Unknown

Dataset Information

0

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


ABSTRACT: 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.

SUBMITTER: Madan CR 

PROVIDER: S-EPMC4038320 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

altmetric image

Publications

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

Madan Christopher R CR   Spetch Marcia L ML  

F1000Research 20140121


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 poi  ...[more]

Similar Datasets

| S-EPMC2680402 | biostudies-other
2021-01-31 | E-MTAB-9916 | biostudies-arrayexpress
| S-EPMC2661108 | biostudies-literature
| S-EPMC5738739 | biostudies-literature
| S-EPMC10586693 | biostudies-literature
| S-EPMC9596173 | biostudies-literature
| S-EPMC8504422 | biostudies-literature
| S-EPMC5898563 | biostudies-literature
| S-EPMC5676878 | biostudies-literature
| S-EPMC7812752 | biostudies-literature