Kim, Hyunwoo;
(2024)
Human and Machine Recognition of spontaneous and Dynamic Facial Expressions of emotion.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
Over the last few decades, much research on facial expression recognition has predominantly focused on posed, static facial images, often overlooking the importance of dynamic and spontaneous information. This dissertation addresses these gaps by exploring the roles of dynamic and spontaneous aspects in emotion recognition through comprehensive reviews and empirical studies of both humans and automated systems. In the first set of studies, various expression formats - dynamic, target, and non-target static - are analysed to determine the conditions under which dynamic information significantly enhances recognisability of expressions. Results revealed that dynamic cues play a compensatory role, particularly aiding recognition when static expressions fail to represent target emotions adequately. Subsequently, Chapter 2 reviews the existing databases of spontaneous and dynamic facial expressions, detailing their conceptual, technical, and practical features, thereby providing a comprehensive benchmark for research on encoding and decoding facial expressions. Employing automated facial expression analysis tools, Chapter 3 presents an empirical cross-corpus evaluation of the databases reviewed in Chapter 2. Findings showed that, although recognition rates for spontaneous databases generally remain low, they vary significantly across databases, highlighting the inherent difficulty and variability in recognising spontaneous expressions. Furthermore, this work elucidates the critical roles of featural parameters – prototypicality, ambiguity, and complexity – in accurate emotion recognition. In sum, the findings demonstrate that dynamic properties and spontaneous aspects convey important information that significantly influences the human and machine recognition of facial expressions.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Human and Machine Recognition of spontaneous and Dynamic Facial Expressions of emotion |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2024. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10198986 |
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