关键词: 人脸识别, 姿态校正, 正弦变换, 虚拟样本

Abstract: Pose variation is one of the crucial factors and also is a difficult issue that stands in the way of a complete solution to the face recognition problem.The recognition rate will decrease drastically when the probe samples change.This paper proposes a strategy to make pose corrections to the probe samples before recognition，by using Sine Transform（ST） to generate virtual frontal faces，classical algorithms to extract features and the nearest neighbor classifier to classify and recognize.The experiment results on FERET face database demonstrate that the recognition rates increase significantly by adding pose correction，and the best recognition rate has improved by 17%.

Key words: face recognition, pose correction, sine transform, virtual samples