摘要
提出了一种新的基于隐马尔可夫模型的人脸识别方法 .这种方法采用奇异值分解抽取人脸图像特征作为观察序列 ,减少了数据的存储量和计算量 ,并提高了识别率 .实验结果同其它两种基于隐马尔可夫模型的方法进行了比较 .
A new approach based on Hidden Markov Model (HMM) face recognition is presented. Singular value decomposition is used to subtract the character of the face image. As a result, the amount of data storage and the computing time is reduced, and the recognition rate is increased. Experimental results are compared with other two HMM based methods.
出处
《计算机学报》
EI
CSCD
北大核心
2003年第3期340-344,共5页
Chinese Journal of Computers