PROBABILISTIC FACIAL COMPONENT FUSION METHOD FOR FACE DESCRIPTION AND RECOGNITION USING SUBSPACE COMPONENT FEATURE

摘要

PROBLEM TO BE SOLVED: To provide a component based method for coding and recognizing a human face effectively and efficiently.;SOLUTION: Facial component features such as eye feature, eyebrow feature, nose feature, mouth feature, outline feature and hair feature are generated by cascade subspace projections, and detailed regional identity information of a specified facial component is described. Detailed regional identity information can be revealed with individual component features. The combination of component features of eyes, eyebrows, nose, mouth and profile has better face description capability, compared with the global face description. The result obtained on each component based on how good the component match is is weighted. The probabilistic facial component fusion method for combining the facial component features of eyes, eyebrows, nose, mouth and profile with adaptivity attention weights corresponding to the significance of identify information of test face can tackle the problems of various expressions, occlusions and appearance changes displayed on each individual face.;COPYRIGHT: (C)2004,JPO&NCIPI