Title
Tracking for quantifying social network of Drosophila melanogaster Tracking for quantifying social network of Drosophila melanogaster
Author
Faculty/Department
Faculty of Sciences. Physics
Publication type
article
Publication
Subject
Physics
Computer. Automation
Source (journal)
Lecture notes in computer science
Volume/pages
8048(2013) , p. 539-545
ISSN
0302-9743
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
We introduce a simple, high performance and fast computer vision algorithm (Flytracker) for quantifying the social network of Drosophila Melanogaster. FlyTracker is fully automated software for detecting and tracking multiple flies simultaneous using low resolution video footage. These videos were acquired using Flyworld, a dedicated imaging platform. The developed algorithm segments and tracks the flies over time. From the obtained tracks, features for each fly are derived, allowing quantitative analysis of fly behavior. These features include location, orientation and time of interaction, and allow the quantification of fly-interactions. These social interactions, when computed in a group, form a social network, from which we can infer transient social interactions. To test FlyTracker, it is compared to current state of the art software for fly tracking. Results show that FlyTracker is able to track the flies in low resolution with better accuracy and thus providing an aid in quantifying their social network.
Handle