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一种用于监测灵长类动物群体的实时三维视频跟踪系统。

A real-time 3D video tracking system for monitoring primate groups.

作者信息

Ballesta S, Reymond G, Pozzobon M, Duhamel J-R

机构信息

Centre de Neuroscience Cognitive, Centre National de la Recherche Scientifique, 69675 Bron, France; Département de Biologie Humaine, Université Lyon 1, 69622 Villeurbanne, France.

Centre de Neuroscience Cognitive, Centre National de la Recherche Scientifique, 69675 Bron, France; Département de Biologie Humaine, Université Lyon 1, 69622 Villeurbanne, France.

出版信息

J Neurosci Methods. 2014 Aug 30;234:147-52. doi: 10.1016/j.jneumeth.2014.05.022. Epub 2014 May 27.

DOI:10.1016/j.jneumeth.2014.05.022
PMID:24875622
Abstract

To date, assessing the solitary and social behaviors of laboratory primates' colonies relies on time-consuming manual scoring methods. Here, we describe a real-time multi-camera 3D tracking system developed to measure the behavior of socially-housed primates. Their positions are identified using non-invasive color markers such as plastic collars, thus allowing to also track colored objects and to measure their usage. Compared to traditional manual ethological scoring, we show that this system can reliably evaluate solitary behaviors (foraging, solitary resting, toy usage, locomotion) as well as spatial proximity with peers, which is considered as a good proxy of their social motivation. Compared to existing video-based commercial systems currently available to measure animal activity, this system offers many possibilities (real-time data, large volume coverage, multiple animal tracking) at a lower hardware cost. Quantitative behavioral data of animal groups can now be obtained automatically over very long periods of time, thus opening new perspectives in particular for studying the neuroethology of social behavior in primates.

摘要

到目前为止,评估实验室灵长类动物群体的单独行为和社交行为依赖于耗时的人工评分方法。在此,我们描述了一种为测量群居灵长类动物行为而开发的实时多摄像头3D跟踪系统。它们的位置通过非侵入性颜色标记(如塑料项圈)来识别,从而也能够跟踪有颜色的物体并测量其使用情况。与传统的人工行为学评分相比,我们表明该系统能够可靠地评估单独行为(觅食、单独休息、玩具使用、移动)以及与同伴的空间接近程度,这被认为是它们社交动机的良好指标。与目前可用于测量动物活动的现有基于视频的商业系统相比,该系统以较低的硬件成本提供了许多可能性(实时数据、大面积覆盖、多动物跟踪)。现在可以在很长一段时间内自动获取动物群体的定量行为数据,从而为研究灵长类动物社交行为的神经行为学开辟了新的前景。

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