Pixel features series fusion for precise facial components localisation in probabilistic framework

Abstract

A robust and precise scheme for detecting faces and locating the facial components in images at the presence of varying facial contexts as well as complex backgrounds is presented. The system is based on the estimation of the pixel-wised colour distribution of facial components and geometrical information of faces. Probability maps for facial elements are constructed using Gaussian mixture model (GMM) based on the chroma and luma character of facial components. Face candidates are generated based on AdaBoost detection algorithm, and the local skin patch is extracted to generate skin probability map based on GMM. A series of fusion strategy on probability maps is then designed to construct eye, mouth and skin binary maps for verifying each face candidate and locating its facial components, taking facial geometry into consideration. Morphological operators are used for post-processing. Experiments show that more accurate detection results can be obtained as compared to other state-of-the-art methods.

Keywords:

• face detection
• facial components localisation
• Gaussian mixture model
• probability
• fusion
• morphological operation

This work was supported by the Fundamental Research Funds for the Central Universities under grant JUSRP10926. The authors would like to thank the anonymous reviewers for the valuable comments on the earlier version of this manuscript.