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IEEE/ICACT20260308 Slide.20        [Big Slide]	Oral Presentation
	In this study, we proposed a CPI-based deep learning framework for early detection of crowd collapse using CCTV video data. By integrating crowd density and interpersonal spacing, the model successfully captured critical transitions leading to crowd collapse. Experimental results from real disaster cases confirmed that CPI increases sharply several seconds before physical collapse, enabling early warning. This approach moves crowd safety analysis from post-event interpretation to proactive, real-time risk prevention.

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