Aimed at the problems of infrared image recognition under varying illumination,face disguise,etc.,we bring out an infrared human face recognition algorithm based on 2DPCA.The proposed algorithm can work out the covari...Aimed at the problems of infrared image recognition under varying illumination,face disguise,etc.,we bring out an infrared human face recognition algorithm based on 2DPCA.The proposed algorithm can work out the covariance matrix of the training sample easily and directly;at the same time,it costs less time to work out the eigenvector.Relevant experiments are carried out,and the result indicates that compared with the traditional recognition algorithm,the proposed recognition method is swift and has a good adaptability to the changes of human face posture.展开更多
In this paper, the authors derive the asymptotic joint distributions of theeigenvalues of some random matrices which arise from components of covariance model.
基金Sponsored by the Natural Science Fund of Heilongjiang province(Grant No. F2007-13)Science and Technology Research Projects in Office of Education of Heilongjiang province(Grant No.11531034)the Heilongjiang Postdoctoral Science Foundation(Grant No.LBH-Z06054)
文摘Aimed at the problems of infrared image recognition under varying illumination,face disguise,etc.,we bring out an infrared human face recognition algorithm based on 2DPCA.The proposed algorithm can work out the covariance matrix of the training sample easily and directly;at the same time,it costs less time to work out the eigenvector.Relevant experiments are carried out,and the result indicates that compared with the traditional recognition algorithm,the proposed recognition method is swift and has a good adaptability to the changes of human face posture.
文摘In this paper, the authors derive the asymptotic joint distributions of theeigenvalues of some random matrices which arise from components of covariance model.
