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Non-invasive devices and methods for large animal monitoring using automated video processing

Fabienne Porée 1 Vincent Creuze 2, * Marie-Laure Specq 3 Nathalie Samson 3 Jean-Paul Praud 3 Guy Carrault 1 
* Corresponding author
2 ICAR - Image & Interaction
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Objectives: It is now standard for polysomnographical equipment to include video recording, although this modality is generally underexploited, since there is no automated processing associated with the latter. In thepresent report, we investigated the set of features that can be automatically extracted from a video recording, in the context of monitoring of freely moving, non-sedated, newborn lambs. Material and methods: Our database contained seven lambs and a total of 11 recordings, using two different cameras allowing a top view and a side view. Using appropriate methodologies, we show that it is possible to estimate the lamb's movements, its posture (standing or lying) as well as its covered trajectory. Results: Results are discussed as a function of the camera and show that side view recording is well suited for accurate scoring of the lamb's posture, whereas trajectory is best estimated using the top view camera. On the other hand, both cameras provide qualitatively similar results for the estimation of movement of the animals. Conclusion: The data gained from automated video processing, as reported herein, may have multiple applications, especially for animal studies, but may also be extended to human sleep monitoring.
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Submitted on : Monday, September 15, 2014 - 8:58:00 PM
Last modification on : Wednesday, September 14, 2022 - 10:20:04 AM
Long-term archiving on: : Tuesday, December 16, 2014 - 11:45:16 AM


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Fabienne Porée, Vincent Creuze, Marie-Laure Specq, Nathalie Samson, Jean-Paul Praud, et al.. Non-invasive devices and methods for large animal monitoring using automated video processing. Innovation and Research in BioMedical engineering, 2014, 35 (4), pp.173-181. ⟨10.1016/j.irbm.2014.02.002⟩. ⟨lirmm-01064247⟩



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