This title appears in the Scientific Report :
2014
Please use the identifier:
http://dx.doi.org/10.1007/978-3-319-02447-9_44 in citations.
Tracking People in Crowded Scenes
Tracking People in Crowded Scenes
For the collection of trajectory data of pedestrian movement in crowds we are developing software for the automatic extraction of accurate trajectories out of video recordings. In this paper a newly introduced method for a markerless detection is presented. This method identifies people by comparing...
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Personal Name(s): | Boltes, Maik (Corresponding Author) |
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Seyfried, Armin | |
Contributing Institute: |
Jülich Supercomputing Center; JSC |
Published in: |
Pedestrian and Evacuation Dynamics 2012 / Cham : Springer International Publishing, 2014, Chapter 44 |
Imprint: |
Cham
Springer International Publishing
2014
|
Physical Description: |
533-542 |
ISBN: |
978-3-319-02446-2 |
DOI: |
10.1007/978-3-319-02447-9_44 |
Conference: | Pedestrian and Evacuation Dynamics 2012, Zürich (Switzerland), 2012-06-06 - 2012-06-08 |
Document Type: |
Contribution to a book Contribution to a conference proceedings |
Research Program: |
Computational Science and Mathematical Methods |
Publikationsportal JuSER |
For the collection of trajectory data of pedestrian movement in crowds we are developing software for the automatic extraction of accurate trajectories out of video recordings. In this paper a newly introduced method for a markerless detection is presented. This method identifies people by comparing the shape of the top part of their body with the perspective depth field of overhead stereo recordings. Features to match are pyramidal stacks of ellipses, which approximate isolines of the same distance to the camera. |