Developing a Multi-Camera Analysis Methodology for People Counting in Buildings

Abstract: Determining the number and positions of individuals inside a building is critical for effective data management and rescue operations during building disasters. Although recent vision-based methods have been developed for people counting and tracking, they often struggle to process video data from non-overlapping zones. To overcome these challenges, this study proposes a novel multi-camera analysis methodology that integrates a camera network with Re-Identification (Re-ID) models to manage personnel information. Experimental results demonstrate that the system provides precise zone-specific counts and locations of individuals. This approach can significantly improve emergency response by enabling strategic resource allocation and prioritized access.