Multilinear principal component analysis for face recognition with fewer features
نویسندگان
چکیده
In this study, a method is proposed based on multilinear principal component analysis (MPCA) for face recognition. This method utilized less features than traditional MPCA algorithm without downgrading the performance in recognition accuracy. The experiment results show that the proposed method is more suitable for large dataset, obtaining better computational efficiency. Moreover, when support vector machine is employed as the classification method, the superiority of the proposed algorithm reflects significantly. & 2010 Elsevier B.V. All rights reserved.
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عنوان ژورنال:
- Neurocomputing
دوره 73 شماره
صفحات -
تاریخ انتشار 2010