ToxTrac: a fast and robust software for tracking organismsShow others and affiliations
2018 (English)In: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 9, no 3, p. 460-464Article in journal (Refereed) Published
Abstract [en]
1. Behavioral analysis based on video recording is becoming increasingly popular within research fields such as; ecology, medicine, ecotoxicology, and toxicology. However, the programs available to analyze the data, which are; free of cost, user-friendly, versatile, robust, fast and provide reliable statistics for different organisms (invertebrates, vertebrates and mammals) are significantly limited.
2. We present an automated open-source executable software (ToxTrac) for image-based tracking that can simultaneously handle several organisms monitored in a laboratory environment. We compare the performance of ToxTrac with current accessible programs on the web.
3. The main advantages of ToxTrac are: i) no specific knowledge of the geometry of the tracked bodies is needed; ii) processing speed, ToxTrac can operate at a rate >25 frames per second in HD videos using modern computers; iii) simultaneous tracking of multiple organisms in multiple arenas; iv) integrated distortion correction and camera calibration; v) robust against false positives; vi) preservation of individual identification; vii) useful statistics and heat maps in real scale are exported in image, text and excel formats.
4. ToxTrac can be used for high speed tracking of insects, fish, rodents or other species, and provides useful locomotor information in animal behavior experiments. Download ToxTrac here: https://toxtrac.sourceforge.io (Current version v2.61).
Place, publisher, year, edition, pages
British Ecological Society, 2018. Vol. 9, no 3, p. 460-464
Keywords [en]
animal behavior, cockroach, ecology, ecotoxicology, guppy, Kalman filter, salmon, tadpole, tracking software, zebrafish
National Category
Computer Sciences Ecology Other Physics Topics
Identifiers
URN: urn:nbn:se:umu:diva-138329DOI: 10.1111/2041-210X.12874ISI: 000426867600003Scopus ID: 2-s2.0-85030106753OAI: oai:DiVA.org:umu-138329DiVA, id: diva2:1134571
Funder
Swedish Research Council, 2013-5379ÅForsk (Ångpanneföreningen's Foundation for Research and Development)The Kempe Foundations2017-08-212017-08-212024-01-17Bibliographically approved