Eigenface algorithm-based facial expression recognition in conversations - an experimental study

Research output: Contribution to conferencePaper

Abstract

Recognising facial expressions is important in many fields such as computer-human interface. Though different approaches have been widely used in facial expression recognition systems, there are still many problems in practice to achieve the best implementation outcomes. Most systems are tested via the lab-based facial expressions, which may be unnatural. Particularly many systems have problems when they are used for recognising the facial expressions being used during conversation. This paper mainly conducts an experi-mental study on Eigenface algorithm-based facial expression recognition. It primarily aims to investigate the performance of both lab-based facial expressions and facial expressions used during conversation. The experiment also aims to probe the problems arising from the recognition of facial expression in conversations. The study is carried out using both the author’s facial expression as the basis for the lab-based expressions and the facial expression from one elderly person during conversation. The experiment showed a good result in lab-based facial expressions, but there are some issues observed when using the case of facial expressions obtained in conversation. By analysing the experimental results, future research focus has been highlighted as the investigation of how to recognise special emotions such as a wry smile and how to deal with the interferences in the lower part of face when speaking.

Conference

ConferenceThe 9th International Conference on Brain-Inspired Cognitive System​
Abbreviated titleBICS2018
CountryChina
CityXi'an
Period7/07/188/07/18
Internet address

Fingerprint

Facial Expression
Interfaces (computer)
Experiments
Emotions

Keywords

  • facial expression recognition
  • Eigenface algorithm
  • facial expressions in conversations

Cite this

Fei, Z., Yang, E., Li, D., Butler, S., Ijomah, W., & Mackin, N. (2018). Eigenface algorithm-based facial expression recognition in conversations - an experimental study. 1-10. Paper presented at The 9th International Conference on Brain-Inspired Cognitive System​, Xi'an , China.
Fei, Zixiang ; Yang, Erfu ; Li, David ; Butler, Stephen ; Ijomah, Winifred ; Mackin, Neil. / Eigenface algorithm-based facial expression recognition in conversations - an experimental study. Paper presented at The 9th International Conference on Brain-Inspired Cognitive System​, Xi'an , China.10 p.
@conference{eda1031f55b34143b10ede04ca98876c,
title = "Eigenface algorithm-based facial expression recognition in conversations - an experimental study",
abstract = "Recognising facial expressions is important in many fields such as computer-human interface. Though different approaches have been widely used in facial expression recognition systems, there are still many problems in practice to achieve the best implementation outcomes. Most systems are tested via the lab-based facial expressions, which may be unnatural. Particularly many systems have problems when they are used for recognising the facial expressions being used during conversation. This paper mainly conducts an experi-mental study on Eigenface algorithm-based facial expression recognition. It primarily aims to investigate the performance of both lab-based facial expressions and facial expressions used during conversation. The experiment also aims to probe the problems arising from the recognition of facial expression in conversations. The study is carried out using both the author’s facial expression as the basis for the lab-based expressions and the facial expression from one elderly person during conversation. The experiment showed a good result in lab-based facial expressions, but there are some issues observed when using the case of facial expressions obtained in conversation. By analysing the experimental results, future research focus has been highlighted as the investigation of how to recognise special emotions such as a wry smile and how to deal with the interferences in the lower part of face when speaking.",
keywords = "facial expression recognition, Eigenface algorithm, facial expressions in conversations",
author = "Zixiang Fei and Erfu Yang and David Li and Stephen Butler and Winifred Ijomah and Neil Mackin",
year = "2018",
month = "7",
day = "7",
language = "English",
pages = "1--10",
note = "The 9th International Conference on Brain-Inspired Cognitive System​, BICS2018 ; Conference date: 07-07-2018 Through 08-07-2018",
url = "http://bics2018.org/",

}

Fei, Z, Yang, E, Li, D, Butler, S, Ijomah, W & Mackin, N 2018, 'Eigenface algorithm-based facial expression recognition in conversations - an experimental study' Paper presented at The 9th International Conference on Brain-Inspired Cognitive System​, Xi'an , China, 7/07/18 - 8/07/18, pp. 1-10.

Eigenface algorithm-based facial expression recognition in conversations - an experimental study. / Fei, Zixiang; Yang, Erfu; Li, David; Butler, Stephen; Ijomah, Winifred; Mackin, Neil.

2018. 1-10 Paper presented at The 9th International Conference on Brain-Inspired Cognitive System​, Xi'an , China.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Eigenface algorithm-based facial expression recognition in conversations - an experimental study

AU - Fei,Zixiang

AU - Yang,Erfu

AU - Li,David

AU - Butler,Stephen

AU - Ijomah,Winifred

AU - Mackin,Neil

PY - 2018/7/7

Y1 - 2018/7/7

N2 - Recognising facial expressions is important in many fields such as computer-human interface. Though different approaches have been widely used in facial expression recognition systems, there are still many problems in practice to achieve the best implementation outcomes. Most systems are tested via the lab-based facial expressions, which may be unnatural. Particularly many systems have problems when they are used for recognising the facial expressions being used during conversation. This paper mainly conducts an experi-mental study on Eigenface algorithm-based facial expression recognition. It primarily aims to investigate the performance of both lab-based facial expressions and facial expressions used during conversation. The experiment also aims to probe the problems arising from the recognition of facial expression in conversations. The study is carried out using both the author’s facial expression as the basis for the lab-based expressions and the facial expression from one elderly person during conversation. The experiment showed a good result in lab-based facial expressions, but there are some issues observed when using the case of facial expressions obtained in conversation. By analysing the experimental results, future research focus has been highlighted as the investigation of how to recognise special emotions such as a wry smile and how to deal with the interferences in the lower part of face when speaking.

AB - Recognising facial expressions is important in many fields such as computer-human interface. Though different approaches have been widely used in facial expression recognition systems, there are still many problems in practice to achieve the best implementation outcomes. Most systems are tested via the lab-based facial expressions, which may be unnatural. Particularly many systems have problems when they are used for recognising the facial expressions being used during conversation. This paper mainly conducts an experi-mental study on Eigenface algorithm-based facial expression recognition. It primarily aims to investigate the performance of both lab-based facial expressions and facial expressions used during conversation. The experiment also aims to probe the problems arising from the recognition of facial expression in conversations. The study is carried out using both the author’s facial expression as the basis for the lab-based expressions and the facial expression from one elderly person during conversation. The experiment showed a good result in lab-based facial expressions, but there are some issues observed when using the case of facial expressions obtained in conversation. By analysing the experimental results, future research focus has been highlighted as the investigation of how to recognise special emotions such as a wry smile and how to deal with the interferences in the lower part of face when speaking.

KW - facial expression recognition

KW - Eigenface algorithm

KW - facial expressions in conversations

M3 - Paper

SP - 1

EP - 10

ER -

Fei Z, Yang E, Li D, Butler S, Ijomah W, Mackin N. Eigenface algorithm-based facial expression recognition in conversations - an experimental study. 2018. Paper presented at The 9th International Conference on Brain-Inspired Cognitive System​, Xi'an , China.