JOURNAL ARTICLE

Live Demonstration: Vision-Based Real-Time Fall Detection System on Embedded System

Abstract

In this paper, we proposed an implementation of fall detection system on Raspberry Pi with the Intel̅ Neural Compute Stick 2. Firstly, we used skeleton extraction algorithm to obtain the important skeleton information. Secondly, we proposed a robustness neural network using pruning method to reduce the parameter and calculation and combined with the neural compute stick to execute the module. The final result will transfer to the Raspberry Pi to display on the monitor. As a result, it can be implemented on the smaller embedded system.

Keywords:
Computer science Robustness (evolution) Artificial neural network Raspberry pi Pruning Artificial intelligence Computer vision Artificial vision Machine vision Real-time computing Embedded system Internet of Things

Metrics

4
Cited By
0.21
FWCI (Field Weighted Citation Impact)
1
Refs
0.50
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Digital Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
Hand Gesture Recognition Systems
Physical Sciences →  Computer Science →  Human-Computer Interaction
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