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XUE-QIAO WANG AND QIU-QI RUAN
Institute of Information Science
Beijing Jiaotong University
Beijing, 100044 P.R. China
A novel Patched Locality Preserving Projections for 3D face recognition was presented
in this paper. In this paper, we firstly patched each image to get the spatial information,
and then Gabor filter was used extract intrinsic discriminative information embedded
in each patch. Finally Locality Preserving Projections, which was improved by
Principle Components Analysis, was utilized to the corresponding patches to obtain locality
preserving information. The feature was constructed by connecting all these projections.
Recognition was achieved by using a Nearest Neighbor classifier finally. The
novelty of this paper came from: (1) The method was robust to changes in facial expressions
and poses, because Gabor filters promoted their useful properties, such as invariance
to rotation, scale and translations, in feature extraction; (2) The method not only
preserved spatial information, but also preserved locality information of the corresponding
patches. Experiments demonstrated the efficiency and effectiveness of the new
method. The experimental results showed that the new algorithm outperformed the other
popular approaches reported in the literature and achieved a much higher accurate recognition
rate.
Received October 19, 2009; revised January 8, 2010; accepted March 5, 2010.
Communicated by Tyng-Luh Liu.
* This work was also partially supported by the National Natural Science Foundation of China under Grant No.
60973060 and the Doctorial Foundation of Ministry of Education of China under Grant No. 200800040008.