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  PanAf20K: A large video dataset for wild ape detection and behaviour recognition (advance online)

Brookes, O., Mirmehdi, M., Stephens, C., Angedakin, S., Corogenes, K., Dowd, D., et al. (2024). PanAf20K: A large video dataset for wild ape detection and behaviour recognition (advance online). International Journal of Computer Vision. doi:10.1007/s11263-024-02003-z.

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Brookes_PanAf20K_IntJCompVis_2024.pdf (Publisher version), 10MB
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Brookes_PanAf20K_IntJCompVis_2024.pdf
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 Creators:
Brookes, Otto, Author
Mirmehdi, Majid, Author
Stephens, Colleen, Author
Angedakin, Samuel1, Author                 
Corogenes, Katherine2, Author           
Dowd, Dervla, Author
Dieguez, Paula1, Author                 
Hicks, Thurston C., Author
Jones, Sorrel2, Author           
Lee, Kevin2, Author           
Leinert, Vera1, Author           
Lapuente, Juan2, Author           
McCarthy, Maureen2, Author                 
Meier, Amelia1, Author           
Murai, Mizuki1, Author                 
Normand, Emmanuelle, Author
Vergnes, Virginie, Author
Wessling, Erin G., Author
Wittig, Roman M.3, Author                 
Langergraber, Kevin, Author
Maldonado, Nuria1, Author           Yang, Xinyu, AuthorZuberbühler, Klaus, AuthorBoesch, Christophe2, 3, Author                 Arandjelovic, Mimi2, 3, Author                 Kühl, Hjalmar S.3, Author                 Burghardt, Tilo, Author more..
Affiliations:
1Department of Primatology, Max Planck Institute for Evolutionary Anthropology, Max Planck Society, ou_1497674              
2Great Ape Evolutionary Ecology and Conservation, Department of Primatology, Max Planck Institute for Evolutionary Anthropology, Max Planck Society, ou_2149638              
3Chimpanzees, Department of Primatology, Max Planck Institute for Evolutionary Anthropology, Max Planck Society, ou_2149636              

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Free keywords: Animal biometrics; Behaviour recognition; Conservation technology; Imageomics; Video dataset; Wildlife
 Abstract: We present the PanAf20K dataset, the largest and most diverse open-access annotated video dataset of great apes in their natural environment. It comprises more than 7 million frames across ~ 20,000 camera trap videos of chimpanzees and gorillas collected at 18 field sites in tropical Africa as part of the Pan African Programme: The Cultured Chimpanzee. The footage is accompanied by a rich set of annotations and benchmarks making it suitable for training and testing a variety of challenging and ecologically important computer vision tasks including ape detection and behaviour recognition. Furthering AI analysis of camera trap information is critical given the International Union for Conservation of Nature now lists all species in the great ape family as either Endangered or Critically Endangered. We hope the dataset can form a solid basis for engagement of the AI community to improve performance, efficiency, and result interpretation in order to support assessments of great ape presence, abundance, distribution, and behaviour and thereby aid conservation efforts. The dataset and code are available from the project website: PanAf20K. © The Author(s) 2024.

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Language(s): eng - English
 Dates: 2024-03-04
 Publication Status: Published online
 Pages: -
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 Rev. Type: Peer
 Identifiers: DOI: 10.1007/s11263-024-02003-z
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Title: International Journal of Computer Vision
Source Genre: Journal
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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: ISSN: 0920-5691
ISSN: 1573-1405