Human action recognition system for elderly and children care using three stream ConvNet

Chang Di Huang, Chien Yao Wang, Jia Ching Wang

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

16 Scopus citations

Abstract

Because of the change of family structure and population ageing, elderly and children care is become a very important issue in modern society. When adults are busy working, they have no time to care elderly and children who standalone in the home. This paper proposes an elderly and children care system to solve this important problem. The proposed intelligent surveillance system is based on action recognition technique of image processing. In this paper, a three stream convolution neural network is proposed for recognize human actions such as fall floor and baby craw. If the system detect abnormal activities are occurred, it will raise alarm and notice family members. In the experiment, there are totally 21 categories activities are collected from HMDB-51 dataset, UCF-101 dataset and Internet. The proposed system achieves 93.42% recognition rate of selected actions.

Original languageEnglish
Title of host publicationProceedings of 2015 International Conference on Orange Technologies, ICOT 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5-9
Number of pages5
ISBN (Electronic)9781467382373
DOIs
StatePublished - 22 Jun 2016
Event3rd International Conference on Orange Technologies, ICOT 2015 - Hong Kong, Hong Kong
Duration: 19 Dec 201522 Dec 2015

Publication series

NameProceedings of 2015 International Conference on Orange Technologies, ICOT 2015

Conference

Conference3rd International Conference on Orange Technologies, ICOT 2015
Country/TerritoryHong Kong
CityHong Kong
Period19/12/1522/12/15

Keywords

  • action recognition
  • convolutional neural network
  • deep learning
  • moving
  • spatial
  • temporal
  • three stream ConvNet

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