Facial Emotion Recognition to Examine Human Face Using Hybridization Method

2021 ◽  
pp. 205-212
Author(s):  
A. Sravanthi ◽  
B. Sindhuja ◽  
D. Lakshmi Rohitha
Keyword(s):  
Emotion Recognition ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Human Face ◽  
Hybridization Method

scholarly journals Facial Emotion Recognition using Deep Learning

2019 ◽  
Vol 8 (4) ◽  
pp. 10061-10064
Keyword(s):  
Deep Learning ◽  
Emotion Recognition ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Human Face ◽  
Face Emotion Recognition

Face Emotion Recognition (FER), the human face assumes a significant job in programmed acknowledgment of feelings in the field of recognizing human feelings and the cooperation among humans and PC for some genuine applications. The greater part of the revealed facial feeling acknowledgment frameworks aren't completely viewed as subject free unique highlights thus they are not hearty enough for reality. The feelings are successfully variable happenings that are evoked because of affecting power. In this way, all things considered, applications, recognition of feeling is an extremely testing assignment

Beeinträchtigtes Erkennen emotionaler Gesichtsausdrücke durch psychiatrische Patientinnen bei Alexithymie

2013 ◽  
Vol 61 (1) ◽  
pp. 7-15 ◽  
Author(s):  
Daniel Dittrich ◽  
Gregor Domes ◽  
Susi Loebel ◽  
Christoph Berger ◽  
Carsten Spitzer ◽  
...  
Keyword(s):  
Emotion Recognition ◽  
Emotional Expression ◽  
Depression Scale ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Check List ◽  
Psychosomatische Erkrankungen ◽  
Psychiatrische Patienten ◽  
Symptom Check List ◽  
Tas 20

Die vorliegende Studie untersucht die Hypothese eines mit Alexithymie assoziierten Defizits beim Erkennen emotionaler Gesichtsaudrücke an einer klinischen Population. Darüber hinaus werden Hypothesen zur Bedeutung spezifischer Emotionsqualitäten sowie zu Gender-Unterschieden getestet. 68 ambulante und stationäre psychiatrische Patienten (44 Frauen und 24 Männer) wurden mit der Toronto-Alexithymie-Skala (TAS-20), der Montgomery-Åsberg Depression Scale (MADRS), der Symptom-Check-List (SCL-90-R) und der Emotional Expression Multimorph Task (EEMT) untersucht. Als Stimuli des Gesichtererkennungsparadigmas dienten Gesichtsausdrücke von Basisemotionen nach Ekman und Friesen, die zu Sequenzen mit sich graduell steigernder Ausdrucksstärke angeordnet waren. Mittels multipler Regressionsanalyse untersuchten wir die Assoziation von TAS-20 Punktzahl und facial emotion recognition (FER). Während sich für die Gesamtstichprobe und den männlichen Stichprobenteil kein signifikanter Zusammenhang zwischen TAS-20-Punktzahl und FER zeigte, sahen wir im weiblichen Stichprobenteil durch die TAS-20 Punktzahl eine signifikante Prädiktion der Gesamtfehlerzahl (β = .38, t = 2.055, p < 0.05) und den Fehlern im Erkennen der Emotionen Wut und Ekel (Wut: β = .40, t = 2.240, p < 0.05, Ekel: β = .41, t = 2.214, p < 0.05). Für wütende Gesichter betrug die Varianzaufklärung durch die TAS-20-Punktzahl 13.3 %, für angeekelte Gesichter 19.7 %. Kein Zusammenhang bestand zwischen der Zeit, nach der die Probanden die emotionalen Sequenzen stoppten, um ihre Bewertung abzugeben (Antwortlatenz) und Alexithymie. Die Ergebnisse der Arbeit unterstützen das Vorliegen eines mit Alexithymie assoziierten Defizits im Erkennen emotionaler Gesichtsausdrücke bei weiblchen Probanden in einer heterogenen, klinischen Stichprobe. Dieses Defizit könnte die Schwierigkeiten Hochalexithymer im Bereich sozialer Interaktionen zumindest teilweise begründen und so eine Prädisposition für psychische sowie psychosomatische Erkrankungen erklären.

Music to my ears: Age-related decline in musical and facial emotion recognition.

2017 ◽  
Vol 32 (8) ◽  
pp. 698-709 ◽  
Author(s):  
Ryan Sutcliffe ◽  
Peter G. Rendell ◽  
Julie D. Henry ◽  
Phoebe E. Bailey ◽  
Ted Ruffman
Keyword(s):  
Emotion Recognition ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Age Related

Task characteristics influence facial emotion recognition age-effects: A meta-analytic review.

2020 ◽  
Vol 35 (2) ◽  
pp. 295-315 ◽  
Author(s):  
Grace S. Hayes ◽  
Skye N. McLennan ◽  
Julie D. Henry ◽  
Louise H. Phillips ◽  
Gill Terrett ◽  
...  
Keyword(s):  
Emotion Recognition ◽  
Age Effects ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Task Characteristics ◽  
Analytic Review

Usability of a psychotherapeutic interactive gaming tool used in facial emotion recognition for people with schizophrenia (Preprint)

2019 ◽  
Author(s):  
Ingrid Tortadès ◽  
Roberto Gonzalez ◽  
Francesc Alpiste ◽  
Joaquín Fernandez ◽  
Jordi Torner ◽  
...  
Keyword(s):  
Theory Of Mind ◽  
Emotion Recognition ◽  
Attributional Style ◽  
Pilot Project ◽  
Error Rates ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Interactive Software ◽  
Emotional Recognition ◽  
Attribution Questionnaire

BACKGROUND Emotional Recognition (ER) is one of the areas most affected in people with schizophrenia. However, there are no software tools available for the assessment of ER. The interactive software program ‘Feeling Master’ (a cartoon facial recognition tool) was developed to investigate the deficit in facial emotion recognition (FER) with a sample of patients with schizophrenia in a pilot project framework. OBJECTIVE The aim of the study was to test the usability of ‘Feeling Master’ as a psychotherapeutic interactive gaming tool for the assessment of emotional recognition in people with schizophrenia compared with healthy people, and the relationship between FER, attributional style and theory of mind. METHODS Nineteen individuals with schizophrenia and 17 healthy control (HC) subjects completed the ‘Feeling Master’ including five emotions (happiness, sadness, anger, fear, and surprise). Regarding the group with schizophrenia they were evaluated with the Personal and Situational Attribution Questionnaire (IPSAQ) and the Hinting Task (Theory of Mind) to evaluate social cognition. RESULTS Patients with schizophrenia showed impairments in emotion recognition and they remained slower than the HC in the recognition of each emotion (P<.001). Regarding the impairment in the recognition of each emotion we only found a trend toward significance in error rates on fear discrimination (P=.07). And the correlations between correct response on the ‘Feeling Master’ and the hinting task showed significant values in the correlation of surprise and theory of mind (P=.046). CONCLUSIONS In conclusion, the study puts forward the usability of the ‘Feeling Master’ in FER for people with schizophrenia. These findings lend support to the notion that difficulties in emotion recognition are more prevalent in people with schizophrenia, and that these are associated with impairment in ToM, suggesting the potential utility of the FER in the rehabilitation of people with schizophrenia.

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