» Articles » PMID: 37765985

Captive Animal Behavior Study by Video Analysis

Overview
Journal Sensors (Basel)
Publisher MDPI
Specialty Biotechnology
Date 2023 Sep 28
PMID 37765985
Authors
Affiliations
Soon will be listed here.
Abstract

Three video analysis-based applications for the study of captive animal behavior are presented. The aim of the first one is to provide certain parameters to assess drug efficiency by analyzing the movement of a rat. The scene is a three-chamber plastic box. First, the rat can move only in the middle room. The rat's head pose is the first parameter needed. Secondly, the rodent could walk in all three compartments. The entry number in each area and visit duration are the other indicators used in the final evaluation. The second application is related to a neuroscience experiment. Besides the electroencephalographic (EEG) signals yielded by a radio frequency link from a headset mounted on a monkey, the head placement is a useful source of information for reliable analysis, as well as its orientation. Finally, a fusion method to construct the displacement of a panda bear in a cage and the corresponding motion analysis to recognize its stress states are shown. The arena is a zoological garden that imitates the native environment of a panda bear. This surrounding is monitored by means of four video cameras. We have applied the following stages: (a) panda detection for every video camera; (b) panda path construction from all routes; and (c) panda way filtering and analysis.

References
1.
Mathis M, Mathis A . Deep learning tools for the measurement of animal behavior in neuroscience. Curr Opin Neurobiol. 2019; 60:1-11. DOI: 10.1016/j.conb.2019.10.008. View

2.
Zuerl M, Stoll P, Brehm I, Raab R, Zanca D, Kabri S . Automated Video-Based Analysis Framework for Behavior Monitoring of Individual Animals in Zoos Using Deep Learning-A Study on Polar Bears. Animals (Basel). 2022; 12(6). PMC: 8944680. DOI: 10.3390/ani12060692. View

3.
Schutz A, Krause E, Fischer M, Muller T, Freuling C, Conraths F . Computer Vision for Detection of Body Posture and Behavior of Red Foxes. Animals (Basel). 2022; 12(3). PMC: 8833490. DOI: 10.3390/ani12030233. View

4.
Milton R, Shahidi N, Dragoi V . Dynamic states of population activity in prefrontal cortical networks of freely-moving macaque. Nat Commun. 2020; 11(1):1948. PMC: 7181779. DOI: 10.1038/s41467-020-15803-x. View

5.
Chen P, Swarup P, Matkowski W, Kong A, Han S, Zhang Z . A study on giant panda recognition based on images of a large proportion of captive pandas. Ecol Evol. 2020; 10(7):3561-3573. PMC: 7141006. DOI: 10.1002/ece3.6152. View