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Datasets

Over the past years, I have collected data to detect, track, and predict human social dynamics in various scenes:

Here are the links to download the collected data:

People tracking [April 16] Depth videos + ground truth human poses from 2 viewpoints to improve 3D human pose estimation. [project page]
freak [April 16] Depth images + ground truth identity to improve human identification with depth images. [project page]
Graph matching [Dec 15] RGB images +Wireless signals (RSS) from individuals in both indoor and outdoor spaces to improve localization and tracking algorithms. [project page]
People tracking [Jan 16] Aerial RGB videos + ground truth trajectories from multiple targets (e.g., pedestrians, bicyclist, skateboarders, carts,...) navigating an outdoor campus to learn all interactions between humans and their surrounding. [project page]
People tracking


[Jun 14] Human trajectories from an indoor train terminal to learn social dynamics in crowded scenes. [project page]


freak [Aug 09] Low-resolution RGB videos + ground truth trajectories from multiple fixed and moving cameras monitoring the same scenes (indoor and outdoor) to improve object tracking and matching. [project page]

 

 

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© alahi {at} stanford.edu
updated: October 2016

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