Computer Vision Based Transfer Learning-Aided Transformer Model for Fall Detection and Prediction
Sheldon McCall,
Shina Samuel Kolawole,
Afreen Naz
et al.
Abstract:Falls bring about significant risks to individuals' well-being and independence, prompting widespread public health concerns. Swift detection and even predicting the risk of falls are crucial for implementing effective measures to alleviate the adverse consequences associated with such incidents. This study presents a new framework for identifying and forecasting fall risks. Our approach utilizes a novel transformer model trained on 2D poses extracted through an off-the-shelf pose extractor, incorporating tran… Show more
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