Tracking for Quantifying Social Network of Drosophila Melanogaster

  • Tanmay Nath
  • Guangda Liu
  • Barbara Weyn
  • Bassem Hassan
  • Ariane Ramaekers
  • Steve De Backer
  • Paul Scheunders
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8048)

Abstract

We introduce a simple, high performance and fast computer vision algorithm (Flytracker) for quantifying the social network of Drosophila Melanogaster. FlyTracker is fully automated software for detecting and tracking multiple flies simultaneous using low resolution video footage. These videos were acquired using Flyworld, a dedicated imaging platform. The developed algorithm segments and tracks the flies over time. From the obtained tracks, features for each fly are derived, allowing quantitative analysis of fly behavior. These features include location, orientation and time of interaction, and allow the quantification of fly-interactions. These social interactions, when computed in a group, form a social network, from which we can infer transient social interactions. To test FlyTracker, it is compared to current state of the art software for fly tracking. Results show that FlyTracker is able to track the flies in low resolution with better accuracy and thus providing an aid in quantifying their social network.

Keywords

Machine vision Drosophila Melanogaster Tracking Social Network 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Tanmay Nath
    • 1
    • 3
  • Guangda Liu
    • 2
    • 4
  • Barbara Weyn
    • 3
  • Bassem Hassan
    • 2
  • Ariane Ramaekers
    • 2
  • Steve De Backer
    • 3
  • Paul Scheunders
    • 1
  1. 1.Vision LabUniversity of AntwerpBelgium
  2. 2.VIBKU LeuvenBelgium
  3. 3.DCILabsBelgium
  4. 4.Peira Scientific InstrumentsBelgium

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