Frontal Face Image Synthesis Based on Pose Estimation
Fang Sanyon · Jisuanji gongcheng · 2015
In order to process the face image in different poses,this paper proposes a frontal face image synthesis method based on pose estimation.The method is based on the idea of statistical modeling to reconstruct the missing face shape and texture.Firstly,3D average model is applied to estimate the pose parameters of the test face image.Compressed sensing theory is used to filter prototype samples and then a more accurate model of deformation is built up.Secondly,the test face image is separately expressed by texture vector and shape vector.The deformation model theory is used to reconstruct front texture and shape.Finally,synthesis texture is produced according to the original texture and reconstructed texture.Experimental result shows that this method can be used to synthesize natural frontal face image from non-frontal face image with effectiveness and higher recognition rate.