Evidence map›Paper›PMID 40458158›Full record

ArticleJDS communications2025

AnimalMotionViz: An interactive software tool for tracking and visualizing animal motion patterns using computer vision.

Angelo L De Castro, Jin Wang, Jessica G Bonney-King, Gota Morota, Emily K Miller-Cushon, Haipeng Yu

Abstract read
In one paragraph

Article in JDS communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Angelo L De CastroDepartment of Animal Sciences, University of Florida, Gainesville, FL 32611.
Jin WangDepartment of Animal Sciences, University of Florida, Gainesville, FL 32611.
Jessica G Bonney-KingDepartment of Animal Sciences, University of Florida, Gainesville, FL 32611.
Gota MorotaLaboratory of Biometry and Bioinformatics, Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Bunkyo, Tokyo 113-8657, Japan.
Emily K Miller-CushonDepartment of Animal Sciences, University of Florida, Gainesville, FL 32611.
Haipeng YuDepartment of Animal Sciences, University of Florida, Gainesville, FL 32611.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monitoring the movement patterns of dairy cattle can provide important insight into space utilization or space occupancy in a barn. Although several precision livestock technologies have been developed to record dairy cattle movements, there is a lack of open-source tools to track and visualize group-level cattle movement patterns. Therefore, we developed an open-source computer vision software tool, AnimalMotionViz, that allows users to track and visualize group-level dairy cattle movement patterns using motion maps. The software comes with an easy-to-use web-based graphical user interface built with the Python Dash package. It implements a set of background subtraction algorithms in the OpenCV package to track animal motion patterns in real time. The software processes each frame of the input video and identifies the background and foreground using these algorithms. Foreground objects are then subtracted from the background across all frames and cumulatively overlaid on an empty mask image created with the first frame of the input video to visualize the intensity or frequency of motion across different regions. The user can generate a space-use distribution map in an image and video, a core and full-range map in an image, and also track specific regional motion with a custom mask. The software also returns the top 3 peak intensity locations, the total percentage of regions used, and the within-quadrant percentage of regions used. In four 5-min sample videos, quadrants with peak intensity of space use, as identified using the software, aligned with quadrants where calves spent the greatest duration of time, according to continuous recording of behavior from video. The space-use distribution and core and full-range maps generated by AnimalMotionViz can be used to understand space utilization or space occupation by dairy cattle, as well as to assess how space allocation affects their movement. Although AnimalMotionViz was developed to analyze dairy cattle data, its design provides the potential for broader application in studying the movement patterns of other animal species. We conclude that the newly developed AnimalMotionViz is a user-friendly and efficient tool to support research developments in precision livestock farming toward enhancing cattle management practices and improving pen designs.

Identifiers

PMID40458158
PMCPMC12126821

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.