Pose-varied Face Recognition Based on Facial Pose Correction and Virtual Samples
Zhai Gao-yue · Jisuanji fangzhen · 2011
Improving the multi-gesture recognition accuracy in the study of face recognition.The recognition rate will decline sharply when there are large variation of face pose,especially when the training samples are small,the identification may be impossible.In order to solve the problem of lack of training samples,firstly this paper transforms the pose-varied face images to frontal face images and the texture information of faces is kept based on sine transform(ST).Secondly,polynomial transform is used to generate virtual samples when only having single training sample.Finally,combining the subspace feature extraction methods with pose-varied face recognition strategy,the simulation is conducted and the recognition rates have increased by 19 percentage points.