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Multi-Camera Multi-Object Tracking: ICG Lab6

Multi-Camera Multi-Object Tracking: ICG Lab6

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Environment Audio,3D Box Tracking

This dataset contains 6 indoor people tracking scenarios recorded at our laboratory using 4 static Axis P1347 cameras:Ch......

数据结构 ? 585M

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    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    This dataset contains 6 indoor people tracking scenarios recorded at our laboratory using 4 static Axis P1347 cameras:

    • Changing appearance (Chap): This sequence depicts a standard surveillance scenario, where 5 people move unconstrained within the laboratory. Throughout the scene, the people change their visual appearance by putting on jackets with significantly different colors than their sweaters.

    • Leapfrogs (Leaf 1 & 2): These scenarios depict leapfrog games where players leap over each other’s stooped backs. Specific challenges of these sequences are the spatial proximity of players, out-of-plane motion, and difficult poses.

    • Musical chairs (Much): This sequence shows 4 people playing musical chairs and a non-playing moderator who starts and stops the recorded music. Due to the nature of this game, this sequence exhibits fast motion, as well as crowded situations, e.g., when all players race to the available chairs. Furthermore, sitting on the chairs is a rather unusual pose for typical surveillance scenarios and violates the commonly used constraint of standing persons.

    • Pose: This sequence shows up to 6 people in various poses, such as standing, walking, kneeling, crouching, crawling, sitting, and stepping on ladders.

    • Table: This scenario exhibits significant out-of-plane motion as up to 5 people walk and jump over a table.

    For each scenario, we provide the synchronized video streams, the full (extrinsic & intrinsic) camera calibration, manually annotated groundtruth for every 10th frame, as well as a top-view model of the ground-plane.

    Citation

    If you use this data or software, please cite our paper:

    Robust Real-Time Tracking of Multiple Objects by Volumetric Mass Densities
       Horst Possegger, Sabine Sternig, Thomas Mauthner, Peter M. Roth and Horst Bischof
       In Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013  

    BibTeX reference for convenience:

    @INPROCEEDINGS{possegger13a,
      author = {Horst Possegger and Sabine Sternig and Thomas Mauthner and Peter M. Roth and Horst Bischof},
      title = {{Robust Real-Time Tracking of Multiple Objects by Volumetric Mass Densities}},
      booktitle = {{Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}},
      year = {2013}
    }


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