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Neural Information ProcessingA Privacy-Friendly Dataset for Automated Passenger Counting in Public Transport

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Berlin-APC

A Privacy-Friendly Dataset for Automated Passenger Counting in Public Transport

Berlin-APC consists of 12,956 sequences with a shape of t x 20 x 25, where t denotes each sequence's variable number of frames. Note that only 3D LiDAR (but no RGB) information is captured, resulting in one channel per pixel. This mode of recording does not allow the identification of individual passengers  but preserves enough information to give an accurate algorithmic passenger count. The video sequences were recorded in 2017 by 3D LiDAR cameras mounted above the doors of a regional train under regular operation in the Berlin metropolitan area. Every sequence is annotated by the number of boarding and alighting passengers (excluding children) as a label.

The dataset can be found here.

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