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The importance of considering individual differences in expression for in-vehicle emotion recognition - a machine learning approach

Le Houcq Corbi, Raquel and Ihme, Klas and Drewitz, Uwe and Hörmann, Stefan and Bosch, Esther Johanna (2021) The importance of considering individual differences in expression for in-vehicle emotion recognition - a machine learning approach. ACImobility, 21.-22. Sept. 2021, Braunschweig.

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Abstract

High frustration levels during driving are a critical problem for road safety in manual driving and play an essential role in the user experience in all automation levels. Therefore, the development of frustration-sensitive systems is an important step for building user focused systems that adapt its behavior to the user's needs. In this paper, we propose a fully automated process to detect frustration of users in video recordings from in-vehicle driver monitoring. This work uses a unique dataset containing frustrating driving situations that reflect real-world scenarios, which was collected in a driving simulator study with 50 participants with 6 drives each. Following each drive, the participants gave a post-hoc continuous frustration rating. Previous emotion research focused on finding universal expressions of emotion. However, scientific evidence suggests that each individual has a unique set of individual-specific expressions of frustration. Therefore, this work identifies frustration patters on an individual basis. Facial muscle movements have shown to be a promising indicator for emotion recognition. 19 facial muscle movements were detected with the commercially available software FACET and later used to train a Support Vector Machine and Gradient Boosted Tree. The method shows promising results in automated in-vehicle frustration recognition, which is a primary step towards the development of user experience sensitive driving assistance.

Item URL in elib:https://elib.dlr.de/144412/
Document Type:Conference or Workshop Item (Speech)
Title:The importance of considering individual differences in expression for in-vehicle emotion recognition - a machine learning approach
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Le Houcq Corbi, Raquelraquel.lehoucq (at) gmail.comUNSPECIFIED
Ihme, KlasKlas.Ihme (at) dlr.dehttps://orcid.org/0000-0002-7911-3512
Drewitz, UweUwe.Drewitz (at) dlr.dehttps://orcid.org/0000-0002-6542-9698
Hörmann, Stefans.hoermann (at) tum.deUNSPECIFIED
Bosch, Esther JohannaEsther.Bosch (at) dlr.dehttps://orcid.org/0000-0002-6525-2650
Date:September 2021
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Series Name:Proceedings of the ACIMobility Summit 2021
Status:Published
Keywords:User Focused Systems; User Experience; Facial Expression Recognition; Emotion Recognition; Machine Learning
Event Title:ACImobility
Event Location:Braunschweig
Event Type:national Conference
Event Dates:21.-22. Sept. 2021
Organizer:ACImobility
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Road Transport
DLR - Research area:Transport
DLR - Program:V ST Straßenverkehr
DLR - Research theme (Project):V - NGC KoFiF
Location: Braunschweig
Institutes and Institutions:Institute of Transportation Systems > Information Flow Modelling in Mobility Systems, BS
Deposited By: Bosch, Esther Johanna
Deposited On:12 Oct 2021 10:25
Last Modified:12 Oct 2021 10:25

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