Journal of Robotics, Networking and Artificial Life

Volume 2, Issue 2, September 2015, Pages 79 - 84

Facial Expression Recognition Using Thermal Image Processing and Efficient Preparation of Training-data

Authors
Yuu Nakanishi, Yasunari Yoshitomi, Taro Asada, Masayoshi Tabuse
Corresponding Author
Yuu Nakanishi
Available Online 1 September 2015.
DOI
https://doi.org/10.2991/jrnal.2015.2.2.3How to use a DOI?
Keywords
Efficient gathering of training data, Facial expression recognition, Thermal image processing, Speech recognition, Vowel judgment
Abstract

Using our previously developed system, we investigated the influence of training data on the facial expression accuracy using the training data of “taro” for the intentional facial expressions of “angry,” “sad,” and “surprised,” and the training data of respective pronunciation for the intentional facial expressions of “happy” and “neutral.” Using the proposed method, the facial expressions were discriminable with average accuracy of 72.4% for “taro,” “koji” and “tsubasa”, for the three facial expressions of “happy,” “neutral,” and “other”.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
2 - 2
Pages
79 - 84
Publication Date
2015/09/01
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
https://doi.org/10.2991/jrnal.2015.2.2.3How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Yuu Nakanishi
AU  - Yasunari Yoshitomi
AU  - Taro Asada
AU  - Masayoshi Tabuse
PY  - 2015
DA  - 2015/09/01
TI  - Facial Expression Recognition Using Thermal Image Processing and Efficient Preparation of Training-data
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 79
EP  - 84
VL  - 2
IS  - 2
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2015.2.2.3
DO  - https://doi.org/10.2991/jrnal.2015.2.2.3
ID  - Nakanishi2015
ER  -