Computing Consensus Curves

5 Dec 2012  ·  Livio De La Cruz, Stephen Kobourov, Sergey Pupyrev, Paul Shen, Sankar Veeramoni ·

We consider the problem of extracting accurate average ant trajectories from many (possibly 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 much better at this task, provided a robust method to computing the average trajectories. We implemented and tested several local (one ant at a time) and global (all ants together) method. Our best performing algorithm uses a novel global method, based on finding edge-disjoint paths in an ant-interaction graph constructed from the input trajectories. The underlying optimization problem is a new and interesting variant of network flow. Even though the problem is NP-hard, we implemented two heuristics, which work very well in practice, outperforming all other approaches, including the best automated system.

PDF Abstract
No code implementations yet. Submit your code now



  Add Datasets introduced or used in this paper

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.


No methods listed for this paper. Add relevant methods here