The estimation of broiler respiration rate based on the semantic segmentation and video amplification
Respiratory rate is an indicator of a broilers’ stress and health status, thus, it is essential to detect respiratory rate contactless and stress-freely. This study proposed an estimation method of broiler respiratory rate by deep learning and machine vision. Experiments were performed at New Hope (...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-12-01
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| Series: | Frontiers in Physics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2022.1047077/full |
| _version_ | 1797979818998890496 |
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| author | Jintao Wang Jintao Wang Longshen Liu Mingzhou Lu Cedric Okinda Cedric Okinda Daniela Lovarelli Marcella Guarino Mingxia Shen |
| author_facet | Jintao Wang Jintao Wang Longshen Liu Mingzhou Lu Cedric Okinda Cedric Okinda Daniela Lovarelli Marcella Guarino Mingxia Shen |
| author_sort | Jintao Wang |
| collection | DOAJ |
| description | Respiratory rate is an indicator of a broilers’ stress and health status, thus, it is essential to detect respiratory rate contactless and stress-freely. This study proposed an estimation method of broiler respiratory rate by deep learning and machine vision. Experiments were performed at New Hope (Shandong Province, P. R. China) and Wen’s group (Guangdong Province, P. R. China), and a total of 300 min of video data were collected. By separating video frames, a data set of 3,000 images was made, and two semantic segmentation models were trained. The single-channel Euler video magnification algorithm was used to amplify the belly fluctuation of the broiler, which saved 55% operation time compared with the traditional Eulerian video magnification algorithm. The contour features significantly related to respiration were used to obtain the signals that could estimate broilers’ respiratory rate. Detrending and band-pass filtering eliminated the influence of broiler posture conversion and motion on the signal. The mean absolute error, root mean square error, average accuracy of the proposed respiratory rate estimation technique for broilers were 3.72%, 16.92%, and 92.19%, respectively. |
| first_indexed | 2024-04-11T05:45:55Z |
| format | Article |
| id | doaj.art-939689e5f90041d69def3bcddccba446 |
| institution | Directory Open Access Journal |
| issn | 2296-424X |
| language | English |
| last_indexed | 2024-04-11T05:45:55Z |
| publishDate | 2022-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physics |
| spelling | doaj.art-939689e5f90041d69def3bcddccba4462022-12-22T04:42:15ZengFrontiers Media S.A.Frontiers in Physics2296-424X2022-12-011010.3389/fphy.2022.10470771047077The estimation of broiler respiration rate based on the semantic segmentation and video amplificationJintao Wang0Jintao Wang1Longshen Liu2Mingzhou Lu3Cedric Okinda4Cedric Okinda5Daniela Lovarelli6Marcella Guarino7Mingxia Shen8School of Mechanical and Power Engineering, Henan Polytechnic University, Jiaozuo, Henan, ChinaLaboratory of Modern Facility Agriculture Technology and Equipment Engineering of Jiangsu Province, College of Engineering, Nanjing Agricultural University, Nanjing, Jiangsu, ChinaLaboratory of Modern Facility Agriculture Technology and Equipment Engineering of Jiangsu Province, College of Engineering, Nanjing Agricultural University, Nanjing, Jiangsu, ChinaLaboratory of Modern Facility Agriculture Technology and Equipment Engineering of Jiangsu Province, College of Engineering, Nanjing Agricultural University, Nanjing, Jiangsu, ChinaLaboratory of Modern Facility Agriculture Technology and Equipment Engineering of Jiangsu Province, College of Engineering, Nanjing Agricultural University, Nanjing, Jiangsu, ChinaDepartment of Electrical and Communications Engineering, School of Engineering and Built Environment, Masinde Muliro University of Science and Technology, Kakamega, KenyaDepartment of Science and Environmental Policy, University of Milan, Milan, ItalyDepartment of Science and Environmental Policy, University of Milan, Milan, ItalyLaboratory of Modern Facility Agriculture Technology and Equipment Engineering of Jiangsu Province, College of Engineering, Nanjing Agricultural University, Nanjing, Jiangsu, ChinaRespiratory rate is an indicator of a broilers’ stress and health status, thus, it is essential to detect respiratory rate contactless and stress-freely. This study proposed an estimation method of broiler respiratory rate by deep learning and machine vision. Experiments were performed at New Hope (Shandong Province, P. R. China) and Wen’s group (Guangdong Province, P. R. China), and a total of 300 min of video data were collected. By separating video frames, a data set of 3,000 images was made, and two semantic segmentation models were trained. The single-channel Euler video magnification algorithm was used to amplify the belly fluctuation of the broiler, which saved 55% operation time compared with the traditional Eulerian video magnification algorithm. The contour features significantly related to respiration were used to obtain the signals that could estimate broilers’ respiratory rate. Detrending and band-pass filtering eliminated the influence of broiler posture conversion and motion on the signal. The mean absolute error, root mean square error, average accuracy of the proposed respiratory rate estimation technique for broilers were 3.72%, 16.92%, and 92.19%, respectively.https://www.frontiersin.org/articles/10.3389/fphy.2022.1047077/fullbroilerrespiration ratecomputer visionsemantic segmentationEuler video magnification |
| spellingShingle | Jintao Wang Jintao Wang Longshen Liu Mingzhou Lu Cedric Okinda Cedric Okinda Daniela Lovarelli Marcella Guarino Mingxia Shen The estimation of broiler respiration rate based on the semantic segmentation and video amplification Frontiers in Physics broiler respiration rate computer vision semantic segmentation Euler video magnification |
| title | The estimation of broiler respiration rate based on the semantic segmentation and video amplification |
| title_full | The estimation of broiler respiration rate based on the semantic segmentation and video amplification |
| title_fullStr | The estimation of broiler respiration rate based on the semantic segmentation and video amplification |
| title_full_unstemmed | The estimation of broiler respiration rate based on the semantic segmentation and video amplification |
| title_short | The estimation of broiler respiration rate based on the semantic segmentation and video amplification |
| title_sort | estimation of broiler respiration rate based on the semantic segmentation and video amplification |
| topic | broiler respiration rate computer vision semantic segmentation Euler video magnification |
| url | https://www.frontiersin.org/articles/10.3389/fphy.2022.1047077/full |
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