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

In this paper, we proposed an implementation of fall detection system on Raspberry Pi with the Intel¯ 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...

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Bibliographic Details
Published in2020 IEEE International Symposium on Circuits and Systems (ISCAS) p. 1
Main Authors Tsai, Tsung-Han, Hsu, Chin-Wei, Wan, Wei-Chung
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2020
Subjects
Cameras
CNN
Embedded systems
Fall detection
Monitoring
neural compute stick2
Neural networks
Raspberry Pi
Real-time systems
Skeleton
Systems architecture
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Summary:In this paper, we proposed an implementation of fall detection system on Raspberry Pi with the Intel¯ 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.
ISBN:9781728133201
1728133203
ISSN:2158-1525
2158-1525
DOI:10.1109/ISCAS45731.2020.9181262