Ant tracking with occlusion tunnels

Fasciano, Thomas; Shin, Min Chul

doi:10.1109/wacv.2014.6836002

Cited by 11 publications

(10 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The second challenge is to associate ants in different frames to tackle the “who is who” problem, given ant detection results in each frame. Regarding these challenges, several methods have been proposed for ant tracking, such as gap filling (Fasciano et al ., ), occlusion tunnels methods (Fasciano et al ., ), video playback and fragment correction methods (Poff et al ., ), but these methods could not solve issues such as ant body overlapping and low contrast problems.…”

Section: Methodsmentioning

confidence: 99%

Heterogeneous activity causes a nonlinear increase in the group energy use of ant workers isolated from queen and brood

Ferral

Holloway

et al. 2017

Insect Science

View full text Add to dashboard Cite

Increasing evidence has shown that the energy use of ant colonies increases sublinearly with colony size so that large colonies consume less per capita energy than small colonies. It has been postulated that social environment (e.g., in the presence of queen and brood) is critical for the sublinear group energetics, and a few studies of ant workers isolated from queens and brood observed linear relationships between group energetics and size. In this paper, we hypothesize that the sublinear energetics arise from the heterogeneity of activity in ant groups, that is, large groups have relatively more inactive members than small groups. We further hypothesize that the energy use of ant worker groups that are allowed to move freely increases more slowly than the group size even if they are isolated from queen and brood. Previous studies only provided indirect evidence for these hypotheses due to technical difficulties. In this study, we applied the automated behavioral monitoring and respirometry simultaneously on isolated worker groups for long time periods, and analyzed the image with the state-of-the-art algorithms. Our results show that when activity was not confined, large groups had lower per capita energy use, a lower percentage of active members, and lower average walking speed than small groups; while locomotion was confined, however, the per capita energy use was a constant regardless of the group size. The quantitative analysis shows a direct link between variation in group energy use and the activity level of ant workers when isolated from queen and brood.

show abstract

Section: Methodsmentioning

confidence: 99%

Heterogeneous activity causes a nonlinear increase in the group energy use of ant workers isolated from queen and brood

Ferral

Holloway

et al. 2017

Insect Science

View full text Add to dashboard Cite

show abstract

“…Solutions for automated video tracking of insects in social groups can be roughly divided into two categories (for reviews see Dell et al, 2014 ; Robie et al, 2017a ): methods for tracking unmarked individuals ( Branson et al, 2009 ; Pérez-Escudero et al, 2014 ; Romero-Ferrero et al, 2019 ; Sridhar et al, 2019 ; Feldman et al, 2012 ; Khan et al, 2005 ; Fasciano et al, 2014 ; Fasciano et al, 2013 ; Bozek et al, 2020 ), and methods for tracking marked individuals ( Mersch et al, 2013 ; Robinson et al, 2012 ). The former category has the obvious advantages of reduced interference with natural behavior, unbounded number of tracked individuals, and not having the burden of tagging animals and maintaining these tags throughout the experiment.…”

Section: Introductionmentioning

confidence: 99%

anTraX, a software package for high-throughput video tracking of color-tagged insects

Gal

Saragosti

Kronauer

2020

eLife

View full text Add to dashboard Cite

Recent years have seen a surge in methods to track and analyze animal behavior. Nevertheless, tracking individuals in closely interacting, group-living organisms remains a challenge. Here, we present anTraX, an algorithm and software package for high-throughput video tracking of color-tagged insects. anTraX combines neural network classification of animals with a novel approach for representing tracking data as a graph, enabling individual tracking even in cases where it is difficult to segment animals from one another, or where tags are obscured. The use of color tags, a well-established and robust method for marking individual insects in groups, relaxes requirements for image size and quality, and makes the software broadly applicable. anTraX is readily integrated into existing tools and methods for automated image analysis of behavior to further augment its output. anTraX can handle large-scale experiments with minimal human involvement, allowing researchers to simultaneously monitor many social groups over long time periods.

show abstract

“…However, although complex social behavior has been the focus of extensive research for over a century, technological advances are only beginning to enable systematic and simultaneous measurements of behavior in large groups of interacting individuals. Solutions for automated video tracking of insects in social groups can be roughly divided into two categories (for reviews see [5,6]): methods for tracking unmarked individuals [13][14][15][16][17][18][19][20][21], and methods for tracking marked individuals [22,23]. The former category has the obvious advantages of reduced interference with natural behavior, less constrained experimental conditions, and an unbounded number of tracked individuals.…”

Section: Introductionmentioning

confidence: 99%

“…The challenge in this approach is to resolve individuals from each other and link their locations in consecutive frames during close range interactions, when they are touching or occluding each other. Common solutions to this problem are to employ sophisticated segmentation methods [13,14,16], to use predictive modeling of the animal motion [13,20], or to use image characteristics to match individuals before and after occlusions [19]. The success of these solutions is case-specific and will usually be limited to relatively simple problems, where interactions are brief, occlusion is minimal, and image resolution is sufficient to resolve the individuals even during an interaction.…”

Section: Introductionmentioning

confidence: 99%

anTraX: high throughput video tracking of color-tagged insects

Gal

Saragosti

Kronauer

2020

Preprint

View full text Add to dashboard Cite

Recent years have seen a surge in methods to track and analyze animal behavior. Nevertheless, tracking individuals in closely interacting, group-living organisms remains a challenge. Here we present anTraX, an algorithm and software package for high-throughput video tracking of color-tagged insects. anTraX combines neural network classification of animals with a novel approach for representing tracking data as a graph, enabling individual tracking even in cases where it is difficult to segment animals from one another, or where tags are obscured. The use of color tags, a well-established and robust method for marking individual insects in groups, relaxes requirements for image size and quality, and makes the software broadly applicable. anTraX is readily integrated into existing tools and methods for automated image analysis of behavior to further augment its output. anTraX can handle large-scale experiments with minimal human involvement, allowing researchers to simultaneously monitor many social groups over long time periods.

show abstract

Ant tracking with occlusion tunnels

Cited by 11 publications

References 15 publications

Heterogeneous activity causes a nonlinear increase in the group energy use of ant workers isolated from queen and brood

Heterogeneous activity causes a nonlinear increase in the group energy use of ant workers isolated from queen and brood

anTraX, a software package for high-throughput video tracking of color-tagged insects

anTraX: high throughput video tracking of color-tagged insects

Contact Info

Product

Resources

About