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

Mary Fletcher; Anna Dornhaus; Min C. Shin

doi:10.1109/WACV.2011.5711555

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 proceeding › Conference contribution

15 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 language	English (US)
Title of host publication	2011 IEEE Workshop on Applications of Computer Vision, WACV 2011
Publisher	IEEE Computer Society
Pages	570-576
Number of pages	7
ISBN (Print)	9781424494965
DOIs	https://doi.org/10.1109/WACV.2011.5711555
State	Published - 2011

Publication series

Name	2011 IEEE Workshop on Applications of Computer Vision, WACV 2011

ASJC Scopus subject areas

Computer Science Applications
Computer Vision and Pattern Recognition

Access to Document

10.1109/WACV.2011.5711555

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). Article 5711555 (2011 IEEE Workshop on Applications of Computer Vision, WACV 2011). IEEE Computer Society. https://doi.org/10.1109/WACV.2011.5711555

Multiple ant tracking with global foreground maximization and variable target proposal distribution. / Fletcher, Mary; Dornhaus, Anna; Shin, Min C.
2011 IEEE Workshop on Applications of Computer Vision, WACV 2011. IEEE Computer Society, 2011. p. 570-576 5711555 (2011 IEEE Workshop on Applications of Computer Vision, WACV 2011).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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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\%.",

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

Abstract

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ASJC Scopus subject areas

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