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Human Action Recognition through the First-Person Point of view, Case Study Two Basic Task

by Mohammad Almasi, Hamed Fathi, Sayed Adel Ghaeinian, Samaneh Samiee
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 24
Year of Publication: 2019
Authors: Mohammad Almasi, Hamed Fathi, Sayed Adel Ghaeinian, Samaneh Samiee
10.5120/ijca2019919703

Mohammad Almasi, Hamed Fathi, Sayed Adel Ghaeinian, Samaneh Samiee . Human Action Recognition through the First-Person Point of view, Case Study Two Basic Task. International Journal of Computer Applications. 177, 24 ( Dec 2019), 19-23. DOI=10.5120/ijca2019919703

@article{ 10.5120/ijca2019919703,
author = { Mohammad Almasi, Hamed Fathi, Sayed Adel Ghaeinian, Samaneh Samiee },
title = { Human Action Recognition through the First-Person Point of view, Case Study Two Basic Task },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2019 },
volume = { 177 },
number = { 24 },
month = { Dec },
year = { 2019 },
issn = { 0975-8887 },
pages = { 19-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number24/31045-2019919703/ },
doi = { 10.5120/ijca2019919703 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:46:48.341465+05:30
%A Mohammad Almasi
%A Hamed Fathi
%A Sayed Adel Ghaeinian
%A Samaneh Samiee
%T Human Action Recognition through the First-Person Point of view, Case Study Two Basic Task
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 24
%P 19-23
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this study, a human motion dataset is built and developed based on indoors and outdoors actions through a bounded-on-head camera and Xsens for tracking the motions. The key point here to structuring the dataset is utilized to set the sequence of a Deep Neural Network and order an arrangement of frames in the performed task (washing, eating, etc.). As a final point, a 3D modeling of the person suggested at every frame centered with the comparable structure of the first network. More than 120,000 frames constructed the dataset, taken from 7 different people, each one acting out different tasks in diverse indoor and outdoor scenarios. The sequences of every video frame were 3D synchronized and segmented 23 parts.

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Index Terms

Computer Science
Information Sciences

Keywords

Machine learning deep learning Computer vision LSTM Recurrent neural network ResNet motion recognition.

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