Enhanced Fall Detection Using YOLOv7-W6-Pose for Real-Time Elderly Monitoring
This study aims to enhance elderly fall detection systems by using the YOLO (You Only Look Once) object detection algorithm with pose estimation, improving both accuracy and efficiency. Utilizing YOLOv7-W6-Pose’s robust real-time object detection and pose estimation capabilities, the proposed system...
Saved in:
Main Authors: | Eugenia Tîrziu, Ana-Mihaela Vasilevschi, Adriana Alexandru, Eleonora Tudora |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-12-01
|
Series: | Future Internet |
Subjects: | |
Online Access: | https://www.mdpi.com/1999-5903/16/12/472 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A hybrid human fall detection method based on modified YOLOv8s and AlphaPose
by: Lei Liu, et al.
Published: (2025-01-01) -
A Real-Time Human Pose Measurement System for Human-In-The-Loop Dynamic Simulators
by: Nicola Giulietti, et al.
Published: (2025-01-01) -
Factors Associated with Fall Risk in the Elderly
by: Zehra Can Karahan, et al.
Published: (2024-12-01) -
Estimating hip impact velocity and acceleration from video-captured falls using a pose estimation algorithm
by: Reese Michaels, et al.
Published: (2025-01-01) -
Target Detection and Robotic Arm Grasp Pose Estimation Based on YOLOv5 and Transfer Learning
by: Li Wanyan, et al.
Published: (2024-03-01)