Qtrajectories: improving the quality of object tracking using self-organizing camera networks

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Jaenen, Uwe; Feuerhake, Udo; Klinger, Tobias; Muhle, Daniel; Haehner, Joerg; Sester, Monika et al.: Qtrajectories: improving the quality of object tracking using self-organizing camera networks. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences I-4 (2012), Nr. 1, S. 269-274. DOI: https://doi.org/10.5194/isprsannals-i-4-269-2012

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/5032

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Sum total of downloads: 25




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Abstract: 
Previous work in the research field of video surveillance intensively focused on separated aspects of object detection, data association, pattern recognition and system design. In contrast, we propose a holistic approach for object tracking in a self-organizing and distributed smart camera network. Each observation task is represented by a software-agent which improves the tracking performance by collaborative behavior. An object tracking agent detects persons in a video stream and associates them with a trajectory. The pattern recognition agent analyses these trajectories by detecting points of interest within the observation field. These are characterized by a non-deterministic behavior of the moving person. The trajectory points (enriched by the results of the pattern recognition agent) will be used by a configuration agent to align the cameras field of view. We show that this collaboration improves the performance of the observation system by increasing the amount of detected trajectory points by 22%.
License of this version: CC BY 3.0 Unported
Document Type: article
Publishing status: publishedVersion
Issue Date: 2012
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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pos. country downloads
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1 image of flag of Germany Germany 20 80.00%
2 image of flag of Portugal Portugal 2 8.00%
3 image of flag of Nepal Nepal 2 8.00%
4 image of flag of Estonia Estonia 1 4.00%

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