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A computer vision-based approach for respiration rate monitoring of group housed pigs

文献类型： 外文期刊

作者： Wang, Meiqing 1 ; Li, Xue 1 ; Larsen, Mona L. V. 1 ; Liu, Dong 1 ; Rault, Jean-Loup 5 ; Norton, Tomas 1 ;

作者机构： 1.Katholieke Univ Leuven KU LEUVEN, Fac Biosci Engn, Kasteelpark Arenberg 30, B-3001 Heverlee, Belgium

2.Swiss Fed Inst Technol, Inst Agr Sci, Anim Nutr, Univ Str 2, CH-8092 Zurich, Switzerland

3.Jiangsu Acad Agr Sci, Inst Agr Facil & Equipment, Nanjing 210014, Peoples R China

4.Aarhus Univ, Dept Anim Sci, Blichers Alle 20, DK-8830 Aarhus, Denmark

5.Univ Vet Med Vetmeduni Vienna, Inst Anim Welf Sci ITT, A-1210 Vienna, Austria

关键词： Physiological monitoring; Oriented object detection; RGB video; Breathing; Animal welfare

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：8.3； 五年影响因子：8.3 ）

ISSN： 0168-1699

年卷期： 2023 年 210 卷

页码：

收录情况： SCI

摘要： In recent years, respiration rate (RR) monitoring using video data has been explored by researchers with rela-tively good success. However, the approaches used so far require the manual identification of the region of interest (ROI) in the image of the animal. When monitoring farm animals, typically housed in groups, such manual actions would entail an excessive time investment and increase the level of subjectivity in the application of the method. The aim of this study was to design a RR monitoring system targeted at group-housed animal applications. The developed system first selected video clips where pigs were in a resting status. Then an oriented object detector was used to detect each animal and select the ROI without manual intervention. Finally the RR is estimated by analyzing the time-varying features extracted from the ROI. Videos of group-housed pigs were collected to test the method, in which 5 pigs were included. Four pigs wore an ECG belt around the abdomen to collect the gold standard (GS) RR measures while a control pig did not wear a belt, with the GS for the control pig obtained through manually observation. The comparison between RR obtained by the computer vision (CV) method and the GS showed good agreement with a mean absolute error of 2.38 breath per minute (bpm) in the 4 pigs wearing belts and 1.72 bpm in the control pig, a root mean square error of 3.46 bpm in the 4 pigs wearing belts and 2.26 bpm in the control pig, and a correlation coefficient of 0.92 in the 4 pigs wearing belts and 0.95 in the control pig.

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