BroilerTrack: Automatic multi-camera multi-broiler tracking
Efficient and continuous tracking of individual broilers is critical for improving poultry management, welfare, and breeding decisions in commercial settings. However, standard Multi-Object Tracking (MOT) techniques face significant challenges in poultry environments due to occlusions, high object s...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-12-01
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| Series: | Smart Agricultural Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S277237552500543X |
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| _version_ | 1849228270902444032 |
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| author | Thinh Phan Hoang Kim Tran Andrew Lockett Isaac Phillips Hao Vo Duy Le Michael T. Kidd James Mason Santiago Avendano Ngan Le |
| author_facet | Thinh Phan Hoang Kim Tran Andrew Lockett Isaac Phillips Hao Vo Duy Le Michael T. Kidd James Mason Santiago Avendano Ngan Le |
| author_sort | Thinh Phan |
| collection | DOAJ |
| description | Efficient and continuous tracking of individual broilers is critical for improving poultry management, welfare, and breeding decisions in commercial settings. However, standard Multi-Object Tracking (MOT) techniques face significant challenges in poultry environments due to occlusions, high object similarity, and dense flocks.In this work, we introduce BroilerTrack, a novel multi-camera multi-broiler tracking framework tailored for the poultry industry. Unlike traditional approaches that rely heavily on appearance features, BroilerTrack employs a position-based tracking strategy in a unified coordinate system (unified plane), thereby circumventing identity ambiguity caused by the homogeneous appearance of broilers. Our proposed BroilerTrack system comprises three key modules: Top-view Aggregation, Side-view Distribution, and Identification Assignment, enabling robust identification (ID) consistency across multiple calibrated views. Furthermore, we present a new Multi-View Broiler dataset collected under commercial-like conditions, featuring synchronized footage from six strategically placed cameras (two top-view and four side-view). Notably, our method requires no unified-plane annotations during training and achieves superior performance over state-of-the-art Multi-camera MOT methods on both detection and association metrics. This work provides a scalable, non-intrusive solution for real-time poultry monitoring, with strong potential for applications in behavior analysis, welfare optimization, and automated breeding selection. |
| format | Article |
| id | doaj-art-0611cbfbd4f24824b243b5236ca448d2 |
| institution | Kabale University |
| issn | 2772-3755 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Smart Agricultural Technology |
| spelling | doaj-art-0611cbfbd4f24824b243b5236ca448d22025-08-23T04:49:51ZengElsevierSmart Agricultural Technology2772-37552025-12-011210131210.1016/j.atech.2025.101312BroilerTrack: Automatic multi-camera multi-broiler trackingThinh Phan0Hoang Kim Tran1Andrew Lockett2Isaac Phillips3Hao Vo4Duy Le5Michael T. Kidd6James Mason7Santiago Avendano8Ngan Le9Department of Electrical Engineering & Computer Science, University of Arkansas, Fayetteville, AR, United StatesDepartment of Electrical Engineering & Computer Science, University of Arkansas, Fayetteville, AR, United StatesDepartment of Electrical Engineering & Computer Science, University of Arkansas, Fayetteville, AR, United StatesDepartment of Electrical Engineering & Computer Science, University of Arkansas, Fayetteville, AR, United StatesDepartment of Electrical Engineering & Computer Science, University of Arkansas, Fayetteville, AR, United StatesDepartment of Electrical Engineering & Computer Science, University of Arkansas, Fayetteville, AR, United StatesDepartment of Poultry Science, University of Arkansas, Fayetteville, AR, United StatesAviagen, Huntsville, AL, United StatesAviagen, Huntsville, AL, United StatesDepartment of Electrical Engineering & Computer Science, University of Arkansas, Fayetteville, AR, United States; Corresponding author.Efficient and continuous tracking of individual broilers is critical for improving poultry management, welfare, and breeding decisions in commercial settings. However, standard Multi-Object Tracking (MOT) techniques face significant challenges in poultry environments due to occlusions, high object similarity, and dense flocks.In this work, we introduce BroilerTrack, a novel multi-camera multi-broiler tracking framework tailored for the poultry industry. Unlike traditional approaches that rely heavily on appearance features, BroilerTrack employs a position-based tracking strategy in a unified coordinate system (unified plane), thereby circumventing identity ambiguity caused by the homogeneous appearance of broilers. Our proposed BroilerTrack system comprises three key modules: Top-view Aggregation, Side-view Distribution, and Identification Assignment, enabling robust identification (ID) consistency across multiple calibrated views. Furthermore, we present a new Multi-View Broiler dataset collected under commercial-like conditions, featuring synchronized footage from six strategically placed cameras (two top-view and four side-view). Notably, our method requires no unified-plane annotations during training and achieves superior performance over state-of-the-art Multi-camera MOT methods on both detection and association metrics. This work provides a scalable, non-intrusive solution for real-time poultry monitoring, with strong potential for applications in behavior analysis, welfare optimization, and automated breeding selection.http://www.sciencedirect.com/science/article/pii/S277237552500543XMultiple broiler trackingMulti-camera multi-broiler trackingBroiler monitoringBroiler trackingBroiler detection |
| spellingShingle | Thinh Phan Hoang Kim Tran Andrew Lockett Isaac Phillips Hao Vo Duy Le Michael T. Kidd James Mason Santiago Avendano Ngan Le BroilerTrack: Automatic multi-camera multi-broiler tracking Smart Agricultural Technology Multiple broiler tracking Multi-camera multi-broiler tracking Broiler monitoring Broiler tracking Broiler detection |
| title | BroilerTrack: Automatic multi-camera multi-broiler tracking |
| title_full | BroilerTrack: Automatic multi-camera multi-broiler tracking |
| title_fullStr | BroilerTrack: Automatic multi-camera multi-broiler tracking |
| title_full_unstemmed | BroilerTrack: Automatic multi-camera multi-broiler tracking |
| title_short | BroilerTrack: Automatic multi-camera multi-broiler tracking |
| title_sort | broilertrack automatic multi camera multi broiler tracking |
| topic | Multiple broiler tracking Multi-camera multi-broiler tracking Broiler monitoring Broiler tracking Broiler detection |
| url | http://www.sciencedirect.com/science/article/pii/S277237552500543X |
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