Real-Time Human Action Recognition With Dynamical Frame Processing via Modified ConvLSTM and BERT

Real-Time Human Action Recognition With Dynamical Frame Processing via Modified ConvLSTM and BERT

In this study, a human action recognition approach with dynamical frame processing is proposed to fulfill the need for action recognition in a real-time manner. A novel architecture with a modified convolutional long short-term memory (ModConvLSTM) with pose heatmaps as input features is proposed to...

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Bibliographic Details
Main Authors: Raden Hadapiningsyah Kusumoseniarto, Zhi-Yuan Lin, Shun-Feng Su, Pei-Jun Lee
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Deep learning
human action recognition
convolutional LSTM
BERT
computer vision
Online Access:https://ieeexplore.ieee.org/document/11045380/
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https://ieeexplore.ieee.org/document/11045380/

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