Particle Tracking and Demography

Obtain population density and body size structure, using video material or image sequences as input. Functions assist in the creation of image sequences from videos, background detection and subtraction, particle identification and tracking. An artificial neural network can be trained for noise filtering. The goal is to supply accurate estimates of population size, structure and/or individual behavior, for use in evolutionary and ecological studies.


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Reference manual

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install.packages("trackdem")

0.4.2 by Marjolein Bruijning, 4 months ago


https://github.com/marjoleinbruijning/trackdem


Report a bug at https://github.com/marjoleinbruijning/trackdem/issues


Browse source code at https://github.com/cran/trackdem


Authors: Marjolein Bruijning , Marco D. Visser , Caspar A. Hallmann , Eelke Jongejans


Documentation:   PDF Manual  


GPL-2 license


Imports png, SDMTools, neuralnet, raster, Rcpp, MASS, grDevices, graphics, stats, shiny

Suggests knitr, rmarkdown, testthat

Linking to Rcpp, RcppArmadillo

System requirements: Python 2.7, Libav, ExifTool


See at CRAN