Computing Consensus Curves

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8504)


We study the problem of extracting accurate average ant trajectories from many (inaccurate) input trajectories contributed by citizen scientists. Although there are many generic software tools for motion tracking and specific ones for insect tracking, even untrained humans are better at this task. We consider several local (one ant at a time) and global (all ants together) methods. Our best performing algorithm uses a novel global method, based on finding edge-disjoint paths in a graph constructed from the input trajectories. The underlying optimization problem is a new and interesting network flow variant. Even though the problem is NP-complete, two heuristics work well in practice, outperforming all other approaches, including the best automated system.


Integer Linear Program Citizen Scientist Global Approach Disjoint Path Fractional Solution 
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 International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of ArizonaTucsonUSA
  2. 2.Institute of Mathematics and Computer ScienceUral Federal UniversityEkaterinburgRussia

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