research-article

Facial Expression Recognition of Animated Human Characters

Authors:

Jae Ho KimAuthors Info & Claims

ICMLC '20: Proceedings of the 2020 12th International Conference on Machine Learning and Computing

Pages 313 - 317

https://doi.org/10.1145/3383972.3384026

Published: 26 May 2020 Publication History

Abstract

Recognition of animated facial expression is an important and a fundamental task for automatically implementing analysis and evaluation of animation movie products. In this work, an improved algorithm was proposed for recognizing facial expression of animated human characters based on the Local Binary Pattern (LBP) and Support Vector Machine (SVM). The proposed method was tested on an animated facial expression database which contained human characters from top rated animations. The experimental results showed that the recognition accuracy of facial expression was significantly improved compared with other methods.

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Cited By

Ghosh ARab RRahman A(2022)Transfer learning based Facial Emotion Detection for Animated Characters2022 25th International Conference on Computer and Information Technology (ICCIT)10.1109/ICCIT57492.2022.10054823(876-881)Online publication date: 17-Dec-2022
https://doi.org/10.1109/ICCIT57492.2022.10054823

Index Terms

Facial Expression Recognition of Animated Human Characters
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object recognition
      2. Computer vision representations
        Appearance and texture representations
  2. Machine learning
    1. Machine learning approaches
      1. Kernel methods
        Support vector machines

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ICMLC '20: Proceedings of the 2020 12th International Conference on Machine Learning and Computing

February 2020

607 pages

ISBN:9781450376426

DOI:10.1145/3383972

Copyright © 2020 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 the author(s) 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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Shenzhen University: Shenzhen University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 May 2020

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ICMLC 2020

ICMLC 2020: 2020 12th International Conference on Machine Learning and Computing

February 15 - 17, 2020

Shenzhen, China

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Cited By

Ghosh ARab RRahman A(2022)Transfer learning based Facial Emotion Detection for Animated Characters2022 25th International Conference on Computer and Information Technology (ICCIT)10.1109/ICCIT57492.2022.10054823(876-881)Online publication date: 17-Dec-2022
https://doi.org/10.1109/ICCIT57492.2022.10054823

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