This algorithm was tested on the LFD fall detection dataset, achieving accuracy, precision, recall, and F1 scores of 98.6%, 98.45%, 98.86%, and 98.65%, respectively. Compared to other excellent fall detection methods, this algorithm has a higher recall rate and a better recognition rate for detecting fall behavior.
Mar 22, 2024
A vision-based approach toward the care and rehabilitation of the elderly by examining the important body symmetry features in falls and activities of daily ...
Nov 1, 2024 · This study proposes a high-resolution spatio-temporal feature extraction method based on a spatio-temporal coordinate attention mechanism.
Yang et al. (2024) introduce a method for fall detection that relies on spatio-temporal features to accurately identify falling incidents by leveraging the ...
The method employs 3D convolutions to extract spatio-temporal features and utilizes gradual down-sampling to generate a multi-resolution sub-network, thus ...
Missing: SMA- | Show results with:SMA-
SMA-GCN: a fall detection method based on spatio-temporal relationship ... Based on this, fall detection for the elderly has received wide attention.… 0.
Sep 10, 2021 · SMA-GCN: a fall detection method based on spatio-temporal relationship. 2024, Multimedia Systems. Future Frame Prediction Network for Human ...
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Finally, the spatiotemporal graph convolution (ST-GCN) is applied to detect and recognize actions such as falls, which meets the effective fall in different ...
Dec 19, 2024 · 2024. SMA-GCN: a fall detection method based on spatio-temporal relationship. Multimedia Systems, 30(2): 90.
This work proposes a detection method that uses a weakly supervised learning-based dual-modal network.
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