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Automatic Image Collection of Objects with Similar Function by Learning Human Grasping Forms Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Monte Carlo Based Importance Estimation of Localized Feature Descriptors for the Recognition of Facial Expressions

Authors : Markus Kächele, Günther Palm, Friedhelm Schwenker

Published in: Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction

Publisher: Springer International Publishing

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Abstract

The automated and exact identification of facial expressions in human computer interaction scenarios is a challenging but necessary task to recognize human emotions by a machine learning system. The human face consists of regions whose elements contribute to single expressions in a different manner. This work aims to shed light onto the importance of specific facial regions to provide information which can be used to discriminate between different facial expressions from a statistical pattern recognition perspective. A sampling based classification approach is used to reveal informative locations in the face. The results are expression-sensitive importance maps that indicate regions of high discriminative power which can be used for various applications.

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previous chapter Multiple-manifolds Discriminant Analysis for Facial Expression Recognition from Local Patches Set
next chapter Noisy Speech Recognition Based on Combined Audio-Visual Classifiers
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Metadata
Title
Monte Carlo Based Importance Estimation of Localized Feature Descriptors for the Recognition of Facial Expressions
Authors
Markus Kächele
Günther Palm
Friedhelm Schwenker
Copyright Year
2015
Book
Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction

Print ISBN: 978-3-319-14898-4

Electronic ISBN: 978-3-319-14899-1

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-14899-1_4

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