Pattern averaging technique for facial expression recognition using support vector machines

Pattern averaging technique for facial expression recognition using support vector machines

Автор: N. P. Gopalan, Sivaiah Bellamkonda

Журнал: International Journal of Image, Graphics and Signal Processing @ijigsp

Статья в выпуске: 9 vol.10, 2018 года.

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Facial expression is one of the nonverbal communication methods of identifying an emotional state of a human being. Due to its crucial importance in Human-Robot interaction, facial expression recognition (FER) is in the limelight of recent research activities. Most of the studies consider the whole expression images in their analysis, and it has several has several drawbacks concerning illumination, orientation, texture, zoom level, time and space complexity. In this paper, a novel feature extraction technique called the pattern averaging is studied on whole image data using reduction in the dimension of the image by averaging the neighboring pixels. The study is found to give better results on standard datasets using support vector machine classifier.

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Facial expression recognition, pattern averaging, support vector machine, human-computer interaction

Короткий адрес: https://sciup.org/15015994

IDR: 15015994   |   DOI: 10.5815/ijigsp.2018.09.04

Список литературы Pattern averaging technique for facial expression recognition using support vector machines

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