Visualization of Range-Constrained Optimal Density Clustering of Trajectories

  • Muhammed Mas-Ud HussainEmail author
  • Goce Trajcevski
  • Kazi Ashik Islam
  • Mohammed Eunus Ali
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10411)


We present a system for efficient detection, continuous maintenance and visualization of range-constrained optimal density clusters of moving objects trajectories, a.k.a. Continuous Maximizing Range Sum (Co-MaxRS) queries. Co-MaxRS is useful in any domain involving continuous detection of “most interesting” regions involving mobile entities (e.g., traffic monitoring, environmental tracking, etc.). Traditional MaxRS finds a location of a given rectangle R which maximizes the sum of the weighted-points (objects) in its interior. Since moving objects continuously change their locations, the MaxRS at a particular time instant need not be a solution at another time instant. Our system solves two important problems: (1) Efficiently computing Co-MaxRS answer-set; and (2) Visualizing the results. This demo will present the implementation of our efficient pruning schemes and compact data structures, and illustrate the end-user tools for specifying the parameters and selecting datasets for Co-MaxRS, along with visualization of the optimal locations.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Muhammed Mas-Ud Hussain
    • 1
    Email author
  • Goce Trajcevski
    • 1
  • Kazi Ashik Islam
    • 2
  • Mohammed Eunus Ali
    • 2
  1. 1.Department of Electrical Engineering and Computer ScienceNorthwestern UniversityEvanstonUSA
  2. 2.Department of Computer Science and EngineeringBangladesh University of Engineering and TechnologyDhakaBangladesh

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