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Erschienen in:
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2018 | OriginalPaper | Buchkapitel

Facial Expression Classification Using Machine Learning Approach: A Review

verfasst von : A. Baskar, T. Gireesh Kumar

Erschienen in: Data Engineering and Intelligent Computing

Verlag: Springer Singapore

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Abstract

Automatic Facial Expression analysis has enthralled increasing attention in the research community in excess of two decades and its expedient in many application like, face animation, customer satisfaction studies, human-computer interaction and video conferencing. The precisely classifying different emotion is an essential problem in facial expression recognition research. There are several machine learning algorithms applied to facial expression recognition expedition. In this paper, we surveyed three different machine learning algorithms such as Bayesian Network, Hidden Markov Model and Support Vector machine and we attempt to answer following questions: How classification algorithm used its characteristics for emotion recognition? How various parameters in learning algorithm is devoted for better classification? What are the robust features used for training? Finally, we examined how advances in machine learning technique used for facial expression recognition?

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Vorheriges Kapitel Frequent SubGraph Mining Algorithms: Framework, Classification, Analysis, Comparisons
Nächstes Kapitel Heuristic Approach for Nonlinear n × n (3 ≤ n ≤ 7) Substitution-Boxes
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Metadaten
Titel
Facial Expression Classification Using Machine Learning Approach: A Review
verfasst von
A. Baskar
T. Gireesh Kumar
Copyright-Jahr
2018
Verlag
Springer Singapore
Buch
Data Engineering and Intelligent Computing

Print ISBN: 978-981-10-3222-6

Electronic ISBN: 978-981-10-3223-3

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-981-10-3223-3_32