The identification of facial expressions with human emotions plays a key role in non-verbal human communication and has applications in several areas. In this work, we propose a descriptor based on areas and angles of triangles formed by the landmarks from face images. We test this descriptors for facial expression recognition by means of an adaptation of the k-Nearest Neighbors classifier called Citation-kNN in which the training examples come in the form of sets of feature vectors. Comparisons with other state-of-the-art techniques on the CK+ dataset are shown. The descriptor remains robust and precise in the recognition of expressions.
CITATION STYLE
Acevedo, D., Negri, P., Buemi, M. E., Gómez Fernández, F., & Mejail, M. (2018). A citation k-NN approach for facial expression recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10657 LNCS, pp. 1–9). Springer Verlag. https://doi.org/10.1007/978-3-319-75193-1_1
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