There is an increasing scientific interest in automatically analysing and understanding human behavior, with particular reference to the evolution of facial expressions and the recognition of the corresponding emotions. In this project we propose a technique based on Functional ANOVA to extract significant patterns of face muscles movements, in order to identify the emotions expressed by actors in recorded videos. This research is part of the BIGMATH project, a European Industrial Doctorate funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No 812912.

Functional statistics for human emotion detection / R. Ji, A. Micheletti, N. Krklec Jerinkic, Z. Desnica. - In: ANNUAL REPORT. - ISSN 2616-7867. - 2020:(2020 Apr 02), pp. 26-30.

Functional statistics for human emotion detection

R. Ji
Co-primo
;
A. Micheletti
Co-primo
;
2020

Abstract

There is an increasing scientific interest in automatically analysing and understanding human behavior, with particular reference to the evolution of facial expressions and the recognition of the corresponding emotions. In this project we propose a technique based on Functional ANOVA to extract significant patterns of face muscles movements, in order to identify the emotions expressed by actors in recorded videos. This research is part of the BIGMATH project, a European Industrial Doctorate funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No 812912.
Settore MAT/06 - Probabilita' e Statistica Matematica
Settore SECS-S/01 - Statistica
   Big Data Challenges for Mathematics (BIGMATH)
   BIGMATH
   EUROPEAN COMMISSION
   H2020
   812912
2-apr-2020
2021
https://ecmiindmath.org/annual-report/
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/886169
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