection based on skin color likelihood

Yuseok Ban, Sang Ki Kim, Sooyeon Kim, Kar Ann Toh, Sangyoun Lee

Research output: Contribution to journalArticlepeer-review

76 Citations (Scopus)


We propose a face detection method based on skin color likelihood via a boosting algorithm which emphasizes skin color information while deemphasizing non-skin color information. A stochastic model is adapted to compute the similarity between a color region and the skin color. Both Haar-like features and Local Binary Pattern (LBP) features are utilized to build a cascaded classifier. The boosted classifier is implemented based on skin color emphasis to localize the face region from a color image. Based on our experiments, the proposed method shows good tolerance to face pose variation and complex background with significant improvements over classical boosting-based classifiers in terms of total error rate performance.

Original languageEnglish
Pages (from-to)1573-1585
Number of pages13
JournalPattern Recognition
Issue number4
Publication statusPublished - 2014 Apr

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) ( NRF-2011-0016302 ).

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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