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Real-time human action recognition using raw depth video-based recurrent neural networks

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Main Authors: Adrián, Sánchez-Caballero, David, Fuentes-Jiménez, Cristina, Losada-Gutiérrez
Format: Book
Language:English
Published: Springer 2023
Subjects:
ConvLSTM
HAR
Online Access:https://link.springer.com/article/10.1007/s11042-022-14075-5
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8310
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spelling oai:localhost:PNK-83102023-04-26T02:35:16Z Real-time human action recognition using raw depth video-based recurrent neural networks Adrián, Sánchez-Caballero David, Fuentes-Jiménez Cristina, Losada-Gutiérrez ConvLSTM HAR CC BY This work proposes and compare two different approaches for real-time human action recognition (HAR) from raw depth video sequences. Both proposals are based on the convolutional long short-term memory unit, namely ConvLSTM, with differences in the architecture and the long-term learning. The former uses a video-length adaptive input data generator (stateless) whereas the latter explores the stateful ability of general recurrent neural networks but is applied in the particular case of HAR. This stateful property allows the model to accumulate discriminative patterns from previous frames without compromising computer memory. Furthermore, since the proposal uses only depth information, HAR is carried out preserving the privacy of people in the scene, since their identities can not be recognized. Both neural networks have been trained and tested using the large-scale NTU RGB+D dataset. 2023-04-26T02:35:16Z 2023-04-26T02:35:16Z 2022 Book https://link.springer.com/article/10.1007/s11042-022-14075-5 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8310 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic ConvLSTM
HAR
spellingShingle ConvLSTM
HAR
Adrián, Sánchez-Caballero
David, Fuentes-Jiménez
Cristina, Losada-Gutiérrez
Real-time human action recognition using raw depth video-based recurrent neural networks
description CC BY
format Book
author Adrián, Sánchez-Caballero
David, Fuentes-Jiménez
Cristina, Losada-Gutiérrez
author_facet Adrián, Sánchez-Caballero
David, Fuentes-Jiménez
Cristina, Losada-Gutiérrez
author_sort Adrián, Sánchez-Caballero
title Real-time human action recognition using raw depth video-based recurrent neural networks
title_short Real-time human action recognition using raw depth video-based recurrent neural networks
title_full Real-time human action recognition using raw depth video-based recurrent neural networks
title_fullStr Real-time human action recognition using raw depth video-based recurrent neural networks
title_full_unstemmed Real-time human action recognition using raw depth video-based recurrent neural networks
title_sort real-time human action recognition using raw depth video-based recurrent neural networks
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s11042-022-14075-5
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8310
_version_ 1764268033301282816
score 8.889492

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