BEHAVE - facilitating behaviour coding from videos with AI-detected animals
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| Název: | BEHAVE - facilitating behaviour coding from videos with AI-detected animals |
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| Autoři: | Reinoud Elhorst, Martyna Syposz, Katarzyna Wojczulanis-Jakubas |
| Zdroj: | Ecological Informatics, Vol 87, Iss , Pp 103106- (2025) |
| Informace o vydavateli: | Elsevier, 2025. |
| Rok vydání: | 2025 |
| Sbírka: | LCC:Information technology LCC:Ecology |
| Témata: | Animal behaviour, Behavioural analysis, Artificial intelligence, Deep learning, Image recognition, Continuous video surveillance, Information technology, T58.5-58.64, Ecology, QH540-549.5 |
| Popis: | Applying video recording to investigate behaviour of wild animals reduces field workload, enhances data accuracy, and minimises disturbance to animals. However, extracting information from collected video data remains a cumbersome and time-consuming task if not, at least partly, automated. Recent advancements in artificial intelligence (AI) offer automatic detection of target animals in video streams, however integrating these detections with software to annotate behaviours is missing. In addition, programs that are able to do these AI detections are often not easy to install or require specialised hardware to run. To address this gap, we introduce BEHAVE, a user-friendly, open-source, free, zero-install tool for coding animal behaviour in video recordings. BEHAVE can use the results of AI detections to skip sections of the video, can extract timestamps from video data, and supports programmable ethograms. The results are saved in a .csv file for further processing. BEHAVE includes a component that allows doing AI detections, on non-specialised hardware, also in a zero-install, user-friendly way. Due to these advantages, the behaviour coding process can be significantly accelerated, resulting in well-organised and readily exportable/importable data. |
| Druh dokumentu: | article |
| Popis souboru: | electronic resource |
| Jazyk: | English |
| ISSN: | 1574-9541 |
| Relation: | http://www.sciencedirect.com/science/article/pii/S1574954125001153; https://doaj.org/toc/1574-9541 |
| DOI: | 10.1016/j.ecoinf.2025.103106 |
| Přístupová URL adresa: | https://doaj.org/article/4722eaa4bb2f4f61863fe6b2dde5ed01 |
| Přístupové číslo: | edsdoj.4722eaa4bb2f4f61863fe6b2dde5ed01 |
| Databáze: | Directory of Open Access Journals |
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Nájsť tento článok vo Web of Science | Abstrakt: | Applying video recording to investigate behaviour of wild animals reduces field workload, enhances data accuracy, and minimises disturbance to animals. However, extracting information from collected video data remains a cumbersome and time-consuming task if not, at least partly, automated. Recent advancements in artificial intelligence (AI) offer automatic detection of target animals in video streams, however integrating these detections with software to annotate behaviours is missing. In addition, programs that are able to do these AI detections are often not easy to install or require specialised hardware to run. To address this gap, we introduce BEHAVE, a user-friendly, open-source, free, zero-install tool for coding animal behaviour in video recordings. BEHAVE can use the results of AI detections to skip sections of the video, can extract timestamps from video data, and supports programmable ethograms. The results are saved in a .csv file for further processing. BEHAVE includes a component that allows doing AI detections, on non-specialised hardware, also in a zero-install, user-friendly way. Due to these advantages, the behaviour coding process can be significantly accelerated, resulting in well-organised and readily exportable/importable data. |
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| ISSN: | 15749541 |
| DOI: | 10.1016/j.ecoinf.2025.103106 |