Yebda, Thinhinane, Benois-Pineau, Jenny ORCID: 0000-0003-0659-8894, Pech, Marion, Amièva, Hélène and Gurrin, Cathal ORCID: 0000-0003-2903-3968 (2020) Detection of semantic risk situations in lifelog data for improving life of frail people. In: 2020 International Conference on Multimedia Retrieval (ICMR'20), 26-29 June 2020, Dublin, Ireland. ISBN 978-1-4503-7087-5
Abstract
The automatic recognition of risk situations for frail people is an
urgent research topic for the interdisciplinary artificial intelligence
and multimedia community. Risky situations can be recognized
from lifelog data recorded with wearable devices. In this paper, we
present a new approach for the detection of semantic risk situations
for frail people in lifelog data. Concept matching between general
lifelog and risk taxonomies was realized and tuned AlexNet was
deployed for detection of two semantic risks situations such as risk
of domestic accident and risk of fraud with promising results.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Uncontrolled Keywords: | neural network; classification; risk situations detection; CNN networks |
Subjects: | UNSPECIFIED |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Initiatives and Centres > ADAPT |
Published in: | Proceedings of the 2020 International Conference on Multimedia Retrieval. . Association for Computing Machinery (ACM). ISBN 978-1-4503-7087-5 |
Publisher: | Association for Computing Machinery (ACM) |
Official URL: | https://doi.org/10.1145/3372278.3391931 |
Copyright Information: | © 2020 The Authors |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | French national ANRT grant:, AAP 2019 "Digital Health Challenge" grant, ALLOCATION: SSESE1902GA and InflexSys project |
ID Code: | 24629 |
Deposited On: | 17 Jun 2020 12:06 by Cathal Gurrin . Last Modified 15 Dec 2021 15:38 |
Documents
Full text available as:
Preview |
PDF
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
1MB |
Downloads
Downloads
Downloads per month over past year
Archive Staff Only: edit this record