Automated monitoring of dairy cow body condition, mobility and weight using a single 3D video capture device.
Automated monitoring of dairy cow body condition, mobility and weight using a single 3D video capture device.
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DOI：
10.1016/j.compind.2018.02.011
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发表时间：
2018-06
影响因子：
10
通讯作者：
Forbes D
中科院分区：
文献类型：
--
作者：
Hansen MF;Smith ML;Smith LN;Abdul Jabbar K;Forbes D
用于同时监测奶牛身体状况、跛行和体重的3D成像。提出了一种用于身体状态评估的新型滚球软件工具。原始的运动脊柱分割/建模方法在三维假设。与手动评分相当或更好的实际性能。讨论了传统评分的局限性，并介绍了一种学习方法。在这里，我们提出了一种低成本的自动化系统，用于农场奶牛的不显眼和连续的福利监测。我们认为，有效和定期监测多种状态特征目前是不可行的，并继续提出3D成像技术，能够获取不同形式的相关动物状态数据（身体状况，跛行和体重），同时使用单个设备。在连续操作的农场条件下获得的结果显示与畜群的人工评分相当或更好。我们还考虑了使用评分的固有局限性，并认为对连续观察的相对变化的敏感性比使用可能被认为是抽象和任意的评分系统提供了更大的好处。
3D imaging for concurrently monitoring cow body condition, lameness and weight. Novel rolling ball software tool is proposed for body condition assessment. Original moving spine segmentation/modelling approach in 3D postulated. Real-world performance that is comparable or better than manual scoring. Limitations of conventional scoring discussed and a learning approach introduced. Here we propose a low-cost automated system for the unobtrusive and continuous welfare monitoring of dairy cattle on the farm. We argue that effective and regular monitoring of multiple condition traits is not currently practicable and go on to propose 3D imaging technology able to acquire differing forms of related animal condition data (body condition, lameness and weight), concurrently using a single device. Results obtained under farm conditions in continuous operation are shown to be comparable or better than manual scoring of the herd. We also consider inherent limitations of using scoring and argue that sensitivity to relative change over successive observations offers greater benefit than the use of what may be considered abstract and arbitrary scoring systems.
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影响因子：
5.1
作者：
Maertens, Willem;Vangeyte, Jurgen;Van Nuffel, Annelies
通讯作者：
Van Nuffel, Annelies
影响因子：
3.5
作者：
FERGUSON, JD;GALLIGAN, DT;THOMSEN, N
通讯作者：
THOMSEN, N
影响因子：
2.6
作者：
Green, L. E.;Huxley, J. N.;Green, M. J.
通讯作者：
Green, M. J.
影响因子：
3.5
作者：
Hoffman, A. C.;Moore, D. A.;Wenz, J. R.
通讯作者：
Wenz, J. R.
影响因子：
8.3
作者：
Cveticanin, D;Wendl, G
通讯作者：
Wendl, G