Data association based ant tracking with interactive error correction

Hoan Nguyen, Thomas Fasciano, Daniel Charbonneau, Anna Dornhaus, Min C. Shin

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

1 Scopus citations

Abstract

The tracking of ants in video is important for the analysis of their complex group behavior. However, the manual analysis of these videos is tedious and time consuming. Automated tracking methods tend to drift due to frequent occlusions during their interactions and similarity in appearance. Semi-automated tracking methods enable corrections of tracking errors by incorporating user interaction. Although it is much lower than manual analysis, the required user time of the existing method is still typically 23 times the actual video length. In this paper, we propose a new semi-automated method that achieves similar accuracy while reducing the user interaction time by (1) mitigating user wait time by incorporating a data association tracking method to separate the tracking from user correction, and (2) minimizing the number of candidates visualized for user during correction. This proposed method is able to reduce the user interaction time by 67% while maintaining the accuracy within 3% of the previous semi-automated method [11].

Original languageEnglish (US)
Title of host publication2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014
PublisherIEEE Computer Society
Pages941-946
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

    Nguyen, H., Fasciano, T., Charbonneau, D., Dornhaus, A., & Shin, M. C. (2014). Data association based ant tracking with interactive error correction. In 2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014 (pp. 941-946). [6836003] (2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014). IEEE Computer Society. https://doi.org/10.1109/WACV.2014.6836003