Real-Time Emotional Analysis

Andreas Savva; Vasso Stylianou

doi:10.1109/ICCECE51049.2023.10084955

Real-Time Emotional Analysis

Andreas Savva, Vasso Stylianou

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper describes the development of a system which captures students' facial expressions during a lecture and by using machine learning methods it produces a timeline of their emotions. Examples of such emotions are: happiness, surprise, fear, neutral and sadness. This can assist an educator to identify aspects for improving a lecture, such as, at which periods of time students were confused, or, in a 3-hour lecture when a break is needed, etc.

Original language	English
Title of host publication	ICCECE 2023 - International Conference on Computer, Electrical and Communication Engineering
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665452519
DOIs	https://doi.org/10.1109/ICCECE51049.2023.10084955
Publication status	Published - 2023
Event	2023 International Conference on Computer, Electrical and Communication Engineering, ICCECE 2023 - Kolkata, India Duration: 20 Jan 2023 → 21 Jan 2023

Publication series

Name	ICCECE 2023 - International Conference on Computer, Electrical and Communication Engineering

Conference

Conference	2023 International Conference on Computer, Electrical and Communication Engineering, ICCECE 2023
Country/Territory	India
City	Kolkata
Period	20/01/23 → 21/01/23

Keywords

Emotion analysis
Facial expressions
Machine learning

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ICCECE51049.2023.10084955

Cite this

@inproceedings{e684e80cafd34ebf8b44d742b358b38a,

title = "Real-Time Emotional Analysis",

abstract = "This paper describes the development of a system which captures students' facial expressions during a lecture and by using machine learning methods it produces a timeline of their emotions. Examples of such emotions are: happiness, surprise, fear, neutral and sadness. This can assist an educator to identify aspects for improving a lecture, such as, at which periods of time students were confused, or, in a 3-hour lecture when a break is needed, etc.",

keywords = "Emotion analysis, Facial expressions, Machine learning",

author = "Andreas Savva and Vasso Stylianou",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 International Conference on Computer, Electrical and Communication Engineering, ICCECE 2023 ; Conference date: 20-01-2023 Through 21-01-2023",

year = "2023",

doi = "10.1109/ICCECE51049.2023.10084955",

language = "English",

series = "ICCECE 2023 - International Conference on Computer, Electrical and Communication Engineering",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "ICCECE 2023 - International Conference on Computer, Electrical and Communication Engineering",

}

Savva, A & Stylianou, V 2023, Real-Time Emotional Analysis. in ICCECE 2023 - International Conference on Computer, Electrical and Communication Engineering. ICCECE 2023 - International Conference on Computer, Electrical and Communication Engineering, Institute of Electrical and Electronics Engineers Inc., 2023 International Conference on Computer, Electrical and Communication Engineering, ICCECE 2023, Kolkata, India, 20/01/23. https://doi.org/10.1109/ICCECE51049.2023.10084955

Real-Time Emotional Analysis. / Savva, Andreas ; Stylianou, Vasso.
ICCECE 2023 - International Conference on Computer, Electrical and Communication Engineering. Institute of Electrical and Electronics Engineers Inc., 2023. (ICCECE 2023 - International Conference on Computer, Electrical and Communication Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Real-Time Emotional Analysis

AU - Savva, Andreas

AU - Stylianou, Vasso

PY - 2023

Y1 - 2023

N2 - This paper describes the development of a system which captures students' facial expressions during a lecture and by using machine learning methods it produces a timeline of their emotions. Examples of such emotions are: happiness, surprise, fear, neutral and sadness. This can assist an educator to identify aspects for improving a lecture, such as, at which periods of time students were confused, or, in a 3-hour lecture when a break is needed, etc.

AB - This paper describes the development of a system which captures students' facial expressions during a lecture and by using machine learning methods it produces a timeline of their emotions. Examples of such emotions are: happiness, surprise, fear, neutral and sadness. This can assist an educator to identify aspects for improving a lecture, such as, at which periods of time students were confused, or, in a 3-hour lecture when a break is needed, etc.

KW - Emotion analysis

KW - Facial expressions

KW - Machine learning

UR - http://www.scopus.com/inward/record.url?scp=85153361710&partnerID=8YFLogxK

U2 - 10.1109/ICCECE51049.2023.10084955

DO - 10.1109/ICCECE51049.2023.10084955

M3 - Conference contribution

AN - SCOPUS:85153361710

T3 - ICCECE 2023 - International Conference on Computer, Electrical and Communication Engineering

BT - ICCECE 2023 - International Conference on Computer, Electrical and Communication Engineering

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 International Conference on Computer, Electrical and Communication Engineering, ICCECE 2023

Y2 - 20 January 2023 through 21 January 2023

ER -

Real-Time Emotional Analysis

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this