2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDMLR-APPL-IVASR-4.8
Paper Title Turkey Behavior Identification using Video Analytics and Object Tracking
Authors Shengtai Ju, Marisa Erasmus, Fengqing Zhu, Amy Reibman, Purdue University, United States
SessionMLR-APPL-IVASR-4: Machine learning for image and video analysis, synthesis, and retrieval 4
LocationArea B
Session Time:Tuesday, 21 September, 13:30 - 15:00
Presentation Time:Tuesday, 21 September, 13:30 - 15:00
Presentation Poster
Topic Applications of Machine Learning: Machine learning for image & video analysis, synthesis, and retrieval
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract In this paper, we propose a method to identify behavior of experimental turkeys by automatically analyzing video recordings. Monitoring turkey health during production is crucial for improved turkey production. Turkey health can be reflected through their common behavior, and changes in the frequency and duration of their behavior can be used to detect sick turkeys early. Video recordings can be manually annotated to assist identifying turkey behaviors, but this is both time consuming and labor intensive. In this paper, we monitor and detect changes in turkey behavior using video analytics. Behaviors of interest include eating, drinking, preening, and pecking. Identifying these behaviors requires accurate estimates of turkeys' and turkey heads' locations. Re-identification of each turkey is crucial after significant shape deformation such as wing flapping and fast walking. Therefore, our system integrates a state-of-the-art turkey tracker and a head tracker with a behavior identification module to identify turkey behavior. Results demonstrate that our system is effective and accurate at estimating the spatial location of turkeys and their heads, and identifying all behaviors of interest with high recall.