Natural-Spontaneous Affective-Cognitive dataset for Adult Students

A. Dawood, S. Turner and P. Perepa, "Natural-Spontaneous Affective-Cognitive dataset for Adult Students with and without Asperger Syndrome (AS)," in IEEE Access.
DOI: 10.1109/ACCESS.2019.2921914


Abstract: Any viable algorithm to infer affective states of individuals with autism requires natural and reliable data in real time and in an uncontrolled environment. For this purpose, this study provides a new natural-spontaneous affective-cognitive dataset based on facial expressions, eye gaze, and head movements for adult students with and without Asperger syndrome (AS). The data gathering and collecting in a computer-based learning environment is one of the significant areas, which has attracted researchers’ attention in affective computing applications. Due to the important impact of emotions on students learning outcome and their performance, the dataset included a range of affective-cognitive states which goes beyond basic emotions. This study reports the methodology that was used in data collection and annotation. Description and comparison of other available datasets were summarized, also the study presents the results that were concluded in more details. In addition, some challenges that were inherent to this study.

keywords: {Autism;Head;Visualization;Lighting;Videos;Real-time systems;Data collection;emotional dataset;autism;Asperger Syndrome;spontaneous;natural;facial expressions;affective computing;affective-cognitive states},


To read the paper go to URL: https://ieeexplore.ieee.org/document/8733795


All views and opinions are the author's and do not necessarily reflected those of any organisation they are associated with. Twitter: @scottturneruon

Multitasking in Emotion Modelling Attention Control

A paper has recently been presented at  2015 International Conference on Affective Computing and Intelligent Interaction (ACII), Xi'an, China 21-24 September 2015   on Multitasking in Emotion Modelling: Attention Control. The work forms part of Mohamed Redha Sidoumou's on-going PhD work in Emotion Modelling.

Multitasking in Emotion Modelling Attention Control

Link to paper: 

http://www.infomus.org/Events/proceedings/ACII2015/papers/Main_Conference/M2_Poster/Poster_Teaser_1/ACII2015_submission_83.pdf

Authors
Mohamed Redha Sidoumou, Scott Turner, Phil Picton School of Science and Technology The University of Northampton St George's Avenue, Northampton, NN2 6JD, UK {mohamed.sidoumou, scott.turner, phil.picton}@northampton.ac.uk 

Kamal Bechkoum School of Computing and Technology University of Gloucestershire Park Campus, The Park, Cheltenham, GL50 2RH, UK kbechkoum@glos.ac.uk 

Karima Benatchba Ecole Nationale Supérieure d’Informatique B.P. 68 M, 16270 Oued-Smar, Algiers, Algeria k_benatchba@esi.dz 

Abstract
The work described in this paper is about building a general model capable of simulating human behaviour and emotions using virtual characters. To make the simulation realistic enough, virtual characters need to express emotions according to the environment and deal with those emotions in a parallel way where an emotional experience can be triggered at the same time as another emotional response. The virtual character will have perceptions, feel and express emotions and respond to different situations. To make the simulation realistic, we used a method allowing the virtual characters to execute tasks, perceive events and display emotions in a parallel way. To do that, we used the multiple resources model  to control the attention and to predict when two or more actions can be executed at the same time. The used emotional model is based on Scherer’s theory. However, in this paper we focus on the control of the attention as a part of the emotional process.


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If you'd like to find out more about Computing at the University of Northampton go to: www.computing.northampton.ac.uk. All views and opinions are the author's and do not necessarily reflected those of any organisation they are associated with