Equivalence Between Optical Flow, the Unrest Index, and Walking Distance to Estimate the Welfare of Broiler Chickens
Modern poultry production demands scalable and non-invasive methods to monitor animal welfare, particularly as broiler strains are increasingly bred for rapid growth, often at the expense of mobility and health. This study evaluates two advanced computer vision techniques—Optical Flow and the Unrest...
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MDPI AG
2025-05-01
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| author | Danilo Florentino Pereira Irenilza de Alencar Nääs Saman Abdanan Mehdizadeh |
| author_facet | Danilo Florentino Pereira Irenilza de Alencar Nääs Saman Abdanan Mehdizadeh |
| author_sort | Danilo Florentino Pereira |
| collection | DOAJ |
| description | Modern poultry production demands scalable and non-invasive methods to monitor animal welfare, particularly as broiler strains are increasingly bred for rapid growth, often at the expense of mobility and health. This study evaluates two advanced computer vision techniques—Optical Flow and the Unrest Index—to assess movement patterns in broiler chickens. Three commercial broiler strains (Hybro<sup>®</sup>, Cobb<sup>®</sup>, and Ross<sup>®</sup>) were housed in controlled environments and continuously monitored using ceiling-mounted video systems. Chicken movements were detected and tracked using a YOLO model, with centroid data informing both the Unrest Index and distance walked metrics. Optical Flow velocity metrics (mean, variance, skewness, and kurtosis) were extracted using the Farnebäck algorithm. Pearson correlation analyses revealed strong associations between Optical Flow variables and traditional movement indicators, with average velocity showing the strongest correlation to walked distance and the Unrest Index. Among the evaluated strains, Cobb<sup>®</sup> demonstrated the strongest correlation between Optical Flow variance and the Unrest Index, indicating a distinct movement profile. The equipment’s movement and the camera’s slight instability had a minimal effect on the Optical Flow measurement. Still, its strong correlation with the Unrest Index and walking distance accredits it as an effective method for high-resolution behavioral monitoring. This study supports the integration of Optical Flow and Unrest Index technologies into precision livestock systems, offering a foundation for predictive welfare management at scale. |
| format | Article |
| id | doaj-art-35eb4be0701543f38de8a8631b3a74b9 |
| institution | DOAJ |
| issn | 2076-2615 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
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| series | Animals |
| spelling | doaj-art-35eb4be0701543f38de8a8631b3a74b92025-08-20T02:58:43ZengMDPI AGAnimals2076-26152025-05-01159131110.3390/ani15091311Equivalence Between Optical Flow, the Unrest Index, and Walking Distance to Estimate the Welfare of Broiler ChickensDanilo Florentino Pereira0Irenilza de Alencar Nääs1Saman Abdanan Mehdizadeh2Department of Management, Development and Technology, School of Science and Engineering, Sao Paulo State University, Tupã 17602-496, SP, BrazilGraduate Program in Production Engineering, Paulista University—UNIP, São Paulo 04026-002, SP, BrazilDepartment of Mechanics of Biosystems Engineering, Faculty of Agricultural Engineering and Rural Development, Agricultural Sciences and Natural Resources University of Khuzestan, Ahvaz 63417-73637, IranModern poultry production demands scalable and non-invasive methods to monitor animal welfare, particularly as broiler strains are increasingly bred for rapid growth, often at the expense of mobility and health. This study evaluates two advanced computer vision techniques—Optical Flow and the Unrest Index—to assess movement patterns in broiler chickens. Three commercial broiler strains (Hybro<sup>®</sup>, Cobb<sup>®</sup>, and Ross<sup>®</sup>) were housed in controlled environments and continuously monitored using ceiling-mounted video systems. Chicken movements were detected and tracked using a YOLO model, with centroid data informing both the Unrest Index and distance walked metrics. Optical Flow velocity metrics (mean, variance, skewness, and kurtosis) were extracted using the Farnebäck algorithm. Pearson correlation analyses revealed strong associations between Optical Flow variables and traditional movement indicators, with average velocity showing the strongest correlation to walked distance and the Unrest Index. Among the evaluated strains, Cobb<sup>®</sup> demonstrated the strongest correlation between Optical Flow variance and the Unrest Index, indicating a distinct movement profile. The equipment’s movement and the camera’s slight instability had a minimal effect on the Optical Flow measurement. Still, its strong correlation with the Unrest Index and walking distance accredits it as an effective method for high-resolution behavioral monitoring. This study supports the integration of Optical Flow and Unrest Index technologies into precision livestock systems, offering a foundation for predictive welfare management at scale.https://www.mdpi.com/2076-2615/15/9/1311machine visionmovement analysisprecision livestock farmingunrest indexYOLO |
| spellingShingle | Danilo Florentino Pereira Irenilza de Alencar Nääs Saman Abdanan Mehdizadeh Equivalence Between Optical Flow, the Unrest Index, and Walking Distance to Estimate the Welfare of Broiler Chickens Animals machine vision movement analysis precision livestock farming unrest index YOLO |
| title | Equivalence Between Optical Flow, the Unrest Index, and Walking Distance to Estimate the Welfare of Broiler Chickens |
| title_full | Equivalence Between Optical Flow, the Unrest Index, and Walking Distance to Estimate the Welfare of Broiler Chickens |
| title_fullStr | Equivalence Between Optical Flow, the Unrest Index, and Walking Distance to Estimate the Welfare of Broiler Chickens |
| title_full_unstemmed | Equivalence Between Optical Flow, the Unrest Index, and Walking Distance to Estimate the Welfare of Broiler Chickens |
| title_short | Equivalence Between Optical Flow, the Unrest Index, and Walking Distance to Estimate the Welfare of Broiler Chickens |
| title_sort | equivalence between optical flow the unrest index and walking distance to estimate the welfare of broiler chickens |
| topic | machine vision movement analysis precision livestock farming unrest index YOLO |
| url | https://www.mdpi.com/2076-2615/15/9/1311 |
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