A genuine smile is indeed in the eyes – The computer aided non-invasive analysis of the exact weight distribution of human smiles across the face

Ugail, Hassan; Aldahoud, Ahmad Ali Asad

doi:10.1016/j.aei.2019.100967

Cited by 8 publications

(2 citation statements)

References 19 publications

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“…In addition, joy can very well detected through the smiling mouth, but especially the “smiling” eyes. Years of psychological (e.g., Ekman et al, 1998 ) and lately engineering research on pattern recognition (e.g., Ugail and Al-dahoud, 2019 ) have shown that the more reliable indicators of a genuine happy facial expression are indeed the eyes. Angry facial expressions are associated with a strong activation of the corrugator supercilii (i.e., the muscle involved in frowning), whereas happy facial expressions are associated with a strong activation of the zygomaticus major, (the muscle involved in smiling) ( Rymarczyk et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

The Recognition of Facial Expressions Under Surgical Masks: The Primacy of Anger

Proverbio

Cerri

2022

Front. Neurosci.

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BackgroundThe need to wear surgical masks in everyday life has drawn the attention of psychologists to the negative effects of face covering on social processing. A recent but not homogeneous literature has highlighted large costs in the ability to recognize emotions.MethodsHere it was investigated how mask covering impaired the recognition of facial mimicry in a large group of 220 undergraduate students. Sex differences in emotion recognition were also analyzed in two subgroups of 94 age-matched participants. Subjects were presented with 112 pictures displaying the faces of eight actors (4 women and 4 men) wearing or not wearing real facemasks, and expressing seven emotional states (neutrality, surprise, happiness, sadness, disgust, anger and fear). The task consisted in categorizing facial expressions while indicating the emotion recognizability with a 3-point Likert scale. Scores underwent repeated measures ANOVAs.ResultsOverall, face masking reduced emotion recognition by 31%. All emotions were affected by mask covering except for anger. Face covering was most detrimental to sadness and disgust, both relying on mouth and nose expressiveness. Women showed a better performance for subtle expressions such as surprise and sadness, both in masked and natural conditions, and men for fear recognition (in natural but especially masked conditions).ConclusionAnger display was unaffected by masking, also because corrugated forehead and frowning eyebrows were clearly exposed. Overall, facial masking seems to polarize non-verbal communication toward the happiness/anger dimension, while minimizing emotions that stimulate an empathic response in the observer.

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Section: Introductionmentioning

confidence: 99%

The Recognition of Facial Expressions Under Surgical Masks: The Primacy of Anger

Proverbio

Cerri

2022

Front. Neurosci.

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“…The results of this can be remarkable performance given particular tasks (e.g. interpreting brain scans [13], identifying fake smiles [53], devising video game strategies [6]). The data a given AI uses is pivotal to how the AI works and how well it functions.…”

Section: The Definitional Dualism Of Aimentioning

confidence: 99%

Researching AI Legibility through Design

Lindley

Akmal

Pilling

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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Everyday interactions with computers are increasingly likely to involve elements of Artificial Intelligence (AI). Encompassing a broad spectrum of technologies and applications, AI poses many challenges for HCI and design. One such challenge is the need to make AI's role in a given system legible to the user in a meaningful way. In this paper we employ a Research through Design (RtD) approach to explore how this might be achieved. Building on contemporary concerns and a thorough exploration of related research, our RtD process reflects on designing imagery intended to help increase AI legibility for users. The paper makes three contributions. First, we thoroughly explore prior research in order to critically unpack the AI legibility problem space. Second, we respond with design proposals whose aim is to enhance the legibility, to users, of systems using AI. Third, we explore the role of design-led enquiry as a tool for critically exploring the intersection between HCI and AI research.

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Real and fake emotion detection using enhanced boosted support vector machine algorithm

Annadurai

Arock

Vadivel

2022

Multimed Tools Appl

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A genuine smile is indeed in the eyes – The computer aided non-invasive analysis of the exact weight distribution of human smiles across the face

Cited by 8 publications

References 19 publications

The Recognition of Facial Expressions Under Surgical Masks: The Primacy of Anger

The Recognition of Facial Expressions Under Surgical Masks: The Primacy of Anger

Researching AI Legibility through Design

Real and fake emotion detection using enhanced boosted support vector machine algorithm

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