Single Sample Face Recognition Based on Sample Augments and MSD Fusion
To overcome the limitation of traditional face recognition methods for single sample face recognition,a single sample face recognition algorithm based on sample augments and MSD fusion is proposed in this paper.First,according to the facial symmetry theory,some relevant information of possible change could be extract to adapt to the future samples.A combination of the original training sample and its virtual average face,symmetrical face as the training sample set is proposed.Then,the maximum scatter difference algorithm was performed on the new training sample set to get the optimal projection matrix,therefore,the features of the training sample and testing facial images could be obtained by projecting them on the optima projection matrix achieved above.During the recognition stage,the fuzzy decision was used to do the classification.Extensive experiment results on famous ORL and FERET show that the algorithm can improve the recognition rate,and has certain robustness.
face recognition virtual samples maximum scatter difference discriminant analysis single sample per person (SSPP)
XU YAN
School of Information Linyi University Shandong Province 276005,China
国际会议
重庆
英文
352-355
2016-03-20（万方平台首次上网日期，不代表论文的发表时间）