Publikation: Automatic framework for tracking honeybee's antennae and mouthparts from low framerate video
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Automatic tracking of the movement of bee's antennae and mouthparts is necessary for studying associative learning of individuals. However, the problem of tracking them is challenging: First, the different classes of objects possess similar appearance and are close to each other. Second, tracking gaps are often present, due to the low frame-rate of the acquired video and the fast motion of the objects. Most existing insect tracking approaches have been developed for slow moving objects, and are not suitable for this application. In this paper, a novel Bayesian framework is proposed to automatically track bees' antennae and their mouthparts. This framework incorporates information about their kinematics, shape, order and temporal correlation between neighboring frames. Experimental evaluation demonstrates the effectiveness and efficiency of the proposed framework.
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SHEN, Minmin, Paul SZYSZKA, C. Giovanni GALIZIA, Dorit MERHOF, 2013. Automatic framework for tracking honeybee's antennae and mouthparts from low framerate video. 2013 20th IEEE International Conference on Image Processing (ICIP). Melbourne, Australia, 15. Sept. 2013 - 18. Sept. 2013. In: 2013 IEEE International Conference on Image Processing. IEEE, 2013, pp. 4112-4116. ISBN 978-1-4799-2341-0. Available under: doi: 10.1109/ICIP.2013.6738847BibTex
@inproceedings{Shen2013-09Autom-26119, year={2013}, doi={10.1109/ICIP.2013.6738847}, title={Automatic framework for tracking honeybee's antennae and mouthparts from low framerate video}, isbn={978-1-4799-2341-0}, publisher={IEEE}, booktitle={2013 IEEE International Conference on Image Processing}, pages={4112--4116}, author={Shen, Minmin and Szyszka, Paul and Galizia, C. Giovanni and Merhof, Dorit} }
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