trackdem: 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.

Version:	0.7.2
Imports:	png, neuralnet, raster, Rcpp, MASS, grDevices, graphics, stats, shiny
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	knitr, rmarkdown, testthat
Published:	2024-05-08
DOI:	10.32614/CRAN.package.trackdem
Author:	Marjolein Bruijning, Marco D. Visser, Caspar A. Hallmann, Eelke Jongejans
Maintainer:	Marjolein Bruijning <m.bruijning at uva.nl>
BugReports:	https://github.com/marjoleinbruijning/trackdem/issues
License:	GPL-2
URL:	https://github.com/marjoleinbruijning/trackdem
NeedsCompilation:	yes
SystemRequirements:	Python (>=2.7), Libav, ExifTool
Citation:	trackdem citation info
In views:	SpatioTemporal, Tracking
CRAN checks:	trackdem results

Documentation:

Reference manual:	trackdem.pdf
Vignettes:	Tutorial

Downloads:

Package source:	trackdem_0.7.2.tar.gz
Windows binaries:	r-devel: trackdem_0.7.2.zip, r-release: trackdem_0.7.2.zip, r-oldrel: trackdem_0.7.2.zip
macOS binaries:	r-release (arm64): trackdem_0.7.2.tgz, r-oldrel (arm64): trackdem_0.7.2.tgz, r-release (x86_64): trackdem_0.7.2.tgz, r-oldrel (x86_64): trackdem_0.7.2.tgz
Old sources:	trackdem archive

Linking:

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