Face detection based on skin color likelihood

• We propose a boosting-based face detection method using skin likelihood.
• Our method emphasizes skin color while deemphasizing non-skin color.
• Good tolerance to severe face pose variation is obtained.
• The proposed method shows robustness against complex background.

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.