摘要
根据人的认识规律,提出了基于图象集的似然度人脸识别方法。该方法把图象集中的各幅图象的信息矩阵的奇异值向量作为矩阵中的一列而构成的图象集特征矩阵。然后,把测试样本的图象集特征矩阵与图象集库中的训练样本图象集的特征矩阵相比较找出它们的相似程度——图象集的似然度,从而进行人脸图象识别。
This paper puts forward a new approach of face recognition based on the similarity of image sets in accordance with the cognitive law. This approach considers the singular vectors of information matrix of each image in the image set as columns of the characteristic matrix of the image set. Then, itcom—pares the characteristic matrix of the testing samples with that of the training samples in the image sets base, to find out the degree of their resemblance —the similarity of image sets. In this way, the face recognition can be carried out.
出处
《计算机工程》
CAS
CSCD
北大核心
2001年第7期113-114,共2页
Computer Engineering
关键词
最小二乘距离
图象集似然度
人脸识别
图象识别
图象集
Characteristic matrix of image set
Least-squares estimator
Similarity of image Sets