Abstract
This paper proposes a method to perform expression invariant face recognition using dictionary learning approach. The proposed method performs the operation in the following stages: the T-region extraction from the face to get the facial region having minimum variation with expression, determination of the wavelet coefficients of the extracted region, dictionary learning using K-SVD and matching. The experiment has been performed on a database that contains 40 persons with 9 expressions each under different illumination conditions. The recognition performed has shown a good accuracy rate as compared to the mostly used PCA-SVM approach. Our system uses label-consistent K-SVD algorithm for dictionary learning to learn a set of dictionaries that represents 3D information of the face. This method fulfills the purpose of sparse coding and classification.
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Maiti, S., Sangwan, D., Raheja, J.L. (2014). Expression-Invariant 3D Face Recognition Using K-SVD Method. In: Gupta, P., Zaroliagis, C. (eds) Applied Algorithms. ICAA 2014. Lecture Notes in Computer Science, vol 8321. Springer, Cham. https://doi.org/10.1007/978-3-319-04126-1_23
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DOI: https://doi.org/10.1007/978-3-319-04126-1_23
Publisher Name: Springer, Cham
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