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...
Autores principales: | , |
---|---|
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 |