Visual Analysis of Emotions Using AI Image-Processing Software: Possible Male/Female Differences between the Emotion Pairs "Neutral" - "Fear" and "Pleasure" - "Pain"

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11240%2F21%3A10438829" target="_blank" >RIV/00216208:11240/21:10438829 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11310/21:10438829

Výsledek na webu

<a href="https://doi.org/10.1145/3453892.3461656" target="_blank" >https://doi.org/10.1145/3453892.3461656</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3453892.3461656" target="_blank" >10.1145/3453892.3461656</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Visual Analysis of Emotions Using AI Image-Processing Software: Possible Male/Female Differences between the Emotion Pairs "Neutral" - "Fear" and "Pleasure" - "Pain"

Popis výsledku v původním jazyce

Inferring the emotional state of an individual by viewing his/her facial expression seems to be present in all human cultures. Numerous studies have shown that various changes in facial muscles determine the resulting facial expression. The analysis of images of faces expressing emotional states promises to contribute to quantification of the claimed observations. Here, we use a suite of AI (artificial intelligence) algorithms, along with ML (maximum likelihood) estimated distributions to quantify the shift in facial expression from &quot;neutral&quot; to &quot;fear&quot; and &quot;pain&quot; to &quot;pleasure&quot;. The images are single frames of five emotional states (neutral, fear, pain, pleasure, laugh) expressed by actors and actresses in BDSM videos. We extract a feature vector for each image, dimension-reduce these feature vectors by mapping them onto a two-dimensional manifold and calculate the norms of the normalized displacement vectors for each emotional pair. We then find that the ML distributions of the norms are Gamma-distributed and that the modes for each pair are different for both males and females. We use Wilks lambda to determine significance. We find that the distributions for the females are significantly different, but not for the males. The methodology we present here has widespread applications: monitoring the emotional states of humans in various settings; among these: determining whether participants in BDSM and similar videos are indeed volunteering their participation or are victims of criminal activity.

Název v anglickém jazyce

Visual Analysis of Emotions Using AI Image-Processing Software: Possible Male/Female Differences between the Emotion Pairs "Neutral" - "Fear" and "Pleasure" - "Pain"

Popis výsledku anglicky

Inferring the emotional state of an individual by viewing his/her facial expression seems to be present in all human cultures. Numerous studies have shown that various changes in facial muscles determine the resulting facial expression. The analysis of images of faces expressing emotional states promises to contribute to quantification of the claimed observations. Here, we use a suite of AI (artificial intelligence) algorithms, along with ML (maximum likelihood) estimated distributions to quantify the shift in facial expression from &quot;neutral&quot; to &quot;fear&quot; and &quot;pain&quot; to &quot;pleasure&quot;. The images are single frames of five emotional states (neutral, fear, pain, pleasure, laugh) expressed by actors and actresses in BDSM videos. We extract a feature vector for each image, dimension-reduce these feature vectors by mapping them onto a two-dimensional manifold and calculate the norms of the normalized displacement vectors for each emotional pair. We then find that the ML distributions of the norms are Gamma-distributed and that the modes for each pair are different for both males and females. We use Wilks lambda to determine significance. We find that the distributions for the females are significantly different, but not for the males. The methodology we present here has widespread applications: monitoring the emotional states of humans in various settings; among these: determining whether participants in BDSM and similar videos are indeed volunteering their participation or are victims of criminal activity.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10602 - Biology (theoretical, mathematical, thermal, cryobiology, biological rhythm), Evolutionary biology

Projekt

<a href="/cs/project/GJ19-12885Y" target="_blank" >GJ19-12885Y: Behaviorální a psycho-fyziologická reakce na prezentaci ambivalentních obrazových a zvukových stimulů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

PETRA 2021: The 14th PErvasive Technologies Related to Assistive Environments Conference

ISBN

978-1-4503-8792-7

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

342-346

Název nakladatele

Association for Computing Machinery

Místo vydání

New York

Místo konání akce

Corfu Greece

Datum konání akce

29. 6. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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