Cargando…

Visualizing and quantifying movement from pre-recorded videos: The spectral time-lapse (STL) algorithm

When studying animal behaviour within an open environment, movement-related data are often important for behavioural analyses. Therefore, simple and efficient techniques are needed to present and analyze the data of such movements. However, it is challenging to present both spatial and temporal info...

Descripción completa

Detalles Bibliográficos
Autores principales: Madan, Christopher R, Spetch, Marcia L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000Research 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4038320/
https://www.ncbi.nlm.nih.gov/pubmed/25580219
http://dx.doi.org/10.12688/f1000research.3-19.v1
_version_ 1782318333590241280
author Madan, Christopher R
Spetch, Marcia L
author_facet Madan, Christopher R
Spetch, Marcia L
author_sort Madan, Christopher R
collection PubMed
description When studying animal behaviour within an open environment, movement-related data are often important for behavioural analyses. Therefore, simple and efficient techniques are needed to present and analyze the data of such movements. However, it is challenging to present both spatial and temporal information of movements within a two-dimensional image representation. To address this challenge, we developed the spectral time-lapse (STL) algorithm that re-codes an animal’s position at every time point with a time-specific color, and overlays it with a reference frame of the video, to produce a summary image. We additionally incorporated automated motion tracking, such that the animal’s position can be extracted and summary statistics such as path length and duration can be calculated, as well as instantaneous velocity and acceleration. Here we describe the STL algorithm and offer a freely available MATLAB toolbox that implements the algorithm and allows for a large degree of end-user control and flexibility.
format Online
Article
Text
id pubmed-4038320
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher F1000Research
record_format MEDLINE/PubMed
spelling pubmed-40383202015-01-09 Visualizing and quantifying movement from pre-recorded videos: The spectral time-lapse (STL) algorithm Madan, Christopher R Spetch, Marcia L F1000Res Web Tool When studying animal behaviour within an open environment, movement-related data are often important for behavioural analyses. Therefore, simple and efficient techniques are needed to present and analyze the data of such movements. However, it is challenging to present both spatial and temporal information of movements within a two-dimensional image representation. To address this challenge, we developed the spectral time-lapse (STL) algorithm that re-codes an animal’s position at every time point with a time-specific color, and overlays it with a reference frame of the video, to produce a summary image. We additionally incorporated automated motion tracking, such that the animal’s position can be extracted and summary statistics such as path length and duration can be calculated, as well as instantaneous velocity and acceleration. Here we describe the STL algorithm and offer a freely available MATLAB toolbox that implements the algorithm and allows for a large degree of end-user control and flexibility. F1000Research 2014-01-21 /pmc/articles/PMC4038320/ /pubmed/25580219 http://dx.doi.org/10.12688/f1000research.3-19.v1 Text en Copyright: © 2014 Madan CR and Spetch ML http://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/publicdomain/zero/1.0/ Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).
spellingShingle Web Tool
Madan, Christopher R
Spetch, Marcia L
Visualizing and quantifying movement from pre-recorded videos: The spectral time-lapse (STL) algorithm
title Visualizing and quantifying movement from pre-recorded videos: The spectral time-lapse (STL) algorithm
title_full Visualizing and quantifying movement from pre-recorded videos: The spectral time-lapse (STL) algorithm
title_fullStr Visualizing and quantifying movement from pre-recorded videos: The spectral time-lapse (STL) algorithm
title_full_unstemmed Visualizing and quantifying movement from pre-recorded videos: The spectral time-lapse (STL) algorithm
title_short Visualizing and quantifying movement from pre-recorded videos: The spectral time-lapse (STL) algorithm
title_sort visualizing and quantifying movement from pre-recorded videos: the spectral time-lapse (stl) algorithm
topic Web Tool
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4038320/
https://www.ncbi.nlm.nih.gov/pubmed/25580219
http://dx.doi.org/10.12688/f1000research.3-19.v1
work_keys_str_mv AT madanchristopherr visualizingandquantifyingmovementfromprerecordedvideosthespectraltimelapsestlalgorithm
AT spetchmarcial visualizingandquantifyingmovementfromprerecordedvideosthespectraltimelapsestlalgorithm