Live demonstration: Vision-based real-time fall detection system on embedded system

Tsung Han Tsai, Chin Wei Hsu, Wei Chung Wan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publication2020 IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728133201
StatePublished - 2020
Event52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Virtual, Online
Duration: 10 Oct 202021 Oct 2020

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2020-October
ISSN (Print)0271-4310

Conference

Conference52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020
CityVirtual, Online
Period10/10/2021/10/20

Keywords

  • CNN
  • Fall detection
  • Neural compute stick2
  • Raspberry pi

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