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ToxId: an efficient algorithm to solve occlusions when tracking multiple animals
Umeå University, Faculty of Science and Technology, Department of Physics.
Umeå University, Faculty of Science and Technology, Department of Physics.
Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
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2017 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, article id 14774Article in journal (Refereed) Published
Abstract [en]

Video analysis of animal behaviour is widely used in fields such as ecology, ecotoxicology, and evolutionary research. However, when tracking multiple animals, occlusion and crossing are problematic, especially when the identity of each individual needs to be preserved. We present a new algorithm, ToxId, which preserves the identity of multiple animals by linking trajectory segments using their intensity histogram and Hu-moments. We verify the performance and accuracy of our algorithm using video sequences with different animals and experimental conditions. The results show that our algorithm achieves state-of-the-art accuracy using an efficient approach without the need of learning processes, complex feature maps or knowledge of the animal shape. ToxId is also computationally efficient, has low memory requirements, and operates without accessing future or past frames.

Place, publisher, year, edition, pages
2017. Vol. 7, article id 14774
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:umu:diva-142244DOI: 10.1038/s41598-017-15104-2ISI: 000414569100064OAI: oai:DiVA.org:umu-142244DiVA, id: diva2:1164545
Funder
Swedish Research Council, 2013-5379Available from: 2017-12-11 Created: 2017-12-11 Last updated: 2018-06-09Bibliographically approved

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Rodriguez, AlvaroZhang, HanqingKlaminder, JonatanBrodin, TomasAndersson, Magnus
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