Multi Visual Modality Fall Detection Dataset
Falls are one of the leading causes of injury-related deaths among the elderly worldwide. Effective detection of falls can reduce the risk of complications and injuries. Fall detection can be performed using wearable devices or ambient sensors; these methods may struggle with user compliance issues...
Main Authors: | Stefan Denkovski, Shehroz S. Khan, Brandon Malamis, Sae Young Moon, Bing Ye, Alex Mihailidis |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2022-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9910156/ |
Similar Items
-
Visual Fall Detection From Activities of Daily Living for Assistive Living
by: Samyan Qayyum Wahla, et al.
Published: (2023-01-01) -
Privacy-protecting behaviours of risk detection in people with dementia using videos
by: Pratik K. Mishra, et al.
Published: (2023-01-01) -
Intelligent Complementary Multi-Modal Fusion for Anomaly Surveillance and Security System
by: Jae-hyeok Jeong, et al.
Published: (2023-11-01) -
UP-Fall Detection Dataset: A Multimodal Approach
by: Lourdes Martínez-Villaseñor, et al.
Published: (2019-04-01) -
Autoencoder-Based Visual Anomaly Localization for Manufacturing Quality Control
by: Devang Mehta, et al.
Published: (2023-12-01)