Computer Vision Applied to Detect Lethargy through Animal Motion Monitoring: A Trial on African Swine Fever in Wild Boar.
Computer Vision Applied to Detect Lethargy through Animal Motion Monitoring: A Trial on African Swine Fever in Wild Boar.
复制标题
计算机视觉应用于通过动物运动监测检测嗜睡：野猪非洲猪瘟试验。
DOI：
10.3390/ani10122241
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发表时间：
2020-11-29
期刊：
影响因子：
--
通讯作者：
Sánchez-Vizcaíno JM
中科院分区：
文献类型：
--
作者：
Fernández-Carrión E;Barasona JÁ;Sánchez Á;Jurado C;Cadenas-Fernández E;Sánchez-Vizcaíno JM
非洲猪瘟威胁着全世界的生猪福利。在其临床症状中，该疾病表现为发烧和虚弱，随后动物活动逐渐减慢。当前计算机视觉的进步使我们能够检测动物、跟踪它们的运动，从而监控动物的活动。在这项工作中，我们使用这项技术在感染非洲猪瘟病毒的动物试验中计算动物运动，并证明当体温升高时运动显着减少。早期发现传染病是疾病监测中降低爆发风险的最具成本效益的策略。最新的深度学习和计算机视觉改进是强大的工具，有可能开辟流行病学和疾病控制的新研究领域。这些技术在这里被用来开发一种旨在实时跟踪和计算动物运动的算法。该算法用于实验试验，以评估欧亚野猪的非洲猪瘟 (ASF) 感染过程。总体而言，结果显示运动减少与 ASF 感染引起的发烧呈负相关。此外，与未感染的动物相比，受感染的动物的运动量显着降低。获得的结果表明，基于人工视觉的运动监测系统可能在室内使用，以引发发烧的怀疑。它将帮助农民和动物卫生服务机构检测与传染病相关的早期临床症状。考虑到当前世界养猪业的担忧，该技术为畜牧业展示了一种有前景的非侵入式、经济且实时的解决方案，特别是非洲猪瘟。
African swine fever threatens pig welfare worldwide. Among its clinical signs, this disease manifests fever and weakness followed by progressive deceleration in the animal activities. The current computer vision advances allow us to detect animals, to track their movements and, therefore, to monitor animal activity. In this work, we used this technology to compute animal motion in a trial with animals infected with African swine fever virus, and proved a significant reduction in motion when the body temperature increased. Early detection of infectious diseases is the most cost-effective strategy in disease surveillance for reducing the risk of outbreaks. Latest deep learning and computer vision improvements are powerful tools that potentially open up a new field of research in epidemiology and disease control. These techniques were used here to develop an algorithm aimed to track and compute animal motion in real time. This algorithm was used in experimental trials in order to assess African swine fever (ASF) infection course in Eurasian wild boar. Overall, the outcomes showed negative correlation between motion reduction and fever caused by ASF infection. In addition, infected animals computed significant lower movements compared to uninfected animals. The obtained results suggest that a motion monitoring system based on artificial vision may be used in indoors to trigger suspicions of fever. It would help farmers and animal health services to detect early clinical signs compatible with infectious diseases. This technology shows a promising non-intrusive, economic and real time solution in the livestock industry with especial interest in ASF, considering the current concern in the world pig industry.
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影响因子：
3.7
作者：
Fernández-Carrión E;Martínez-Avilés M;Ivorra B;Martínez-López B;Ramos ÁM;Sánchez-Vizcaíno JM
通讯作者：
Sánchez-Vizcaíno JM
影响因子：
4.3
作者：
Martinez-Aviles, M.;Fernandez-Carrion, E.;Sanchez-Vizcaino, J. M.
通讯作者：
Sanchez-Vizcaino, J. M.
影响因子：
4.3
作者：
Zhou, Xintao;Li, Nan;Hu, Rongliang
通讯作者：
Hu, Rongliang
影响因子：
19.5
作者：
Russakovsky, Olga;Deng, Jia;Fei-Fei, Li
通讯作者：
Fei-Fei, Li
影响因子：
2.4
作者：
LUO, PF;CHAO, YJ;PETERS, WH
通讯作者：
PETERS, WH