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

Madan, Christopher R.; Spetch, Marcia L

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.

Citation

Madan, C. R., & Spetch, M. L. (2014). Visualizing and quantifying movement from pre-recorded videos: The spectral time-lapse (STL) algorithm. F1000Research, 3, 19. https://doi.org/10.12688/f1000research.3-19.v1

• Journal Article Type: Article
• Online Publication Date: Jan 21, 2014
• Publication Date: Jan 21, 2014
• Deposit Date: May 31, 2023
• Publicly Available Date: May 31, 2023
• Journal: F1000Research
• Publisher: F1000Research
• Peer Reviewed: Peer Reviewed
• Volume: 3
• Pages: 19
• DOI: https://doi.org/10.12688/f1000research.3-19.v1
• Keywords: movement; tracking; path analysis; video visualization; video summarization; image analysis
• Public URL: https://nottingham-repository.worktribe.com/output/4930377
• Publisher URL: https://f1000research.com/articles/3-19/v1