Trajectory Similarity Measures Using Minimal Paths

  • Brais Cancela
  • Marcos Ortega
  • Alba Fernández
  • Manuel G. Penedo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8156)


Dealing with surveillance systems, large amount of distance measures are presented in order to classify both normal and abnormal behavior. Typically, techniques based in point-to-point distances are used. However, these techniques do not take into account information about the environment, like pits or restricted areas, for instance. Using a minimal path algorithm to model the usual paths, we develop new trajectory distance measures that are able to introduce information about the scene. The results obtained show promising results.


Potential Image Abnormal Behavior Dynamic Time Warping Minimal Path Trajectory Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Brais Cancela
    • 1
  • Marcos Ortega
    • 1
  • Alba Fernández
    • 1
  • Manuel G. Penedo
    • 1
  1. 1.Varpa Group, Department of Computer ScienceUniversity of A CoruñaSpain

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