« Trajectory Management and Analysis » : différence entre les versions

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* Python bindings: inspiration from OpenCV?
* Python bindings: inspiration from OpenCV?
* Representation of clusters, motion patterns: prototypes, paths, Gaussian processes
* Representation of clusters, motion patterns: prototypes, paths, Gaussian processes
==Data Sources==
* http://www.rtreeportal.org/
* http://crawdad.cs.dartmouth.edu/data.php, eg http://crawdad.cs.dartmouth.edu/epfl/mobility
* http://research.microsoft.com/en-us/downloads/b16d359d-d164-469e-9fd4-daa38f2b2e13/default.aspx


==Resources==
==Resources==
* Vlachos (LCSS) http://alumni.cs.ucr.edu/~mvlachos/publications.html
* http://www-ctp.di.fct.unl.pt/~fb/gisruk2011_final.pdf
* http://www-ctp.di.fct.unl.pt/~fb/gisruk2011_final.pdf
* http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5337231
* http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5337231
* http://isl.cs.unipi.gr/pubs/theses/Frentzos_PhD_Thesis_EN.pdf
* http://isl.cs.unipi.gr/pubs/theses/Frentzos_PhD_Thesis_EN.pdf

Version du 8 juin 2012 à 22:31

  • Data structure for trajectories?
    • dimention: 2D, 3D?
    • time dimension: constant sampling rate?
  • Application data:
    • GPS: potentially different sampling rate
    • case of fixed point detection (BT)
    • tracking from video data: potential missing points (occlusion)
  • Exceptions ??
  • Python bindings: inspiration from OpenCV?
  • Representation of clusters, motion patterns: prototypes, paths, Gaussian processes

Data Sources

Resources