Manifold based methods in facial expression recognition

Kun Xie

doi:10.1117/12.2030812

19 July 2013 Manifold based methods in facial expression recognition

Kun Xie

Proceedings Volume 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013); 887831 (2013) https://doi.org/10.1117/12.2030812
Event: Fifth International Conference on Digital Image Processing, 2013, Beijing, China

Abstract

This paper describes a novel method for facial expression recognition based on non-linear manifold techniques. The graph-based algorithms are designed to treat structure in data, and regularize accordingly. This same goal is shared by several other algorithms, from linear method principal components analysis (PCA) to modern variants such as Laplacian eigenmaps. In this paper we focus on manifold learning for dimensionality reduction and clustering using Laplacian eigenmaps for facial expression recognition. We evaluate the algorithm by using all the pixels and selected features respectively and compare the performance of the proposed non-linear manifold method with the previous linear manifold approach, and the non linear method produces higher recognition rate than the facial expression representation using linear methods.

Citation Download Citation

Kun Xie "Manifold based methods in facial expression recognition", Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 887831 (19 July 2013); https://doi.org/10.1117/12.2030812

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