Fall Detection Dataset for Multiclass Classification

 This dataset was created as part of the DeFall project and shot at the MAGIC (MulticoreWare Academia Global Innovation Centre) Lab. It supports research and development in fall detection using computer vision and machine learning, including 9 distinct classes of activities related to falls and non-fall events. The dataset aims to enhance the robustness of fall detection systems by providing a diverse range of scenarios.