A set of multiple images for a person provides much richer appearance information than a single image.Extracting the common information of multiple images can improve face recognition performance.The classic principal angle-based approach MSM does not work well while appling in single test image matching with image set case.A new approach based on the criterion of minimum reconstruction error from the principal components of test images is proposed.Some experiments are implemented on testing face image sets extracted from MBGC data set,and the experimental results show that the proposed approach possesses significant performance upgrade and is superior to the single image-based and principal angle-based approaches.%同一对象的多张图像提供了比单张图像更丰富的外观信息,提取多张人脸图像共性信息可提高人脸识别率.经典的基于主方向夹角的MSM应用于单张图像对一组图像匹配,识别效果不佳,为此提出基于主分量重构误差最小准则的单张图像与一组注册图像人脸识别算法原理,并作了实施.在由MBGC项目提供的图像组建的测试集上进行的测试表明,所提出的算法识别效果提高幅度明显优于基于依次单张匹配和基于最大主方向夹角准则的方法.
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