Pang Ying Han and Hiew Fu San and Ooi Shih Yin
Face Recognition using a Kernelization of Graph Embedding
209 - 213
2012
6
2
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/13302
https://publications.waset.org/vol/62
World Academy of Science, Engineering and Technology
Linearization of graph embedding has been emerged
as an effective dimensionality reduction technique in pattern
recognition. However, it may not be optimal for nonlinearly
distributed real world data, such as face, due to its linear nature. So, a
kernelization of graph embedding is proposed as a dimensionality
reduction technique in face recognition. In order to further boost the
recognition capability of the proposed technique, the Fishers
criterion is opted in the objective function for better data
discrimination. The proposed technique is able to characterize the
underlying intraclass structure as well as the interclass separability.
Experimental results on FRGC database validate the effectiveness of
the proposed technique as a feature descriptor.
Open Science Index 62, 2012