Computing consensus curves

Livio De La Cruz, Stephen Kobourov, Sergey Pupyrev, Paul S. Shen, Sankar Veeramoni

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationExperimental Algorithms - 13th International Symposium, SEA 2014, Proceedings
PublisherSpringer-Verlag
Pages223-234
Number of pages12
ISBN (Print)9783319079585
DOIs
StatePublished - Jan 1 2014
Event13th International Symposium on Experimental Algorithms, SEA 2014 - Copenhagen, Denmark
Duration: Jun 29 2014Jul 1 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8504 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th International Symposium on Experimental Algorithms, SEA 2014
CountryDenmark
CityCopenhagen
Period6/29/147/1/14

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    De La Cruz, L., Kobourov, S., Pupyrev, S., Shen, P. S., & Veeramoni, S. (2014). Computing consensus curves. In Experimental Algorithms - 13th International Symposium, SEA 2014, Proceedings (pp. 223-234). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8504 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-319-07959-2_19