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Soft Computing

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01-07-2014 | Methodologies and Application

An approach to facial expression recognition integrating radial basis function kernel and multidimensional scaling analysis

Authors: Shaowei Wang, Zhizheng Zhuo, Hongyu Yang, Haiyun Li

Published in: Soft Computing | Issue 7/2014

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Abstract

To better deal with high dimensions and extract the essential feature of facial expression images in facial expression recognition task, a novel approach integrating radial basis function kernel and multidimensional scaling analysis is proposed in this paper. Firstly, the radial basis function kernel is invoked to map facial expression images to the Hilbert space. Then, Hilbert distance is substituted for the Euclidean distance and a neighbor graph is constructed to express the relationship between data points by employing k nearest neighbor method. Finally, we apply the modified MDS algorithm to reduce the dimension and extract features of facial expression images. Experiments results on the JAFFE database show that this proposed algorithm performs better than Isomap algorithm and supervised Isomap algorithm, and it is more feasible and effective.

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Title: An approach to facial expression recognition integrating radial basis function kernel and multidimensional scaling analysis
Authors: Shaowei Wang
Zhizheng Zhuo
Hongyu Yang
Haiyun Li
Publication date: 01-07-2014
Publisher: Springer Berlin Heidelberg
Published in: Soft Computing / Issue 7/2014
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-013-1149-9

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