Multiple ant tracking with global foreground maximization and variable target proposal distribution

Mary Fletcher, Anna Dornhaus, Min C. Shin

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

13 Scopus citations

Abstract

Motion and behavior analysis of social insects such as ants requires tracking many ants over time. This process is highly labor-intensive and tedious. Automatic tracking is challenging as ants often interact with one another, resulting in frequent occlusions that cause drifts in tracking. In addition, tracking many objects is computationally expensive. In this paper, we present a robust and efficient method for tracking multiple ants. We first prevent drifts by maximizing the coverage of foreground pixels at at global scale. Secondly, we improve speed by reducing markov chain length through dynamically changing the target proposal distribution for perturbed ant selection. Using a real dataset with ground truth, we demonstrate that our algorithm was able to improve the accuracy by 15% (resulting in 98% tracking accuracy) and the speed by 76%.

Original languageEnglish (US)
Title of host publication2011 IEEE Workshop on Applications of Computer Vision, WACV 2011
Pages570-576
Number of pages7
DOIs
Publication statusPublished - 2011
Event2011 IEEE Workshop on Applications of Computer Vision, WACV 2011 - Kona, HI, United States
Duration: Jan 5 2011Jan 7 2011

Other

Other2011 IEEE Workshop on Applications of Computer Vision, WACV 2011
CountryUnited States
CityKona, HI
Period1/5/111/7/11

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ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

Cite this

Fletcher, M., Dornhaus, A., & Shin, M. C. (2011). Multiple ant tracking with global foreground maximization and variable target proposal distribution. In 2011 IEEE Workshop on Applications of Computer Vision, WACV 2011 (pp. 570-576). [5711555] https://doi.org/10.1109/WACV.2011.5711555