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NAPS: Integrating pose estimation and tag-based tracking.
Wolf, Scott W; Ruttenberg, Dee M; Knapp, Daniel Y; Webb, Andrew E; Traniello, Ian M; McKenzie-Smith, Grace C; Leheny, Sophie A; Shaevitz, Joshua W; Kocher, Sarah D.
Afiliación
  • Wolf SW; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, USA.
  • Ruttenberg DM; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, USA.
  • Knapp DY; Department of Physics, Princeton University, Princeton, New Jersey, USA.
  • Webb AE; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, USA.
  • Traniello IM; Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, USA.
  • McKenzie-Smith GC; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, USA.
  • Leheny SA; Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, USA.
  • Shaevitz JW; Department of Physics, Princeton University, Princeton, New Jersey, USA.
  • Kocher SD; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, USA.
Methods Ecol Evol ; 14(10): 2541-2548, 2023 Oct.
Article en En | MEDLINE | ID: mdl-38681746
ABSTRACT
1. Significant advances in computational ethology have allowed the quantification of behaviour in unprecedented detail. Tracking animals in social groups, however, remains challenging as most existing methods can either capture pose or robustly retain individual identity over time but not both. 2. To capture finely resolved behaviours while maintaining individual identity, we built NAPS (NAPS is ArUco Plus SLEAP), a hybrid tracking framework that combines state-of-the-art, deep learning-based methods for pose estimation (SLEAP) with unique markers for identity persistence (ArUco). We show that this framework allows the exploration of the social dynamics of the common eastern bumblebee (Bombus impatiens). 3. We provide a stand-alone Python package for implementing this framework along with detailed documentation to allow for easy utilization and expansion. We show that NAPS can scale to long timescale experiments at a high frame rate and that it enables the investigation of detailed behavioural variation within individuals in a group. 4. Expanding the toolkit for capturing the constituent behaviours of social groups is essential for understanding the structure and dynamics of social networks. NAPS provides a key tool for capturing these behaviours and can provide critical data for understanding how individual variation influences collective dynamics.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Methods Ecol Evol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Methods Ecol Evol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos