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.
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Nath, T. et al. (2013). Tracking for Quantifying Social Network of Drosophila Melanogaster. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8048. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40246-3_67
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DOI: https://doi.org/10.1007/978-3-642-40246-3_67
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