« Trajectory Management and Analysis » : différence entre les versions

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* Application data:
* Application data:
** GPS: potentially different sampling rate
** GPS: potentially different sampling rate
** case of fixed point detection (BT)
** fixed point detection (eg, BT)
** mobile id detection (BT from mobile sensors such as smartphones (Y. Malinovskiy))
** tracking from video data: potential missing points (occlusion)
** tracking from video data: potential missing points (occlusion)
* Exceptions ??
* Exceptions ??
* Python bindings: inspiration from OpenCV?
* Python bindings: inspiration from OpenCV?
* Generic interface to different database engines, possibly with spatial extensions (eg PostgreSQL with PostGIS, SQLite with SpatiaLite)
* Representation of clusters, motion patterns: prototypes, paths, Gaussian processes
* Representation of clusters, motion patterns: prototypes, paths, Gaussian processes
* Use of Catch for tests (https://github.com/philsquared/Catch): [https://raw.github.com/philsquared/Catch/master/single_include/catch.hpp header] only
* Use of Catch for tests (https://github.com/philsquared/Catch): [https://raw.github.com/philsquared/Catch/master/single_include/catch.hpp header] only
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==Resources==
==Resources==
* Microsoft Research http://research.microsoft.com/pubs/164590/KDD12-PopularRoutes.pdf
* Vlachos (LCSS) http://alumni.cs.ucr.edu/~mvlachos/publications.html
* 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 20 décembre 2012 à 21:37

  • Data structure for trajectories?
    • dimention: 2D, 3D?
    • time dimension: constant sampling rate?
  • Application data:
    • GPS: potentially different sampling rate
    • fixed point detection (eg, BT)
    • mobile id detection (BT from mobile sensors such as smartphones (Y. Malinovskiy))
    • tracking from video data: potential missing points (occlusion)
  • Exceptions ??
  • Python bindings: inspiration from OpenCV?
  • Generic interface to different database engines, possibly with spatial extensions (eg PostgreSQL with PostGIS, SQLite with SpatiaLite)
  • Representation of clusters, motion patterns: prototypes, paths, Gaussian processes
  • Use of Catch for tests (https://github.com/philsquared/Catch): header only

Data Sources

Resources