research-article

A Customer Emotion Recognition through Facial Expression using POEM descriptor and SVM classifier

Authors:

Moulay Smail Bouzakraoui,

Abdelalim Sadiq,

Nourddine EnneyaAuthors Info & Claims

BDCA'17: Proceedings of the 2nd international Conference on Big Data, Cloud and Applications

Article No.: 80, Pages 1 - 6

https://doi.org/10.1145/3090354.3090436

Published: 29 March 2017 Publication History

Abstract

The main contribution of this paper is the modeling and implementation of an automatic facial expression analysis system for measuring emotional customer that can predict their behavior in the decision-making. The model is based on POEM algorithm to extract face features and detect customer emotions. Then, we classify those emotions by SVM classifier to predict customer satisfaction.

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Cited By

Saurav SSaini RSingh S(2021)Facial Expression Recognition Using Dynamic Local Ternary Patterns With Kernel Extreme Learning Machine ClassifierIEEE Access10.1109/ACCESS.2021.31080299(120844-120868)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3108029
Canedo DNeves A(2019)Facial Expression Recognition Using Computer Vision: A Systematic ReviewApplied Sciences10.3390/app92146789:21(4678)Online publication date: 2-Nov-2019
https://doi.org/10.3390/app9214678
Ferraz CSaito JNeto MNovais RFerraz CViana W(2018)A comprehensive analysis of Local Binary Convolutional Neural Network for fast face recognition in surveillance videoProceedings of the 24th Brazilian Symposium on Multimedia and the Web10.1145/3243082.3267444(265-268)Online publication date: 16-Oct-2018
https://dl.acm.org/doi/10.1145/3243082.3267444

Index Terms

A Customer Emotion Recognition through Facial Expression using POEM descriptor and SVM classifier
1. Applied computing
  1. Arts and humanities
2. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
  2. Machine learning
    1. Learning paradigms
      1. Supervised learning
        Supervised learning by classification
    2. Machine learning approaches
      1. Classification and regression trees

Index terms have been assigned to the content through auto-classification.

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Over the last two decades automatic facial expression recognition has become an active research area. Facial expressions are an important channel of non-verbal communication, and can provide cues to emotions and intentions. This paper introduces a ...

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cover image ACM Other conferences

BDCA'17: Proceedings of the 2nd international Conference on Big Data, Cloud and Applications

March 2017

685 pages

ISBN:9781450348522

DOI:10.1145/3090354

Conference Chairs:
Mohamed Lazaar
ENSA, Tetuan, Morocco
,
Youness Tabii
ENSA, Tetuan, Morocco
,
Mohamed Chrayah
ENSA, Tetuan - Morocco
,
Mohammed Al Achhab
ENSA, Tetuan, Morocco

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Ministère de I'enseignement supérieur: Ministère de I'enseignement supérieur

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 March 2017

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BDCA'17

BDCA'17: 2nd international Conference on Big Data, Cloud and Applications

March 29 - 30, 2017

Tetouan, Morocco

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Cited By

Saurav SSaini RSingh S(2021)Facial Expression Recognition Using Dynamic Local Ternary Patterns With Kernel Extreme Learning Machine ClassifierIEEE Access10.1109/ACCESS.2021.31080299(120844-120868)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3108029
Canedo DNeves A(2019)Facial Expression Recognition Using Computer Vision: A Systematic ReviewApplied Sciences10.3390/app92146789:21(4678)Online publication date: 2-Nov-2019
https://doi.org/10.3390/app9214678
Ferraz CSaito JNeto MNovais RFerraz CViana W(2018)A comprehensive analysis of Local Binary Convolutional Neural Network for fast face recognition in surveillance videoProceedings of the 24th Brazilian Symposium on Multimedia and the Web10.1145/3243082.3267444(265-268)Online publication date: 16-Oct-2018
https://dl.acm.org/doi/10.1145/3243082.3267444

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