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Hesitant-Intuitionistic Trapezoidal Fuzzy Prioritized Operators Based on Einstein Operations with Their Application to Multi-criteria Group Decision-Making Read chapter Read first chapter

2020 | OriginalPaper | Chapter

Tracking Changing Human Emotions from Facial Image Sequence by Landmark Triangulation: An Incircle-Circumcircle Duo Approach

Authors : Md Nasir, Paramartha Dutta, Avishek Nandi

Published in: Algorithms in Machine Learning Paradigms

Publisher: Springer Singapore

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Abstract

Intelligent recognition of human emotions from face images is a challenging proposition in the field of affective computing which becomes even more difficult when one has to deal with characterizing the nature of transition of human emotion from a relevant sequence of face images. In the present scope, we considered a triangulation mechanism derived from the landmark points of the face images. Resulting in a number of triangle formulations which are found to be sensitive to different emotions like anger, disgust, fear, happiness, sadness, and surprise. Accordingly a pair of circles, viz, incircle and circumcircle corresponding to these triangles are taken into account and geometric features arising out of such pair are utilized for classification of different emotional transitions from various face image sequences. Results of the proposed method obtained by application on various benchmark image databases are found to be quite impressive and encouraging compared to existing state-of-the-art technique.

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previous chapter A Linear Regression-Based Resource Utilization Prediction Policy for Live Migration in Cloud Computing
next chapter Recognizing Human Emotions from Facial Images by Landmark Triangulation: A Combined Circumcenter-Incenter-Centroid Trio Feature-Based Method
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Metadata
Title
Tracking Changing Human Emotions from Facial Image Sequence by Landmark Triangulation: An Incircle-Circumcircle Duo Approach
Authors
Md Nasir
Paramartha Dutta
Avishek Nandi
Copyright Year
2020
Publisher
Springer Singapore
Book
Algorithms in Machine Learning Paradigms

Print ISBN: 978-981-15-1040-3

Electronic ISBN: 978-981-15-1041-0

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-15-1041-0_8

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