Fall 2022


We used the TBD Pedestrian Dataset[1] by CMU. It has the following salient features:

  • Multiple static cameras (3 views) with intrinsic and extrinsic matrix provided for each camera.
  • Bird’s eye view scene (matching our target domain)
  • Provides ground human truth trajectory (3D points projected to Z=0 plane)
  • Each trajectory matched with pedestrian ID across all 3 viewpoints.
  • Provides Frame level trajectory coordinates
TBD Pedestrian Dataset setup – provides multi-view time-synchronized video feed with camera matrices
2D labeled trajectories for each pedestrian in all 3 camera views. Pedestrians are matched and given the same ID across all 3 views.


[1] Wang, A., Biswas, A., Admoni, H., & Steinfeld, A. (2022). Towards Rich, Portable, and Large-Scale Pedestrian Data Collection. ArXiv, abs/2203.01974