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Dual viewpoint passenger state classification using 3D CNNs
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Tu, Ian, Bhalerao, Abhir, Griffiths, Nathan, Muñoz Delgado, Mauricio, Thomason, Alasdair, Popham, Thomas and Mouzakitis, Alexandros (2018) Dual viewpoint passenger state classification using 3D CNNs. In: IEEE Intelligent Vehicles Symposium (IV'18) , Chang Shu, China, 26-19 June 2018. Published in: 2018 IEEE Intelligent Vehicles Symposium (IV) doi:10.1109/IVS.2018.8500564 ISSN 1931-0587.
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Official URL: https://doi.org/10.1109/IVS.2018.8500564
Abstract
The rise of intelligent vehicle systems will lead to more human-machine interactions and so there is a need to create a bridge between the system and the actions and behaviours of the people inside the vehicle. In this paper, we propose a dual camera setup to monitor the actions and behaviour of vehicle passengers and a deep learning architecture which can utilise video data to classify a range of actions. The method incorporates two different views as input to a 3D convolutional network and uses transfer learning from other action recognition data. The performance of this method is evaluated using an in-vehicle dataset, which contains video recordings of people performing a range of common in-vehicle actions. We show that the combination of transfer learning and using dual viewpoints in a 3D action recognition network offers an increase in classification accuracy of action classes with distinct poses, e.g. mobile phone use and sleeping, whilst it does not apply as well for classifying those actions with small movements, such as talking and eating.
Item Type: | Conference Item (Paper) | |||||||||
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Subjects: | H Social Sciences > HE Transportation and Communications T Technology > TL Motor vehicles. Aeronautics. Astronautics |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | |||||||||
Library of Congress Subject Headings (LCSH): | Automobile occupants, Automobiles -- Design and construction, Machine learning | |||||||||
Journal or Publication Title: | 2018 IEEE Intelligent Vehicles Symposium (IV) | |||||||||
Publisher: | IEEE | |||||||||
ISSN: | 1931-0587 | |||||||||
Official Date: | 22 October 2018 | |||||||||
Dates: |
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DOI: | 10.1109/IVS.2018.8500564 | |||||||||
Status: | Peer Reviewed | |||||||||
Publication Status: | Published | |||||||||
Access rights to Published version: | Restricted or Subscription Access | |||||||||
Date of first compliant deposit: | 1 May 2018 | |||||||||
Date of first compliant Open Access: | 11 May 2018 | |||||||||
RIOXX Funder/Project Grant: |
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Conference Paper Type: | Paper | |||||||||
Title of Event: | IEEE Intelligent Vehicles Symposium (IV'18) | |||||||||
Type of Event: | Conference | |||||||||
Location of Event: | Chang Shu, China | |||||||||
Date(s) of Event: | 26-19 June 2018 | |||||||||
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