摘要
在单样本人脸识别中,由于训练样本的数量受限,充分利用样本的信息就显得十分重要;针对这种情况,通过采用旋转和反转原始图像的方法增加样本信息,提出了基于虚拟信息的单样本分块人脸识别方法,充分利用了样本的整体信息和局部信息。实验表明,在对人脸图像进行识别时取得了较好的效果,在一定程度上克服了单样本下姿态对识别效果的强烈影响。
As the number of training samples limited in the face recognition with one training sample per person,it is quite important to make full use of the information of the samples.Aiming at this situation,a method of sub-block face recognition based on virtual information with one training image per person is proposed,which makes the best of the globe and local information of the samples.Compared by the examples,the proposed method attains a better result when recognizes face image.At a certain extent,it can overcomes the intensive influence of pose to the recognition effect.
出处
《计算机工程与应用》
CSCD
北大核心
2009年第19期146-149,共4页
Computer Engineering and Applications
关键词
虚拟样本
特征提取
分块
图像旋转
virtual information
feature extraction
sub-block
image circumgyration
