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3D panoramic multi-person localization and tracking are prominent in manyapplications, however, conventional methods using LiDAR equipment could beeconomically expensive and also computationally inefficient due to theprocessing of point cloud data. In this work, we propose an effective andefficient approach at a low cost. First, we obtain panoramic videos with fournormal cameras. Then, we transform human locations from a 2D panoramic imagecoordinate to a 3D panoramic camera coordinate using camera geometry and humanbio-metric property (i.e., height). Finally, we generate 3D tracklets byassociating human appearance and 3D trajectory. We verify the effectiveness ofour method on three datasets including a new one built by us, in terms of 3Dsingle-view multi-person localization, 3D single-view multi-person tracking,and 3D panoramic multi-person localization and tracking. Our code and datasetare available at \url{https://github.com/fandulu/MPLT}.

Using Panoramic Videos for Multi-person Localization and Tracking in a 3D Panoramic Coordinate