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Data Preview ? 708K

    Data Structure ?


    Data Set Information:


    Attribute Information:

    : Pedestrian tracks are stored in the tracks.csv. Each row in such files contains 14 comma-separated attributes, with missing values denoted by a€?Nonea€?. The attributes are in order:
    a€¢ oid: unique agent id (int),
    a€¢ timestamp: time in seconds (float),
    a€¢ x: x component of position vector (float),
    a€¢ y: y component of position vector (float),
    a€¢ body_roll: roll body angle in degrees (float),
    a€¢ body_pitch: pitch body angle in degrees (float),
    a€¢ body_yaw: yaw body angle in degrees (float),
    a€¢ head_roll: roll head angle in degrees (float),
    a€¢ head_pitch: pitch head angle in degrees (float),
    a€¢ head_yaw: yaw head angle in degrees (float),
    a€¢ other_oid: list of ids of agents currently present in the scene ([list of int]),
    a€¢ other_class: list of other agentsa€? class labels ([list of int]),
    a€¢ other_x: list of other agentsa€? x coordinates ([list of float]),
    a€¢ other_y: list of other agentsa€? y coordinates ([list of float]).
    Labels used to identify agent types are available in agent_class_label_info.csv.
    The file semantic_map.png contains a map of the static environment, where semantic labels are color-encoded according to the mapping available in semantic_map_label_info.csv. Information needed to transform between image and world coordinates is stored in the file map2world_info.txt.

    Relevant Papers:

    [1] Blaiotta, Claudia. 'Learning generative socially-aware models of pedestrian motion.' IEEE Robotics and Automation Letters, 2019.

    Citation Request:

    You may use this data for scientific, non-commercial purposes, as long as you give credit to the owners when publishing any work based on this data. Please cite [1].