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

24 Nov 2019  ·  Fan Yang, Feiran Li, Yang Wu, Sakriani Sakti, Satoshi Nakamura ·

3D panoramic multi-person localization and tracking are prominent in many applications, however, conventional methods using LiDAR equipment could be economically expensive and also computationally inefficient due to the processing of point cloud data. In this work, we propose an effective and efficient approach at a low cost. First, we obtain panoramic videos with four normal cameras. Then, we transform human locations from a 2D panoramic image coordinate to a 3D panoramic camera coordinate using camera geometry and human bio-metric property (i.e., height). Finally, we generate 3D tracklets by associating human appearance and 3D trajectory. We verify the effectiveness of our method on three datasets including a new one built by us, in terms of 3D single-view multi-person localization, 3D single-view multi-person tracking, and 3D panoramic multi-person localization and tracking. Our code and dataset are available at \url{}.

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 Ranked #1 on Multi-Object Tracking on MOT15_3D (using extra training data)

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Task Dataset Model Metric Name Metric Value Global Rank Uses Extra
Training Data
Result Benchmark
Multi-Object Tracking MOT15_3D MPLT MOTA 54.2 # 1


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