In the past few years, cross-modal distillation has garnered a lot of interest due to the rapid growth of multi-modal data. In this paper, we study stress recognition of the drivers corresponding to the driving situation. Our method enables us to recognize stress from unlabeled videos. We perform cross-modal distillation based on wearable physiological sensors and videos from on-board cameras. In this cross-modal distillation, knowledge is transferred from sensor to vision modality.

Drivers stress identification in real-world driving tasks

Bano S;Gotta A
2022

Abstract

In the past few years, cross-modal distillation has garnered a lot of interest due to the rapid growth of multi-modal data. In this paper, we study stress recognition of the drivers corresponding to the driving situation. Our method enables us to recognize stress from unlabeled videos. We perform cross-modal distillation based on wearable physiological sensors and videos from on-board cameras. In this cross-modal distillation, knowledge is transferred from sensor to vision modality.
2022
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
9781665416474
Cross-modal transfer
Deep Learning
Stress detection
File in questo prodotto:
File Dimensione Formato  
prod_471816-doc_191771.pdf

accesso aperto

Descrizione: Postprint - Drivers stress identification in real-world driving tasks
Tipologia: Versione Editoriale (PDF)
Dimensione 200.38 kB
Formato Adobe PDF
200.38 kB Adobe PDF Visualizza/Apri
prod_471816-doc_191835.pdf

solo utenti autorizzati

Descrizione: Drivers stress identification in real-world driving tasks
Tipologia: Versione Editoriale (PDF)
Dimensione 907.83 kB
Formato Adobe PDF
907.83 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/417673
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact