An Automated AI Framework for Quantitative Measurement of Mammalian Behavior

Despite the large amount of video data captured during ethological studies of wild mammals, there is no widely accepted method available to automatically and quantitatively measure and analyze animal behavior. We developed a framework using facial recognition and deep learning to automatically track, measure, and quantify the behavior of single or multiple individuals from 10 distinct mammalian taxa, including three species of primates, three species of bovids, three species of carnivores, and one species of equid. We used spatiotemporal information based on animal skeleton models to recognize a set of distinct behaviors such as walking, feeding, grooming, and resting, and achieved an accuracy ranging from 0.82 to 0.96. Accuracies of validation videos ranged from 0.80 to 0.99. Our study offers an innovative analytical platform for the rapid and accurate evaluation of animal behavior in both captive and field settings.

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Publication Details

Journal
Integrative Zoology
Published
2025-04-14
DOI
https://doi.org/10.1111/1749-4877.12985
Citations
1
Primary Topic
Primate Behavior and Ecology
Type
article
Field-Weighted Citation Impact
2.44

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article en
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Abstract

Despite the large amount of video data captured during ethological studies of wild mammals, there is no widely accepted method available to automatically and quantitatively measure and analyze animal behavior. We developed a framework using facial recognition and deep learning to automatically track, measure, and quantify the behavior of single or multiple individuals from 10 distinct mammalian taxa, including three species of primates, three species of bovids, three species of carnivores, and one species of equid. We used spatiotemporal information based on animal skeleton models to recognize a set of distinct behaviors such as walking, feeding, grooming, and resting, and achieved an accuracy ranging from 0.82 to 0.96. Accuracies of validation videos ranged from 0.80 to 0.99. Our study offers an innovative analytical platform for the rapid and accurate evaluation of animal behavior in both captive and field settings.

Integrative ZoologyVol. 21(2)
University of Illinois Urbana-Champaign (US), The University of Western Australia (AU), Chinese Academy of Sciences (CN), Vancouver Island University (CA), Northwest University (CN), Yanan University Affiliated Hospital (CN), Xinjiang Institute of Ecology and Geography (CN), Shaanxi Institute of Zoology (CN), Dali University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 14%
Primate Behavior and Ecology
2.44
DOIOpen Access PDFOpenAlex
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