Ant tracking with occlusion tunnels

Thomas Fasciano, Anna Dornhaus, Min C. Shin

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

4 Scopus citations

Abstract

The automated tracking of social insects, such as ants, can efficiently provide unparalleled amounts of data for the of study complex group behaviors. However, a high level of occlusion along with similarity in appearance and motion can cause the tracking to drift to an incorrect ant. In this paper, we reduce drifting by using occlusion to identify incorrect ants and prevent the tracking from drifting to them. The key idea is that a set of ants enter occlusion, move through occlusion then exit occlusion. We do not attempt to track through occlusions but simply find a set of objects that enters and exits them. Knowing that tracking must stay within a set of ants exiting a given occlusion, we reduce drifting by preventing tracking to ants outside the occlusion. Using four 5000 frame video sequences of an ant colony, we demonstrate that the usage of occlusion tunnel reduces the tracking error of (1) drifting to another ant by 30% and (2) early termination of tracking by 7%.

Original languageEnglish (US)
Title of host publication2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014
PublisherIEEE Computer Society
Pages947-952
Number of pages6
ISBN (Print)9781479949854
DOIs
StatePublished - Jan 1 2014
Event2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014 - Steamboat Springs, CO, United States
Duration: Mar 24 2014Mar 26 2014

Publication series

Name2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014

Other

Other2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014
CountryUnited States
CitySteamboat Springs, CO
Period3/24/143/26/14

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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  • Cite this

    Fasciano, T., Dornhaus, A., & Shin, M. C. (2014). Ant tracking with occlusion tunnels. In 2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014 (pp. 947-952). [6836002] (2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014). IEEE Computer Society. https://doi.org/10.1109/WACV.2014.6836002